Deutsch Intern
    Data Science Chair

    Publications by Andreas Hotho

    These publications are hosted by BibSonomy. A searchable overview of my publications can be found here.

    2025[ to top ]
    • Modeling and Analyzing the Influence of Non-Item Pages on Sequential Next-Item Prediction E. Fischer; A. Zehe; A. Hotho; D. Schlör in ACM Trans. Recomm. Syst. (2025).
    • Identifying Axiomatic Mathematical Transformation Steps using Tree-Structured Pointer Networks S. Wankerl; J. Pfister; A. Dulny; G. Götz; A. Hotho in Transactions on Machine Learning Research (2025).
    • PreAdapter: Pre-training Language Models on Knowledge Graphs J. Omeliyanenko; A. Hotho; D. Schlör G. Demartini, K. Hose, M. Acosta, M. Palmonari, G. Cheng, H. Skaf-Molli, N. Ferranti, D. Hernández, A. Hogan (Eds.) (2025). 210–226.
    • Exploring Design Choices for Autoregressive Deep Learning Climate Models F. Gallusser; S. Hentschel; A. Krause; A. Hotho (2025).
    • ModernGBERT: German-only 1B Encoder Model Trained from Scratch A. Ehrmanntraut; J. Wunderle; J. Pfister; F. Jannidis; A. Hotho (2025).
    • Enriching Large Language ...
      Enriching Large Language Models with Knowledge Graphs for Computational Literary Studies T. Hagen; J. Omeliyanenko; A. Ehrmanntraut; A. Hotho; A. Zehe; F. Jannidis in Handbook on Neurosymbolic AI and Knowledge Graphs (2025).
    2024[ to top ]
    • Modeling and Analyzing the Influence of Non-Item Pages on Sequential Next-Item Prediction E. Fischer; D. Schlör; A. Zehe; A. Hotho in CoRR (2024). abs/2408.15953
    • From Chat to Publication Management: Organizing your related work using BibSonomy \& LLMs T. Völker; J. Pfister; T. Koopmann; A. Hotho P. D. Clough, M. Harvey, F. Hopfgartner (Eds.) (2024). 386–390.
    • GrINd: Grid Interpolation Network for Scattered Observations A. Dulny; P. Heinisch; A. Hotho; A. Krause in Lecture Notes in Computer Science, A. Bifet, J. Davis, T. Krilavicius, M. Kull, E. Ntoutsi, I. Zliobaite (Eds.) (2024). (Vol. 14947) 177–193.
    • Effects of AI understanding-training on AI literacy, usage, self-determined interactions, and anthropomorphization with voice assistants A. Markus; J. Pfister; C. Carolus; A. Hotho; C. Wienrich in Computers and Education Open (2024). 6(1) 100176.
    • ModeConv: A Novel Convolution for Distinguishing Anomalous and Normal Structural Behavior M. Schaller; D. Schlör; A. Hotho in CoRR (2024). abs/2407.00140
    • LLäMmlein: Compact and Competitive German-Only Language Models from Scratch J. Pfister; J. Wunderle; A. Hotho in CoRR (2024). abs/2411.11171
    • Verantwortungsvolle Empfehlungssysteme für die medizinische Diagnostik D. Schlör; A. Hotho in Edition Moderne Postmoderne (2024). 101.
    • Towards the development of an automated robotic storyteller: comparing approaches for emotional story annotation for non-verbal expression via body language S. C. Steinhaeusser; A. Zehe; P. Schnetter; A. Hotho; B. Lugrin in J. Multimodal User Interfaces (2024). 18(4) 1–23.
    • Pollice Verso at SemEval-2024 Task 6: The Roman Empire Strikes Back K. Kobs; J. Pfister; A. Hotho A. K. Ojha, A. S. Dogruöz, H. T. Madabushi, G. D. S. Martino, S. Rosenthal, A. Rosá (Eds.) (2024). 1529–1536.
    • Systematic Evaluation of Synthetic Data Augmentation for Multi-class NetFlow Traffic M. Wolf; D. Landes; A. Hotho; D. Schlör in CoRR (2024). abs/2408.16034
    • BibSonomy Meets ChatLLMs for Publication Management: From Chat to Publication Management: Organizing your related work using BibSonomy \& LLMs T. Völker; J. Pfister; T. Koopmann; A. Hotho in CoRR (2024). abs/2401.09092
    • OtterlyObsessedWithSemantics at SemEval-2024 Task 4: Developing a Hierarchical Multi-Label Classification Head for Large Language Models J. Wunderle; J. Schubert; A. Cacciatore; A. Zehe; J. Pfister; A. Hotho A. K. Ojha, A. S. Dogruöz, H. T. Madabushi, G. D. S. Martino, S. Rosenthal, A. Rosá (Eds.) (2024). 602–612.
    • KI 2024: Advances in Artificial Intelligence - 47th German Conference on AI, Würzburg, Germany, September 25-27, 2024, Proceedings A. Hotho; S. Rudolph in Lecture Notes in Computer Science (2024). (Vol. 14992) Springer.
    • Generative Inpainting for Shapley-Value-Based Anomaly Explanation J. Tritscher; P. Lissmann; M. Wolf; A. Krause; A. Hotho; D. Schlör in Communications in Computer and Information Science, L. Longo, S. Lapuschkin, C. Seifert (Eds.) (2024). (Vol. 2153) 230–243.
    • CompTrails: comparing hyp...
      CompTrails: comparing hypotheses across behavioral networks T. Koopmann; M. Becker; F. Lemmerich; A. Hotho in Data Mining and Knowledge Discovery (2024).
    • Benchmarking of synthetic network data: Reviewing challenges and approaches M. Wolf; J. Tritscher; D. Landes; A. Hotho; D. Schlör in Comput. Secur. (2024). 145 103993.
    • Global Vegetation Modeling with Pre-Trained Weather Transformers P. Janetzky; F. Gallusser; S. Hentschel; A. Hotho; A. Krause in CoRR (2024). abs/2403.18438
    • IMU Airtime Detection in Snowboard Halfpipe: U-Net Deep Learning Approach Outperforms Traditional Threshold Algorithms T. Gorges; P. Davidson; M. Boeschen; A. Hotho; C. Merz in Sensors (2024). 24(21)
    • Empower the user - The impact of functional understanding training on usage, social perception, and self-determined interactions with intelligent voice assistants A. Markus; J. Pfister; A. Carolus; A. Hotho; C. Wienrich in Comput. Educ. Artif. Intell. (2024). 6 100229.
    • Data Generation for Explainable Occupational Fraud Detection J. Tritscher; M. Wolf; A. Krause; A. Hotho; D. Schlör in Lecture Notes in Computer Science, A. Hotho, S. Rudolph (Eds.) (2024). (Vol. 14992) 246–259.
    • GrINd: Grid Interpolation Network for Scattered Observations A. Dulny; P. Heinisch; A. Hotho; A. Krause (2024).
    • Adapting Sequential Recommender Models to Content Recommendation in Chat Data using Non-Item Page-Models A. Zehe; E. Fischer; J. Kaiser; T. Wagner; A. Hotho in CEUR Workshop Proceedings, V. W. Anelli, P. Basile, T. D. Noia, F. M. Donini, A. Ferrara, C. Musto, F. Narducci, A. Ragone, M. Zanker (Eds.) (2024). (Vol. 3817) 66–84.
    • Resources for Graph Data and Knowledge A. Hogan; I. Horrocks; A. Hotho; L. Kagal; U. Sattler in TGDK (2024). 2(2) 1:1–1:2.
    • SuperGLEBer: German Language Understanding Evaluation Benchmark J. Pfister; A. Hotho K. Duh, H. Gómez-Adorno, S. Bethard (Eds.) (2024). 7904–7923.
    • Marina: Realizing ML-Driv...
      Marina: Realizing ML-Driven Real-Time Network Traffic Monitoring at Terabit Scale M. Seufert; K. Dietz; N. Wehner; S. Geißler; J. Schüler; M. Wolz; A. Hotho; P. Casas; T. Hoßfeld; A. Feldmann in IEEE Transactions on Network and Service Management (2024). 1–1.
    2023[ to top ]
    • Optimizing Medical Servic...
      Optimizing Medical Service Request Processes through Language Modeling and Semantic Search D. Schlör; J. Pfister; A. Hotho in ICMHI 2023 (2023). 136–141.
    • Enhancing Sequential Next...
      Enhancing Sequential Next-Item Prediction through Modelling Non-Item Pages E. Fischer; D. Schlör; A. Zehe; A. Hotho (2023).
    • Long-Term Effects of Perceived Friendship with Intelligent Voice Assistants on Usage Behavior, User Experience, and Social Perceptions C. Wienrich; A. Carolus; A. Markus; Y. Augustin; J. Pfister; A. Hotho in Computers (2023). 12(4)
    • Can Neural Networks Distinguish High-school Level Mathematical Concepts? S. Wankerl; A. Dulny; G. Goetz; A. Hotho (2023).
    • Higher-Order DeepTrails: Unified Approach to *Trails T. Koopmann; J. Pfister; A. Markus; A. Carolus; C. Wienrich; A. Hotho in CEUR Workshop Proceedings, M. Leyer, J. Wichmann (Eds.) (2023).
    • TaylorPDENet: Learning PDEs from non-grid Data P. Heinisch; A. Dulny; A. Krause; A. Hotho (2023).
    • DynaBench: A Benchmark Dataset for Learning Dynamical Systems from Low-Resolution Data A. Dulny; A. Hotho; A. Krause D. Koutra, C. Plant, M. Gomez Rodriguez, E. Baralis, F. Bonchi (Eds.) (2023). 438–455.
    • ConvMOS: climate model ou...
      ConvMOS: climate model output statistics with deep learning M. Steininger; D. Abel; K. Ziegler; A. Krause; H. Paeth; A. Hotho in Data Mining and Knowledge Discovery (2023). 37(1) 136–166.
    • Swarming Detection in Smart Beehives Using Auto Encoders for Audio Data P. Janetzky; M. Schaller; A. Krause; A. Hotho (2023). 1–5.
    • Evaluating feature relevance XAI in network intrusion detection J. Tritscher; M. Wolf; A. Hotho; D. Schlör in The World Conference on eXplainable Artificial Intelligence (xAI 2023) - to appear (2023).
    • Automatic Speech Detection on a Smart Beehive’s Raspberry Pi P. Janetzky; P. Lissmann; A. Hotho; A. Krause (2023).
    • CapsKG: Enabling Continual Knowledge Integration in Language Models for Automatic Knowledge Graph Completion J. Omeliyanenko; A. Zehe; A. Hotho; D. Schlör in International Semantic Web Conference ISWC 2023, to appear (2023).
    • Towards a Computational A...
      Towards a Computational Analysis of Suspense: Detecting Dangerous Situations A. Zehe; J. Schröter; A. Hotho (2023).
    • Occupational Fraud Detection through Agent-based Data Generation J. Tritscher; A. Roos; D. Schlör; A. Hotho; A. Krause in The 8th Workshop on MIning DAta for financial applicationS MIDAS 2023 - to appear (2023).
    • Feature relevance XAI in anomaly detection: Reviewing approaches and challenges J. Tritscher; A. Krause; A. Hotho in Frontiers in Artificial Intelligence (2023). 6
    • Zero-Shot Clickbait Spoiling by Rephrasing Titles as Questions D. Wangsadirdja; J. Pfister; K. Kobs; A. Hotho (2023). 1090–1095.
    • Liquor-HGNN: A heterogeneous graph neural network for leakage detection in water distribution networks M. "Schaller; M. "Steininger; A. "Dulny; D. "Schlör; A. "Hotho in LWDA’23: Lernen, Wissen, Daten, Analysen. October 09--11, 2023, Marburg, Germany, (M. Leyer, Ed.) (2023).
    2022[ to top ]
    • On Background Bias in Deep Metric Learning K. Kobs; A. Hotho in CoRR (2022). abs/2210.01615
    • One Graph to Rule them All: Using NLP and Graph Neural Networks to analyse Tolkien’s Legendarium V. Perri; L. Qarkaxhija; A. Zehe; A. Hotho; I. Scholtes in CEUR Workshop Proceedings, F. Karsdorp, K. L. Nielbo (Eds.) (2022). (Vol. 3290) 291–317.
    • Semi-unsupervised Learning for Time Series Classification P. Davidson; M. Steininger; A. Huhn; A. Krause; A. Hotho in CoRR (2022). abs/2207.03119
    • Open ERP System Data For Occupational Fraud Detection J. Tritscher; F. Gwinner; D. Schlör; A. Krause; A. Hotho in arxiv (2022).
    • Anomaly Detection in Beehives: An Algorithm Comparison P. Davidson; M. Steininger; F. Lautenschlager; A. Krause; A. Hotho A. Ahrens, R. V. Prasad, C. Benavente-Peces, N. Ansari (Eds.) (2022). 1–20.
    • The Impact of Different System Call Representations on Intrusion Detection S. Wunderlich; M. Ring; D. Landes; A. Hotho in Log. J. IGPL (2022). 30(2) 239–251.
    • Comparison of Data Representations and Machine Learning Architectures for User Identification on Arbitrary Motion Sequences C. Schell; A. Hotho; M. E. Latoschik in CoRR (2022). abs/2210.00527
    • CLIP knows image aesthetics S. Hentschel; K. Kobs; A. Hotho in Frontiers in artificial intelligence (2022). 5 976235.
    • On Learning Hierarchical Embeddings from Encrypted Network Traffic N. Wehner; M. Ring; J. Schüler; A. Hotho; T. Hoßfeld; M. Seufert (2022). 1–7.
    • SenPoi at SemEval-2022 Task 10: Point me to your Opinion, SenPoi J. Pfister; S. Wankerl; A. Hotho G. Emerson, N. Schluter, G. Stanovsky, R. Kumar, A. Palmer, N. Schneider, S. Singh, S. Ratan (Eds.) (2022). 1313–1323.
    • Do Different Deep Metric Learning Losses Lead to Similar Learned Features? K. Kobs; M. Steininger; A. Dulny; A. Hotho in CoRR (2022). abs/2205.02698
    • WueDevils at SemEval-2022 Task 8: Multilingual News Article Similarity via Pair-Wise Sentence Similarity Matrices D. Wangsadirdja; F. Heinickel; S. Trapp; A. Zehe; K. Kobs; A. Hotho (2022). 1235–1243.
    • Point me to your Opinion, SenPoi J. Pfister; S. Wankerl; A. Hotho (2022). 1313–1323.
    • Semi-unsupervised Learning for Time Series Classification P. Davidson; M. Steininger; A. Huhn; A. Krause; A. Hotho in Milets@KDD (2022).
    • LSX team5 at SemEval-2022 Task 8: Multilingual News Article Similarity Assessment based on Word- and Sentence Mover’s Distance S. Heil; K. Kopp; A. Zehe; K. Kobs; A. Hotho (2022). 1190–1195.
    • InDiReCT: Language-Guided...
      InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for Images K. Kobs; M. Steininger; A. Hotho (2022).
    • Sequential Item Recommendation in the MOBA Game Dota 2 A. Dallmann; J. Kohlmann; D. Zoller; A. Hotho in CoRR (2022). abs/2201.08724
    • Towards Responsible Medical Diagnostics Recommendation Systems D. Schlör; A. Hotho in CoRR (2022). abs/2209.03760
    • NeuralPDE: Modelling Dynamical Systems from Data A. Dulny; A. Hotho; A. Krause in Lecture Notes in Computer Science, R. Bergmann, L. Malburg, S. C. Rodermund, I. J. Timm (Eds.) (2022). (Vol. 13404) 75–89.
    2021[ to top ]
    • Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research T. Koopmann; M. Stubbemann; M. Kapa; M. Paris; G. Buenstorf; T. Hanika; A. Hotho; R. Jäschke; G. Stumme in Scientometrics (2021).
    • Density-based weighting f...
      Density-based weighting for imbalanced regression M. Steininger; K. Kobs; P. Davidson; A. Krause; A. Hotho in Machine Learning, (A. Appice; S. Escalera; J. A. Gamez; H. Trautmann, Eds.) (2021).
    • A financial game with opportunities for fraud J. Tritscher; A. Krause; D. Schlör; F. Gwinner; S. von Mammen; A. Hotho (2021). 1–5.
    • Anomaly Detection in Beehives: An Algorithm Comparison P. Davidson; M. Steininger; F. Lautenschlager; A. Krause; A. Hotho (2021).
    • Detecting Presence Of Speech In Acoustic Data Obtained From Beehives P. Janetzky; P. Davidson; M. Steininger; A. Krause; A. Hotho F. Font, A. Mesaros, D. P. W. Ellis, E. Fonseca, M. Fuentes, B. Elizalde (Eds.) (2021). 26–30.
    • NeuralPDE: Modelling Dynamical Systems from Data A. Dulny; A. Hotho; A. Krause (2021).
    • Semi-Supervised Learning for Grain Size Distribution Interpolation K. Kobs; C. Schäfer; M. Steininger; A. Krause; R. Baumhauer; H. Paeth; A. Hotho (2021). 34–44.
    • Malware detection on windows audit logs using LSTMs M. Ring; D. Schlör; S. Wunderlich; D. Landes; A. Hotho in Computers & Security (2021). 109 102389.
    • A financial game with opportunities for fraud J. Tritscher; A. Krause; D. Schlör; F. Gwinner; S. von Mammen; A. Hotho in IEE COG 2021 (2021). 2021
    • Semi-unsupervised Learning: An In-depth Parameter Analysis P. Davidson; F. Buckermann; M. Steininger; A. Krause; A. Hotho S. Edelkamp, R. Möller, E. Rueckert (Eds.) (2021). 51–66.
    • The Semantic Web - ISWC 2021 - 20th International Semantic Web Conference, ISWC 2021, Virtual Event, October 24-28, 2021, Proceedings A. Hotho; E. Blomqvist; S. Dietze; A. Fokoue; Y. Ding; P. M. Barnaghi; A. Haller; M. Dragoni; H. Alani in Lecture Notes in Computer Science (2021). (Vol. 12922) Springer.
    • Detecting Scenes in Ficti...
      Detecting Scenes in Fiction: A new Segmentation Task A. Zehe; L. Konle; L. Dümpelmann; E. Gius; A. Hotho; F. Jannidis; L. Kaufmann; M. Krug; F. Puppe; N. Reiter; A. Schreiber; N. Wiedmer (2021).
    • Do Different Deep Metric Learning Losses Lead to Similar Learned Features? K. Kobs; M. Steininger; A. Dulny; A. Hotho in Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) (2021). 10644–10654.
    • Shared Task on Scene Segmentation @ KONVENS 2021 A. Zehe; L. Konle; S. Guhr; L. Dümpelmann; E. Gius; A. Hotho; F. Jannidis; L. Kaufmann; M. Krug; F. Puppe; N. Reiter; A. Schreiber (2021). 1–21.
    • CoBERT: Scientific Collab...
      CoBERT: Scientific Collaboration Prediction via Sequential Recommendation T. Koopmann; K. Kobs; K. Herud; A. Hotho (2021). 45–54.
    • Sequential Item Recommendation in the MOBA Game Dota 2 A. Dallmann; J. Kohlmann; D. Zoller; A. Hotho (2021). 10–17.
    • Learning Mathematical Relations Using Deep Tree Models S. Wankerl; A. Dulny; G. Götz; A. Hotho (2021). 1681–1687.
    • A Case Study on Sampling ...
      A Case Study on Sampling Strategies for Evaluating Neural Sequential Item Recommendation Models A. Dallmann; D. Zoller; A. Hotho (2021).
    • Comparison of Transformer...
      Comparison of Transformer-Based Sequential Product Recommendation Models for the Coveo Data Challenge E. Fischer; D. Zoller; A. Hotho in SIGIR Workshop On eCommerce (2021).
    • Self-Supervised Multi-Task Pretraining Improves Image Aesthetic Assessment J. Pfister; K. Kobs; A. Hotho (2021). 816–825.
    • Assessing Media Bias in Cross-Linguistic and Cross-National Populations A. Sales; A. Zehe; L. B. Marinho; A. Veloso; A. Hotho; J. Omeliyanenko in Proceedings of the International AAAI Conference on Web and Social Media (2021). 15(1) 561–572.
    • Evaluating the multi-task learning approach for land use regression modelling of air pollution A. Dulny; M. Steininger; F. Lautenschlager; A. Krause; A. Hotho in Journal of Physics: Conference Series (2021). 1834(1) 012004.
    2020[ to top ]
    • OpenLUR: Off-the-shelf air pollution modeling with open features and machine learning F. Lautenschlager; M. Becker; K. Kobs; M. Steininger; P. Davidson; A. Krause; A. Hotho in Atmospheric Environment (2020). 233 117535.
    • LM4KG: Improving Common S...
      LM4KG: Improving Common Sense Knowledge Graphs with Language Models J. Omeliyanenko; A. Zehe; L. Hettinger; A. Hotho J. Z. Pan, V. Tamma, C. d’Amato, K. Janowicz, B. Fu, A. Polleres, O. Seneviratne, L. Kagal (Eds.) (2020). 456–473.
    • Evaluating the multi-task learning approach for land use regression modelling of air pollution A. Dulny; M. Steininger; F. Lautenschlager; A. Krause; A. Hotho (2020).
    • Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part I U. Brefeld; Élisa Fromont; A. Hotho; A. J. Knobbe; M. H. Maathuis; C. Robardet in Lecture Notes in Computer Science (2020). (Vol. 11906) Springer.
    • Deep Learning for Climate...
      Deep Learning for Climate Model Output Statistics M. Steininger; D. Abel; K. Ziegler; A. Krause; H. Paeth; A. Hotho in Tackling Climate Change with Machine Learning Workshop at NeurIPS 2020 (2020).
    • Towards Predicting the Subscription Status of Twitch.tv Users K. Kobs; M. Potthast; M. Wiegmann; A. Zehe; B. Stein; A. Hotho in Proceedings of ECML-PKDD 2020 ChAT Discovery Challenge on Chat Analytics for Twitch (2020).
    • Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part II U. Brefeld; Élisa Fromont; A. Hotho; A. J. Knobbe; M. H. Maathuis; C. Robardet in Lecture Notes in Computer Science (2020). (Vol. 11907) Springer.
    • Evaluation of Post-hoc XA...
      Evaluation of Post-hoc XAI Approaches Through Synthetic Tabular Data J. Tritscher; M. Ring; D. Schlr; L. Hettinger; A. Hotho D. Helic, G. Leitner, M. Stettinger, A. Felfernig, Z. W. Ra\’s (Eds.) (2020). 422–430.
    • NICER — Aesthetic Image Enhancement with Humans in the Loop M. Fischer; K. Kobs; A. Hotho (2020). 357–362.
    • Time Series Forecasting for Self-Aware Systems A. Bauer; M. Züfle; N. Herbst; A. Zehe; A. Hotho; S. Kounev in Proceedings of the IEEE (2020). 1–26.
    • Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part III U. Brefeld; Élisa Fromont; A. Hotho; A. J. Knobbe; M. H. Maathuis; C. Robardet in Lecture Notes in Computer Science (2020). (Vol. 11908) Springer.
    • Integrating Keywords into...
      Integrating Keywords into BERT4Rec for Sequential Recommendation E. Fischer; D. Zoller; A. Dallmann; A. Hotho (2020). (Vol. 12325) 275–282.
    • Anomaly Detection in Beeh...
      Anomaly Detection in Beehives using Deep Recurrent Autoencoders P. Davidson; M. Steininger; F. Lautenschlager; K. Kobs; A. Krause; A. Hotho (2020). 142–149.
    • iNALU: Improved Neural Ar...
      iNALU: Improved Neural Arithmetic Logic Unit D. Schlör; M. Ring; A. Hotho in Frontiers in Artificial Intelligence (2020). 3 71.
    • Financial Fraud Detection with Improved Neural Arithmetic Logic Units D. Schlör; M. Ring; A. Krause; A. Hotho (2020). (Vol. Fifth Workshop on MIning DAta for financial applicationS)
    • HarryMotions – Classify...
      HarryMotions – Classifying Relationships in Harry Potter based on Emotion Analysis A. Zehe; J. Arns; L. Hettinger; A. Hotho (2020).
    • SimLoss: Class Similariti...
      SimLoss: Class Similarities in Cross Entropy K. Kobs; M. Steininger; A. Zehe; F. Lautenschlager; A. Hotho D. Helic, G. Leitner, M. Stettinger, A. Felfernig, Z. W. Ra\’s (Eds.) (2020). 431–439.
    • MapLUR: Exploring a New Paradigm for Estimating Air Pollution Using Deep Learning on Map Images M. Steininger; K. Kobs; A. Zehe; F. Lautenschlager; M. Becker; A. Hotho in ACM Trans. Spatial Algorithms Syst. (2020). 6(3)
    • Smartwatch-Derived Data and Machine Learning Algorithms Estimate Classes of Ratings of Perceived Exertion in Runners: A Pilot Study P. Davidson; P. Düking; C. Zinner; B. Sperlich; A. Hotho in Sensors (2020).
    • Improving Sentiment Analysis with Biofeedback Data D. Schlör; A. Zehe; K. Kobs; B. Veseli; F. Westermeier; L. Brübach; D. Roth; M. E. Latoschik; A. Hotho (2020). 28–33.
    • Emote-Controlled: Obtaini...
      Emote-Controlled: Obtaining Implicit Viewer Feedback through Emote based Sentiment Analysis on Comments of Popular Twitch.tv Channels K. Kobs; A. Zehe; A. Bernstetter; J. Chibane; J. Pfister; J. Tritscher; A. Hotho in ACM Transactions on Social Computing (2020). 3(2) 1–34.
    • Where to Submit? Helping Researchers to Choose the Right Venue K. Kobs; T. Koopmann; A. Zehe; D. Fernes; P. Krop; A. Hotho (2020). 878–883.
    2019[ to top ]
    • Flow-based network traffi...
      Flow-based network traffic generation using Generative Adversarial Networks M. Ring; D. Schlör; D. Landes; A. Hotho in Computers & Security (2019). 82 156–172.
    • Solving Mathematical Exer...
      Solving Mathematical Exercises: Prediction of Students’ Success S. Wankerl; G. Götz; A. Hotho in CEUR Workshop Proceedings, R. Jäschke, M. Weidlich (Eds.) (2019). (Vol. 2454) 190–194.
    • Detection of Scenes in Fi...
      Detection of Scenes in Fiction E. Gius; F. Jannidis; M. Krug; A. Zehe; A. Hotho; F. Puppe; J. Krebs; N. Reiter; N. Wiedmer; L. Konle (2019).
    • A Survey of Network-based Intrusion Detection Data Sets M. Ring; S. Wunderlich; D. Scheuring; D. Landes; A. Hotho in Computers & Security (2019). 86 147–167.
    • Team Xenophilius Lovegood...
      Team Xenophilius Lovegood at SemEval-2019 Task 4: Hyperpartisanship Classification using Convolutional Neural Networks A. Zehe; L. Hettinger; S. Ernst; C. Hauptmann; A. Hotho (2019).
    • EClaiRE: Context Matters!...
      EClaiRE: Context Matters! – Comparing Word Embeddings for Relation Classification L. Hettinger; A. Zehe; A. Dallmann; A. Hotho K. David, K. Geihs, M. Lange, G. Stumme (Eds.) (2019). 191–204.
    • On the Right Track! Analy...
      On the Right Track! Analysing and Predicting Navigation Success in Wikipedia T. Koopmann; A. Dallmann; L. Hettinger; T. Niebler; A. Hotho in HT ’19, C. Atzenbeck, J. Rubart, D. E. Millard (Eds.) (2019). 143–152.
    • Comparison of System Call Representations for Intrusion Detection. S. Wunderlich; M. Ring; D. Landes; A. Hotho in Advances in Intelligent Systems and Computing, F. Martínez-Álvarez, A. T. Lora, J. A. S. Muñoz, H. Quintián, E. Corchado (Eds.) (2019). (Vol. 951) 14–24.
    2018[ to top ]
    • A White-Box Model for Detecting Author Nationality by Linguistic Differences in Spanish Novels A. Zehe; D. Schlör; U. Henny-Krahmer; M. Becker; A. Hotho (2018).
    • Adaptive kNN Using Expected Accuracy for Classification of Geo-Spatial Data M. Kibanov; M. Becker; J. Müller; M. Atzmueller; A. Hotho; G. Stumme (2018).
    • Air Trails -- Urban Air Quality Campaign Exploration Patterns M. Becker; F. Lautenschlager; A. Hotho (2018).
    • Burrows’ Zeta: Exploring and Evaluating Variants and Parameters C. Schöch; D. Schlör; A. Zehe; H. Gebhard; M. Becker; A. Hotho (2018). 274–277.
    • Big-Data Helps SDN to Improve Application Specific Quality of Service S. Schwarzmann; A. Blenk; O. Dobrijevic; M. Jarschel; A. Hotho; T. Zinner; F. Wamser in Big Data and Software Defined Networks (2018).
    • Analysing Direct Speech in German Novels F. Jannidis; L. Konle; A. Zehe; A. Hotho; M. Krug (2018).
    • Burrows Zeta: Varianten und Evaluation C. Schöch; J. Calvo; A. Zehe; A. Hotho (2018).
    • Accessing Information with Tags: Search and Ranking B. Navarro Bullock; A. Hotho; G. Stumme in Social Information Access: Systems and Technologies, P. Brusilovsky, D. He (Eds.) (2018). 310–343.
    • ClaiRE at SemEval-2018 Ta...
      ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings L. Hettinger; A. Dallmann; A. Zehe; T. Niebler; A. Hotho (2018).
    • Detection of slow port scans in flow-based network traffic M. Ring; D. Landes; A. Hotho in PLOS ONE (2018). 13(9) 1–18.
    • EveryAware Gears: A Tool to visualize and analyze all types of Citizen Science Data F. Lautenschlager; M. Becker; M. Steininger; A. Hotho D. Burghardt, S. Chen, G. Andrienko, N. Andrienko, R. Purves, A. Diehl (Eds.) (2018).
    • Flow-based Network Traffic Generation using Generative Adversarial Networks. M. Ring; D. Schlör; D. Landes; A. Hotho in CoRR (2018). abs/1810.07795
    2017[ to top ]
    • Learning Semantic Related...
      Learning Semantic Relatedness From Human Feedback Using Metric Learning T. Niebler; M. Becker; C. Pölitz; A. Hotho (2017).
    • Flow-based benchmark data...
      Flow-based benchmark data sets for intrusion detection M. Ring; S. Wunderlich; D. Grüdl; D. Landes; A. Hotho (2017). 361–369.
    • Learning Word Embeddings ...
      Learning Word Embeddings from Tagging Data: A methodological comparison T. Niebler; L. Hahn; A. Hotho (2017).
    • Sedentary Behavior among ...
      Sedentary Behavior among National Elite Rowers during Off-Training—A Pilot Study B. Sperlich; M. Becker; A. Hotho; B. Wallmann-Sperlich; M. Sareban; K. Winkert; J. M. Steinacker; G. Treff in Frontiers in Physiology (2017). 8 655.
    • Learning Semantic Related...
      Learning Semantic Relatedness from Human Feedback Using Relative Relatedness Learning T. Niebler; M. Becker; C. Pölitz; A. Hotho (2017).
    • A Toolset for Intrusion a...
      A Toolset for Intrusion and Insider Threat Detection M. Ring; S. Wunderlich; D. Grüdl; D. Landes; A. Hotho in Data Analytics and Decision Support for Cybersecurity: Trends, Methodologies and Applications, I. Palomares Carrascosa, H. K. Kalutarage, Y. Huang (Eds.) (2017). 3–31.
    • Creation of Flow-Based Da...
      Creation of Flow-Based Data Sets for Intrusion Detection M. Ring; S. Wunderlich; D. Grüdl; D. Landes; A. Hotho in Journal of Information Warfare (2017). 16(4) 41–54.
    • Towards Sentiment Analysi...
      Towards Sentiment Analysis on German Literature A. Zehe; M. Becker; F. Jannidis; A. Hotho G. Kern-Isberner, J. Fürnkranz, M. Thimm (Eds.) (2017). 387–394.
    • Improving Session Recomme...
      Improving Session Recommendation with Recurrent Neural Networks by Exploiting Dwell Time A. Dallmann; A. Grimm; C. Pölitz; D. Zoller; A. Hotho (2017).
    • Leveraging User-Interacti...
      Leveraging User-Interactions for Time-Aware Tag Recommendations D. Zoller; S. Doerfel; C. Pölitz; A. Hotho in CEUR Workshop Proceedings (2017).
    • Participatory sensing, op...
      Participatory sensing, opinions and collective awareness V. Loreto; M. Haklay; A. Hotho; V. C. P. Servedio; G. Stumme; J. Theunis; F. Tria (2017). Springer.
    • Comparing Hypotheses Abou...
      Comparing Hypotheses About Sequential Data: A Bayesian Approach and Its Applications F. Lemmerich; P. Singer; M. Becker; L. Espin-Noboa; D. Dimitrov; D. Helic; A. Hotho; M. Strohmaier Y. Altun, K. Das, T. Mielikäinen, D. Malerba, J. Stefanowski, J. Read, M. \vZitnik, M. Ceci, S. D\vzeroski (Eds.) (2017). 354–357.
    • IP2Vec: Learning Similari...
      IP2Vec: Learning Similarities Between IP Addresses M. Ring; D. Landes; A. Dallmann; A. Hotho in 2017 IEEE International Conference on Data Mining Workshops (ICDMW) (2017). 657–666.
    • Mining social semantics o...
      Mining social semantics on the social web A. Hotho; R. Jaeschke; K. Lerman in Semantic Web (2017). 8(5) 623–624.
    • A Bayesian Method for Comparing Hypotheses About Human Trails P. Singer; D. Helic; A. Hotho; M. Strohmaier in ACM Trans. Web (2017). 11(3) 14:1–14:29.
    • MixedTrails: Bayesian hyp...
      MixedTrails: Bayesian hypothesis comparison on heterogeneous sequential data M. Becker; F. Lemmerich; P. Singer; M. Strohmaier; A. Hotho in Data Mining and Knowledge Discovery (2017).
    2016[ to top ]
    • Prediction of Happy Endings in German Novels A. Zehe; M. Becker; L. Hettinger; A. Hotho; I. Reger; F. Jannidis in CEUR Workshop Proceedings, P. Cellier, T. Charnois, A. Hotho, S. Matwin, M.-F. Moens, Y. Toussaint (Eds.) (2016). (Vol. 1646) 9–16.
    • Significance Testing for ...
      Significance Testing for the Classification of Literary Subgenres L. Hettinger; F. Jannidis; I. Reger; A. Hotho (2016).
    • Extracting Semantics from...
      Extracting Semantics from Unconstrained Navigation on Wikipedia T. Niebler; D. Schlör; M. Becker; A. Hotho in KI (2016). 30(2) 163–168.
    • SparkTrails: A MapReduce ...
      SparkTrails: A MapReduce Implementation of HypTrails for Comparing Hypotheses About Human Trails. M. Becker; H. Mewes; A. Hotho; D. Dimitrov; F. Lemmerich; M. Strohmaier J. Bourdeau, J. Hendler, R. Nkambou, I. Horrocks, B. Y. Zhao (Eds.) (2016). 17–18.
    • Proceedings of the Workshop on Interactions between Data Mining and Natural Language Processing, DMNLP 2016, co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2016, Riva del Garda, Italy, September 23, 2016. P. Cellier; T. Charnois; A. Hotho; S. Matwin; M.-F. Moens; Y. Toussaint in CEUR Workshop Proceedings (2016). (Vol. 1646) CEUR-WS.org.
    • Mining Subgroups with Exc...
      Mining Subgroups with Exceptional Transition Behavior F. Lemmerich; M. Becker; P. Singer; D. Helic; A. Hotho; M. Strohmaier B. Krishnapuram, M. Shah, A. J. Smola, C. Aggarwal, D. Shen, R. Rastogi (Eds.) (2016). 965–974.
    • Comparison of non-invasive individual monitoring of the training and health of athletes with commercially available wearable technologies P. Düking; A. Hotho; F. K. Fuss; H.-C. Holmberg; B. Sperlich in Frontiers in Physiology (2016). 7(71)
    • Extracting Semantics from...
      Extracting Semantics from Random Walks on Wikipedia: Comparing learning and counting methods A. Dallmann; T. Niebler; F. Lemmerich; A. Hotho R. West, L. Zia, D. Taraborelli, J. Leskovec (Eds.) (2016).
    • Classification of Literar...
      Classification of Literary Subgenres L. Hettinger; F. Jannidis; I. Reger; A. Hotho (2016).
    • Analyzing Features for the Detection of Happy Endings in German Novels F. Jannidis; I. Reger; A. Zehe; M. Becker; L. Hettinger; A. Hotho (2016).
    • Creation of Specific Flow-Based Training Data Sets for Usage Behaviour Classification F. Otto; M. Ring; D. Landes; A. Hotho (2016). 437.
    • Posted, Visited, Exported...
      Posted, Visited, Exported: Altmetrics in the Social Tagging System BibSonomy D. Zoller; S. Doerfel; R. Jäschke; G. Stumme; A. Hotho in Journal of Informetrics (2016). 10(3) 732–749.
    • What Users Actually do in...
      What Users Actually do in a Social Tagging System: A Study of User Behavior in BibSonomy S. Doerfel; D. Zoller; P. Singer; T. Niebler; A. Hotho; M. Strohmaier in ACM Transactions on the Web (2016). 10(2) 14:1–14:32.
    • FolkTrails: Interpreting ...
      FolkTrails: Interpreting Navigation Behavior in a Social Tagging System T. Niebler; M. Becker; D. Zoller; S. Doerfel; A. Hotho in CIKM ’16 (2016).
    2015[ to top ]
    • Genre classification on German novels L. Hettinger; M. Becker; I. Reger; F. Jannidis; A. Hotho (2015).
    • VizTrails: An Information...
      VizTrails: An Information Visualization Tool for Exploring Geographic Movement Trajectories M. Becker; P. Singer; F. Lemmerich; A. Hotho; D. Helic; M. Strohmaier in HT ’15 (2015). 319–320.
    • ConDist: A Context-Driven...
      ConDist: A Context-Driven Categorical Distance Measure M. Ring; F. Otto; M. Becker; T. Niebler; D. Landes; A. Hotho ECMLPKDD2015 (Ed.) (2015).
    • Participatory Patterns in an International Air Quality Monitoring Initiative A. Sîrbu; M. Becker; S. Caminiti; B. De Baets; B. Elen; L. Francis; P. Gravino; A. Hotho; S. Ingarra; V. Loreto; A. Molino; J. Mueller; J. Peters; F. Ricchiuti; F. Saracino; V. D. P. Servedio; G. Stumme; J. Theunis; F. Tria; J. Van den Bossche (2015).
    • On Publication Usage in a Social Bookmarking System D. Zoller; S. Doerfel; R. Jäschke; G. Stumme; A. Hotho (2015).
    • Modeling and Extracting Load Intensity Profiles J. v. Kistowski; H. Nikolas; D. Zoller; S. Kounev; A. Hotho (2015).
    • Media Bias in German Onli...
      Media Bias in German Online Newspapers A. Dallmann; F. Lemmerich; D. Zoller; A. Hotho (2015).
    • Automatic Threshold Calcu...
      Automatic Threshold Calculation for the Categorical Distance Measure ConDist. M. Ring; D. Landes; A. Hotho in CEUR Workshop Proceedings, R. Bergmann, S. Görg, G. Müller (Eds.) (2015). (Vol. 1458) 52–63.
    • MicroTrails: Comparing Hy...
      MicroTrails: Comparing Hypotheses About Task Selection on a Crowdsourcing Platform M. Becker; K. Borchert; M. Hirth; H. Mewes; A. Hotho; P. Tran-Gia in i-KNOW ’15 (2015). 10:1–10:8.
    • Hyptrails: A bayesian app...
      Hyptrails: A bayesian approach for comparing hypotheses about human trails P. Singer; D. Helic; A. Hotho; M. Strohmaier (2015).
    • Participatory Patterns in...
      Participatory Patterns in an International Air Quality Monitoring Initiative A. Sîrbu; M. Becker; S. Caminiti; B. De Baets; B. Elen; L. Francis; P. Gravino; A. Hotho; S. Ingarra; V. Loreto; A. Molino; J. Mueller; J. Peters; F. Ricchiuti; F. Saracino; V. D. P. Servedio; G. Stumme; J. Theunis; F. Tria; J. Van den Bossche in PLoS ONE (2015). 10(8) e0136763.
    • Photowalking the city: co...
      Photowalking the city: comparing hypotheses about urban photo trails on Flickr M. Becker; P. Singer; F. Lemmerich; A. Hotho; D. Helic; M. Strohmaier (2015).
    2014[ to top ]
    • Subjective vs. Objective Data: Bridging the Gap M. Becker; A. Hotho; J. Mueller; M. Kibanov; M. Atzmueller; G. Stumme (2014).
    • Ubicon and its Applications for Ubiquitous Social Computing M. Atzmueller; M. Becker; M. Kibanov; C. Scholz; S. Doerfel; A. Hotho; B.-E. Macek; F. Mitzlaff; J. Mueller; G. Stumme in New Review of Hypermedia and Multimedia (2014). 20(1) 53–77.
    • Of course we share! Testi...
      Of course we share! Testing Assumptions about Social Tagging Systems S. Doerfel; D. Zoller; P. Singer; T. Niebler; A. Hotho; M. Strohmaier (2014).
    • Proceedings of the 1st In...
      Proceedings of the 1st International Workshop on Interactions between Data Mining and Natural Language Processing co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, DMNLP@PKDD/ECML 2014, Nancy, France, September 15, 2014 P. Cellier; T. Charnois; A. Hotho; S. Matwin; M.-F. Moens; Y. Toussaint in CEUR Workshop Proceedings (2014). (Vol. 1202) CEUR-WS.org.
    • HypTrails: A Bayesian App...
      HypTrails: A Bayesian Approach for Comparing Hypotheses about Human Trails on the Web P. Singer; D. Helic; A. Hotho; M. Strohmaier (2014).
    • The social distributional...
      The social distributional hypothesis: a pragmatic proxy for homophily in online social networks F. Mitzlaff; M. Atzmueller; A. Hotho; G. Stumme in Social Network Analysis and Mining (2014). 4(1)
    • The sixth ACM RecSys workshop on recommender systems and the social web D. Jannach; J. Freyne; W. Geyer; I. Guy; A. Hotho; B. Mobasher (2014). 395.
    • Folksonomies P. Singer; T. Niebler; A. Hotho; M. Strohmaier in Encyclopedia of Social Network Analysis and Mining (2014). 542–547.
    • Evaluating Assumptions about Social Tagging - A Study of User Behavior in BibSonomy S. Doerfel; D. Zoller; P. Singer; T. Niebler; A. Hotho; M. Strohmaier T. Seidl, M. Hassani, C. Beecks (Eds.) (2014). 18–19.
    • How Social is Social Tagg...
      How Social is Social Tagging? S. Doerfel; D. Zoller; P. Singer; T. Niebler; A. Hotho; M. Strohmaier in WWW 2014 (2014).
    • Proceedings of the 6th Workshop on Recommender Systems and the Social Web (RSWeb 2014) co-located with the 8th ACM Conference on Recommender Systems (RecSys 2014), Foster City, CA, USA, October 6, 2014 D. Jannach; J. Freyne; W. Geyer; I. Guy; A. Hotho; B. Mobasher in CEUR Workshop Proceedings (2014). (Vol. 1271) CEUR-WS.org.
    2013[ to top ]
    • Proceedings of the Fifth ACM RecSys Workshop on Recommender Systems and the Social Web co-located with the 7th ACM Conference on Recommender Systems (RecSys 2013), Hong Kong, China, October 13, 2013. B. Mobasher; D. Jannach; W. Geyer; J. Freyne; A. Hotho; S. S. Anand; I. Guy in CEUR Workshop Proceedings (2013). (Vol. 1066) CEUR-WS.org.
    • Semantics of User Interaction in Social Media F. Mitzlaff; M. Atzmueller; G. Stumme; A. Hotho in Complex Networks IV, G. Ghoshal, J. Poncela-Casasnovas, R. Tolksdorf (Eds.) (2013). (Vol. 476)
    • Deeper Into the Folksonomy Graph: FolkRank Adaptations and Extensions for Improved Tag Recommendations N. Landia; S. Doerfel; R. Jäschke; S. S. Anand; A. Hotho; N. Griffiths in cs.IR (2013). 1310.1498
    • Informationelle Selbstbestimmung Im Web 2.0 Chancen Und Risiken Sozialer Verschlagwortungssysteme S. Doerfel; A. Hotho; A. Kartal-Aydemir; A. Roßnagel; G. Stumme (2013). Vieweg + Teubner Verlag.
    • Computing Semantic Relate...
      Computing Semantic Relatedness from Human Navigational Paths: A Case Study on Wikipedia P. Singer; T. Niebler; M. Strohmaier; A. Hotho in International Journal on Semantic Web and Information Systems (IJSWIS) (2013). 9(4) 41–70.
    • Tag Recommendations for SensorFolkSonomies J. Mueller; S. Doerfel; M. Becker; A. Hotho; G. Stumme (2013). (Vol. 1066)
    • A Generic Platform for Ub...
      A Generic Platform for Ubiquitous and Subjective Data M. Becker; J. Mueller; A. Hotho; G. Stumme (2013). New York, NY, USA.
    • How Tagging Pragmatics Influence Tag Sense Discovery in Social Annotation Systems T. Niebler; P. Singer; D. Benz; C. Körner; M. Strohmaier; A. Hotho in Advances in Information Retrieval, P. Serdyukov, P. Braslavski, S. Kuznetsov, J. Kamps, S. Rüger, E. Agichtein, I. Segalovich, E. Yilmaz (Eds.) (2013). (Vol. 7814) 86–97.
    • Exploiting Structural Consistencies with Stacked Conditional Random Fields P. Kluegl; M. Toepfer; F. Lemmerich; A. Hotho; F. Puppe in Mathematical Methodologies in Pattern Recognition and Machine Learning Springer Proceedings in Mathematics & Statistics (2013). 30 111–125.
    • Ubiquitous Social Media Analysis Third International Workshops, MUSE 2012, Bristol, UK, September 24, 2012, and MSM 2012, Milwaukee, WI, USA, June 25, 2012, Revised Selected Papers M. Atzmueller; A. Chin; D. Helic; A. Hotho (2013). Imprint: Springer, Berlin, Heidelberg.
    • Awareness and Learning in...
      Awareness and Learning in Participatory Noise Sensing M. Becker; S. Caminiti; D. Fiorella; L. Francis; P. Gravino; M. (Muki) Haklay; A. Hotho; V. Loreto; J. Mueller; F. Ricchiuti; V. D. P. Servedio; A. Sîrbu; F. Tria in PLoS ONE (2013). 8(12) e81638.
    2012[ to top ]
    • Proceedings of the Third International Workshop on Mining Ubiquitous and Social Environments (MUSE 2012) M. Atzmueller; A. Hotho (2012). Workshop Notes, Bristol, UK.
    • Stacked Conditional Random Fields Exploiting Structural Consistencies P. Klügl; M. Toepfer; F. Lemmerich; A. Hotho; F. Puppe P. L. Carmona, J. S. Sánchez, A. Fred (Eds.) (2012). 240–248.
    • The challenge of recommender systems challenges. A. Said; D. Tikk; A. Hotho P. Cunningham, N. J. Hurley, I. Guy, S. S. Anand (Eds.) (2012). 9–10.
    • Leveraging publication metadata and social data into FolkRank for scientific publication recommendation S. Doerfel; R. Jäschke; A. Hotho; G. Stumme in RSWeb ’12 (2012). 9–16.
    • Challenges in Tag Recommendations for Collaborative Tagging Systems R. Jäschke; A. Hotho; F. Mitzlaff; G. Stumme in Recommender Systems for the Social Web, J. J. Pazos Arias, A. Fernández Vilas, R. P. Díaz Redondo (Eds.) (2012). (Vol. 32) 65–87.
    • RSWeb ’12: Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web B. Mobasher; D. Jannach; W. Geyer; A. Hotho (2012). ACM, Dublin, Ireland.
    • Collective Information Ex...
      Collective Information Extraction with Context-Specific Consistencies. P. Klügl; M. Toepfer; F. Lemmerich; A. Hotho; F. Puppe in Lecture Notes in Computer Science, P. A. Flach, T. D. Bie, N. Cristianini (Eds.) (2012). (Vol. 7523) 728–743.
    • Datenschutz im Web 2.0 am Beispiel des sozialen Tagging-Systems BibSonomy. B. Krause; H. Lerch; A. Hotho; A. Roßnagel; G. Stumme in Informatik Spektrum (2012). 35(1) 12–23.
    • Face-to-Face Contacts at a Conference: Dynamics of Communities and Roles M. Atzmueller; S. Doerfel; A. Hotho; F. Mitzlaff; G. Stumme in Modeling and Mining Ubiquitous Social Media (2012). (Vol. 7472)
    • Modeling and Mining Ubiquitous Social Media M. Atzmueller; A. Chin; D. Helic; A. Hotho in Lecture Notes in Computer Science (2012). (Vol. 7472) Springer Verlag, Heidelberg, Germany.
    • Publikationen im Web 2.0 A. Hotho in Informatik-Spektrum (2012). 1–5.
    • Ubicon: Observing Social ...
      Ubicon: Observing Social and Physical Activities M. Atzmueller; M. Becker; S. Doerfel; M. Kibanov; A. Hotho; B.-E. Macek; F. Mitzlaff; J. Mueller; C. Scholz; G. Stumme (2012).
    • 4th ACM RecSys workshop on recommender systems and the social web. B. Mobasher; D. Jannach; W. Geyer; A. Hotho P. Cunningham, N. J. Hurley, I. Guy, S. S. Anand (Eds.) (2012). 345–346.
    • Recommender Systems for S...
      Recommender Systems for Social Tagging Systems L. Balby Marinho; A. Hotho; R. Jäschke; A. Nanopoulos; S. Rendle; L. Schmidt-Thieme; G. Stumme; P. Symeonidis in SpringerBriefs in Electrical and Computer Engineering (2012). Springer.
    • Extending FolkRank with content data N. Landia; S. S. Anand; A. Hotho; R. Jäschke; S. Doerfel; F. Mitzlaff in RSWeb ’12 (2012). 1–8.
    2011[ to top ]
    • On the Semantics of User Interaction in Social Media (Extended Abstract, Resubmission) F. Mitzlaff; M. Atzmueller; G. Stumme; A. Hotho (2011).
    • Towards Mining Semantic Maturity in Social Bookmarking Systems M. Atzmueller; D. Benz; A. Hotho; G. Stumme A. Passant, S. Fernández, J. Breslin, U. Bojārs (Eds.) (2011).
    • Resource-Aware On-Line RFID Localization Using Proximity Data C. Scholz; S. Doerfel; M. Atzmueller; A. Hotho; G. Stumme (2011). 129–144.
    • One Tag to Bind Them All: Measuring Term Abstractness in Social Metadata D. Benz; C. Körner; A. Hotho; G. Stumme; M. Strohmaier (2011).
    • Segmentation of References with Skip-Chain Conditional Random Fields for Consistent Label Transitions M. Toepfer; P. Kluegl; A. Hotho; F. Puppe (2011).
    • Face-to-Face Contacts dur...
      Face-to-Face Contacts during a Conference: Communities, Roles, and Key Players M. Atzmueller; S. Doerfel; A. Hotho; F. Mitzlaff; G. Stumme (2011).
    • Analysis of Social Media and Ubiquitous Data - International Workshops MSM 2010, Toronto, Canada, June 13, 2010, and MUSE 2010, Barcelona, Spain, September 20, 2010, Revised Selected Papers M. Atzmueller; A. Hotho; M. Strohmaier; A. Chin in Lecture Notes in Computer Science (2011). (Vol. 6904) Springer.
    • Community Assessment using Evidence Networks F. Mitzlaff; M. Atzmueller; D. Benz; A. Hotho; G. Stumme in LNAI (2011). (Vol. 6904)
    • From Semantic Web Mining to Social and Ubiquitous Mining - A Subjective View on Past, Current, and Future Research. A. Hotho; G. Stumme D. Fensel (Ed.) (2011). 143–153.
    • 3rd workshop on recommender systems and the social web J. Freyne; S. S. Anand; I. Guy; A. Hotho in RecSys ’11 (2011). 383–384.
    • Resource-Aware On-Line RFID Localization Using Proximity Data C. Scholz; S. Doerfel; M. Atzmueller; A. Hotho; G. Stumme (2011).
    • Tagging data as implicit ...
      Tagging data as implicit feedback for learning-to-rank B. N. Bullock; R. Jäschke; A. Hotho (2011).
    • Social Tagging Recommender Systems. L. B. Marinho; A. Nanopoulos; L. Schmidt-Thieme; R. Jäschke; A. Hotho; G. Stumme; P. Symeonidis in Recommender Systems Handbook, F. Ricci, L. Rokach, B. Shapira, P. B. Kantor (Eds.) (2011). 615–644.
    • Face-to-Face Contacts during LWA 2010 - Communities, Roles, and Key Players M. Atzmueller; S. Doerfel; A. Hotho; F. Mitzlaff; G. Stumme (2011).
    • Enhancing Social Interactions at Conferences M. Atzmueller; D. Benz; S. Doerfel; A. Hotho; R. Jäschke; B. E. Macek; F. Mitzlaff; C. Scholz; G. Stumme in it - Information Technology (2011). 53(3) 101–107.
    • A Comparison of Content-Based Tag Recommendations in Folksonomy Systems J. Illig; A. Hotho; R. Jäschke; G. Stumme in Lecture Notes in Computer Science, K. E. Wolff, D. E. Palchunov, N. G. Zagoruiko, U. Andelfinger (Eds.) (2011). (Vol. 6581) 136–149.
    • One Tag to Bind Them All : Measuring Term Abstractness in Social Metadata D. Benz; C. Körner; A. Hotho; G. Stumme; M. Strohmaier G. Antoniou, M. Grobelnik, E. Simperl, B. Parsia, D. Plexousakis, J. Pan, P. D. Leenheer (Eds.) (2011).
    • Proceedings of the 2011 International Workshop on Mining Ubiquitous and Social Environments (MUSE 2011) M. Atzmueller; A. Hotho (2011). ECML/PKDD 2011, Athens, Greece.
    • Introduction to the Special Issue on Social Linking and Hypermedia C. Cattuto; A. Hotho in New Review of Hypermedia and Multimedia (2011). 17(3) 241–242.
    • Privacy-aware spam detection in social bookmarking systems B. N. Bullock; H. Lerch; A. Ro\ssnagel; A. Hotho; G. Stumme in i-KNOW ’11 (2011). 15:1–15:8.
    • Combining Data-Driven and Semantic Approaches for Text Mining. S. Bloehdorn; S. Blohm; P. Cimiano; E. Giesbrecht; A. Hotho; U. Lösch; A. Mädche; E. Mönch; P. Sorg; S. Staab; J. Völker D. Fensel (Ed.) (2011). 115–142.
    • Recommendation in the Social Web R. Burke; J. Gemmell; A. Hotho; R. Jäschke in AI Magazine (2011). 32(3) 46–56.
    2010[ to top ]
    • Proceedings of the 2010 Workshop on Mining Ubiquitous and Social Environments (MUSE 2010) M. Atzmueller; A. Hotho (2010). ECML/PKDD 2010, Barcelona, Spain.
    • Community Assessment usin...
      Community Assessment using Evidence Networks F. Mitzlaff; M. Atzmüller; D. Benz; A. Hotho; G. Stumme (2010).
    • Datenschutz im Web 2.0 am...
      Datenschutz im Web 2.0 am Beispiel des sozialen Tagging-Systems BibSonomy B. Krause; H. Lerch; A. Hotho; A. Roßnagel; G. Stumme in Informatik-Spektrum (2010). 1–12.
    • Visit me, click me, be my friend: An analysis of evidence networks of user relationships in Bibsonomy F. Mitzlaff; D. Benz; G. Stumme; A. Hotho (2010).
    • Social Bookmarking-Systeme – die unerkannten Datensammler - Ungewollte personenbezogene Datenverabeitung? H. Lerch; B. Krause; A. Hotho; A. Roßnagel; G. Stumme in MultiMedia und Recht (2010). 7 454–458.
    • Local Adaptive Extraction of References P. Kluegl; A. Hotho; F. Puppe in LNAI 6359, R. Dillmann, J. Beyerer, U. D. Hanebeck, T. Schultz (Eds.) (2010). 40–47.
    • Ubiquitous Data
      Ubiquitous Data A. Hotho; R. Ulslev Pedersen; M. Wurst in Lecture Notes in Computer Science (2010). (6202) 61–74.
    • Academic Publication Management with PUMA - collect, organize and share publications D. Benz; A. Hotho; R. Jäschke; G. Stumme; A. Halle; A. G. S. Lima; H. Steenweg; S. Stefani in Lecture Notes in Computer Science, M. Lalmas, J. Jose, A. Rauber, F. Sebastiani, I. Frommholz (Eds.) (2010). (Vol. 6273) 417–420.
    • Proceedings of the LWA 2010 - Lernen, Wissen, Adaptivität M. Atzmueller; D. Benz; A. Hotho; G. Stumme in Technical report (KIS), 2010-10 (2010). Department of Electrical Engineering/Computer Science, Kassel University.
    • Semantics made by you and...
      Semantics made by you and me: Self-emerging ontologies can capture the diversity of shared knowledge D. Benz; A. Hotho; G. Stumme (2010).
    • Data Mining on Folksonomies A. Hotho in Intelligent Information Access, G. Armano, M. de Gemmis, G. Semeraro, E. Vargiu (Eds.) (2010). (Vol. 301) 57–82.
    • Conditional Random Fields For Local Adaptive Reference Extraction M. Toepfer; P. Kluegl; A. Hotho; F. Puppe. M. Atzmüller, D. Benz, A. Hotho, G. Stumme (Eds.) (2010).
    • Academic Publication Management with PUMA - collect, organize and share publications D. Benz; A. Hotho; R. Jäschke; G. Stumme; A. Halle; A. S. Lima-Gerlach; H. Steenweg; S. Stefani (2010). 417–420.
    • Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System für Wissenschaftler A. Hotho; D. Benz; F. Eisterlehner; R. Jäschke; B. Krause; C. Schmitz; G. Stumme in HMD -- Praxis der Wirtschaftsinformatik (2010). Heft 271 47–58.
    • Stop Thinking, start Tagg...
      Stop Thinking, start Tagging - Tag Semantics emerge from Collaborative Verbosity C. Körner; D. Benz; M. Strohmaier; A. Hotho; G. Stumme (2010).
    • Query Logs as Folksonomies D. Benz; A. Hotho; R. Jäschke; B. Krause; G. Stumme in Datenbank-Spektrum (2010). 10(1) 15–24.
    • The Social Bookmark and P...
      The Social Bookmark and Publication Management System BibSonomy D. Benz; A. Hotho; R. Jäschke; B. Krause; F. Mitzlaff; C. Schmitz; G. Stumme in The VLDB Journal (2010). 19(6) 849–875.
    • Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0 B. Berendt; A. Hotho; G. Stumme in Web Semantics: Science, Services and Agents on the World Wide Web (2010). 8(2-3) 95–96.
    2009[ to top ]
    • Evaluating Similarity Mea...
      Evaluating Similarity Measures for Emergent Semantics of Social Tagging B. Markines; C. Cattuto; F. Menczer; D. Benz; A. Hotho; G. Stumme (2009). 641–641.
    • Towards Understanding Spammers - Discovering Local Patterns for Concept Characterization and Description M. Atzmueller; F. Lemmerich; B. Krause; A. Hotho J. F. A. Knobbe (Ed.) (2009).
    • Mapping Bibliographic Rec...
      Mapping Bibliographic Records with Bibliographic Hash Keys J. Voss; A. Hotho; R. Jäschke in Proceedings of the ISI, R. Kuhlen (Ed.) (2009).
    • Social Bookmarking am Beispiel BibSonomy A. Hotho; R. Jäschke; D. Benz; M. Grahl; B. Krause; C. Schmitz; G. Stumme in Social Semantic Web, A. Blumauer, T. Pellegrini (Eds.) (2009). 363–391.
    • Who are the Spammers? Understandable Local Patterns for Concept Description M. Atzmueller; F. Lemmerich; B. Krause; A. Hotho (2009).
    • Managing publications and bookmarks with BibSonomy D. Benz; F. Eisterlehner; A. Hotho; R. Jäschke; B. Krause; G. Stumme C. Cattuto, G. Ruffo, F. Menczer (Eds.) (2009). 323–324.
    • ECML PKDD Discovery Challenge 2009 (DC09) F. Eisterlehner; A. Hotho; R. Jäschke in CEUR-WS.org (2009). (Vol. 497)
    • Testing and Evaluating Ta...
      Testing and Evaluating Tag Recommenders in a Live System R. Jäschke; F. Eisterlehner; A. Hotho; G. Stumme D. Benz, F. Janssen (Eds.) (2009). 44–51.
    • Characterizing Semantic Relatedness of Search Query Terms D. Benz; B. Krause; G. P. Kumar; A. Hotho; G. Stumme (2009).
    2008[ to top ]
    • Analyzing Tag Semantics Across Collaborative Tagging Systems D. Benz; M. Grobelnik; A. Hotho; R. Jäschke; D. Mladenic; V. D. P. Servedio; S. Sizov; M. Szomszor in Dagstuhl Seminar Proceedings, H. Alani, S. Staab, G. Stumme (Eds.) (2008).
    • Logsonomy — A Search Engine Folksonomy R. Jäschke; B. Krause; A. Hotho; G. Stumme (2008).
    • AEON - An approach to the automatic evaluation of ontologies J. Völker; D. Vrandečić; Y. Sure; A. Hotho in Applied Ontology (2008). 3(1-2) 41–62.
    • Tag Recommendations in So...
      Tag Recommendations in Social Bookmarking Systems R. Jäschke; L. Marinho; A. Hotho; L. Schmidt-Thieme; G. Stumme in AI Communications, (E. Giunchiglia, Ed.) (2008). 21(4) 231–247.
    • Semantic Grounding of Tag...
      Semantic Grounding of Tag Relatedness in Social Bookmarking Systems C. Cattuto; D. Benz; A. Hotho; G. Stumme in Lecture Notes in Computer Science (2008). (Vol. 5318) 615–631.
    • Research Challenges in Ubiquitous Knowledge Discovery M. May; B. Berendt; A. Cornuéjols; J. Gama; F. Giannotti; A. Hotho; D. Malerba; E. Menesalvas; K. Morik; R. Pedersen; L. Saitta; Y. Saygin; A. Schuster; K. Vanhoof in Next Generation of Data Mining (Chapman & Hall/Crc Data Mining and Knowledge Discovery Series) (2008). (1st ed.)
    • Social Bookmarking
      Social Bookmarking A. Hotho in Web 2.0 in der Unternehmenspraxis: Grundlagen, Fallstudien und Trends zum Einsatz von Social Software, A. Back, N. Gronau, K. Tochtermann (Eds.) (2008). 26–38.
    • The Anti-Social Tagger - ...
      The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems B. Krause; C. Schmitz; A. Hotho; G. Stumme (2008). 61–68.
    • Logsonomy - social information retrieval with logdata B. Krause; R. Jäschke; A. Hotho; G. Stumme (2008). 157–166.
    • Wikis, Blogs, Bookmarking Tools - Mining the Web 2.0 Workshop B. Berendt; N. Glance; A. Hotho (2008). Workshop at 18th Europ. Conf. on Machine Learning (ECML’08) / 11th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD’08).
    • Semantic Analysis of Tag ...
      Semantic Analysis of Tag Similarity Measures in Collaborative Tagging Systems C. Cattuto; D. Benz; A. Hotho; G. Stumme (2008).
    • ECML PKDD Discovery Challenge 2008 (RSDC’08) A. Hotho; D. Benz; R. Jäschke; B. Krause (2008). Workshop at 18th Europ. Conf. on Machine Learning (ECML’08) / 11th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD’08).
    • Discovering Shared Concep...
      Discovering Shared Conceptualizations in Folksonomies R. Jäschke; A. Hotho; C. Schmitz; B. Ganter; G. Stumme in Web Semantics: Science, Services and Agents on the World Wide Web (2008). 6(1) 38–53.
    • A Comparison of Social Bo...
      A Comparison of Social Bookmarking with Traditional Search B. Krause; A. Hotho; G. Stumme (2008). (Vol. 4956) 101–113.
    2007[ to top ]
    • Themenheft Web Mining A. Hotho; G. Stumme (ed.) in Künstliche Intelligenz (2007). (3) 5–8.
    • Network Properties of Folksonomies C. Cattuto; C. Schmitz; A. Baldassarri; V. D. P. Servedio; V. Loreto; A. Hotho; M. Grahl; G. Stumme in AI Communications (2007). 20(4) 245–262.
    • From Web to Social Web: Discovering and Deploying User and Content Profiles B. Berendt; A. Hotho; D. Mladenic; G. Semeraro in LNCS (September 18, 2006 Series:). (Vol. 4736) Springer, Berlin, Germany.
    • Proceedings of the First International Workshop on Emergent Semantics and Ontology Evolution, ESOE 2007, co-located with ISWC 2007 + ASWC 2007, Busan, Korea, November 12th, 2007 L. Chen; P. Cudré-Mauroux; P. Haase; A. Hotho; E. Ong in CEUR Workshop Proceedings (2008). (Vol. 292) CEUR-WS.org.
    • Mining the World Wide Web A. Hotho; G. Stumme in Künstliche Intelligenz (2007). (3) 5–8.
    • Organizing Publications and Bookmarks in BibSonomy R. Jäschke; M. Grahl; A. Hotho; B. Krause; C. Schmitz; G. Stumme H. Alani, N. Noy, G. Stumme, P. Mika, Y. Sure, D. Vrandecic (Eds.) (2007).
    • Tag Recommendations in Fo...
      Tag Recommendations in Folksonomies R. Jäschke; L. B. Marinho; A. Hotho; L. Schmidt-Thieme; G. Stumme in Lecture Notes in Computer Science, J. N. Kok, J. Koronacki, R. L. de Mántaras, S. Matwin, D. Mladenic, A. Skowron (Eds.) (2007). (Vol. 4702) 506–514.
    • Position Paper: Ontology Learning from Folksonomies. D. Benz; A. Hotho A. Hinneburg (Ed.) (2007). 109–112.
    • Network Properties of Fol...
      Network Properties of Folksonomies C. Schmitz; M. Grahl; A. Hotho; G. Stumme; C. Catutto; A. Baldassarri; V. Loreto; V. D. P. Servedio (2007).
    • Analysis of the Publication Sharing Behaviour in BibSonomy R. Jäschke; A. Hotho; C. Schmitz; G. Stumme in LNCS (2007). (Vol. 4604)
    • Learning Disjointness
      Learning Disjointness J. Völker; D. Vrandecic; Y. Sure; A. Hotho in Lecture Notes in Computer Science, E. Franconi, M. Kifer, W. May (Eds.) (2007). (Vol. 4519)
    • Conceptual Clustering of Social Bookmarking Sites M. Grahl; A. Hotho; G. Stumme (2007). 356–364.
    • Tag Recommendations in Folksonomies R. Jäschke; L. Marinho; A. Hotho; L. Schmidt-Thieme; G. Stumme A. Hinneburg (Ed.) (2007). 13–20.
    • Conceptual Clustering of Social Bookmark Sites M. Grahl; A. Hotho; G. Stumme A. Hinneburg (Ed.) (2007). 50–54.
    2006[ to top ]
    • FolkRank: A Ranking Algor...
      FolkRank: A Ranking Algorithm for Folksonomies A. Hotho; R. Jäschke; C. Schmitz; G. Stumme (2006). 111–114.
    • Semantic Web Mining - Sta...
      Semantic Web Mining - State of the Art and Future Directions G. Stumme; A. Hotho; B. Berendt in Journal of Web Semantics (2006). 4(2) 124–143.
    • Kollaboratives Wissensmanagement C. Schmitz; A. Hotho; R. Jäschke; G. Stumme in Semantic Web - Wege zur vernetzten Wissensgesellschaft, T. Pellegrini, A. Blumauer (Eds.) (2006). 273–290.
    • Personalized Information Access in a Bibliographic Peer-to-Peer System P. Haase; M. Ehrig; A. Hotho; B. Schnizler in Peer-to-Peer and SemanticWeb, Decentralized Management and Exchange of Knowledge and Information, S. Staab, H. Stuckenschmidt (Eds.) (2006). 143–158.
    • BibSonomy: A Social Bookm...
      BibSonomy: A Social Bookmark and Publication Sharing System A. Hotho; R. Jäschke; C. Schmitz; G. Stumme (2006). 87–102.
    • Workshop on Web Mining 2006 (WebMine) B. Berendt; A. Hotho; D. Mladenic; G. Semeraro (2006).
    • Semantics, Web and Mining M. Ackermann; B. Berendt; M. Grobelnik; A. Hotho; D. Mladenic; G. Semeraro; M. Spiliopoulou; G. Stumme; V. Svatek; M. van Someren (2006).
    • Trend Detection in Folkso...
      Trend Detection in Folksonomies A. Hotho; R. Jäschke; C. Schmitz; G. Stumme in Lecture Notes in Computer Science, Y. S. Avrithis, Y. Kompatsiaris, S. Staab, N. E. O’Connor (Eds.) (2006). (Vol. 4306) 56–70.
    • Semantic Network Analysis...
      Semantic Network Analysis of Ontologies B. Hoser; A. Hotho; R. Jäschke; C. Schmitz; G. Stumme in LNCS (2006). (Vol. 4011) 514–529.
    • Learning Ontologies to Im...
      Learning Ontologies to Improve Text Clustering and Classification S. Bloehdorn; P. Cimiano; A. Hotho in From Data and Information Analysis to Knowledge Engineering (2006). 334–341.
    • Boosting for Text Classification with Semantic Features S. Bloehdorn; A. Hotho in Advances in Web Mining and Web Usage Analysis (2006). (Vol. 3932) 149–166.
    • Content Aggregation on Knowledge Bases using Graph Clustering C. Schmitz; A. Hotho; R. Jäschke; G. Stumme in LNCS (2006). (Vol. 4011) 530–544.
    • TRIAS - An Algorithm for ...
      TRIAS - An Algorithm for Mining Iceberg Tri-Lattices R. Jäschke; A. Hotho; C. Schmitz; B. Ganter; G. Stumme (2006).
    • Information Retrieval in ...
      Information Retrieval in Folksonomies: Search and Ranking A. Hotho; R. Jäschke; C. Schmitz; G. Stumme in LNCS (2006). (Vol. 4011) 411–426.
    • Wege zur Entdeckung von Communities in Folksonomies R. Jäschke; A. Hotho; C. Schmitz; G. Stumme S. Braß, A. Hinneburg (Eds.) (2006). 80–84.
    • Mining Association Rules ...
      Mining Association Rules in Folksonomies C. Schmitz; A. Hotho; R. Jäschke; G. Stumme in Studies in Classification, Data Analysis, and Knowledge Organization, V. Batagelj, H.-H. Bock, A. Ferligoj, A. Žiberna (Eds.) (2006). 261–270.
    • Emergent Semantics in BibSonomy A. Hotho; R. Jäschke; C. Schmitz; G. Stumme (2006). (Vol. P-94)
    2005[ to top ]
    • Semantic Web Mining and the Representation, Analysis, and Evolution of Web Space B. Berendt; A. Hotho; G. Stumme V. Svatek, V. Snasel (Eds.) (2005). 1–16.
    • Text Clustern mit Hintergrundwissen (Dissertationsbeschreibung) A. Hotho in Künstliche Intelligenz (KI) (2005). 1 62–64.
    • Collaborative and Usage-Driven Evolution of Personal Ontologies. P. Haase; A. Hotho; L. Schmidt-Thieme; Y. Sure in Lecture Notes in Computer Science, A. Gómez-Pérez, J. Euzenat (Eds.) (2005). (Vol. 3532) 486–499.
    • Proc. of the European Web Mining Forum 2005 B. Berendt; A. Hotho; D. Mladenic; G. Semerano; M. Spiliopoulou; G. Stumme; M. van Someren (2005). Workshop at the 16th Europ. Conf. on Machine Learning (ECML’05) / 9th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD’05).
    • Learning Concept Hierarch...
      Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis P. Cimiano; A. Hotho; S. Staab in Journal on Artificial Intelligence Research (2005). 24 305–339.
    • An Ontology-based Framework for Text Mining S. Bloehdorn; P. Cimiano; A. Hotho; S. Staab in LDV Forum - GLDV Journal for Computational Linguistics and Language Technology (2005). 20(1) 87–112.
    • A Brief Survey of Text Mi...
      A Brief Survey of Text Mining A. Hotho; A. Nürnberger; G. Paaß in LDV Forum - GLDV Journal for Computational Linguistics and Language Technology (2005). 20(1) 19–62.
    • Proceedings of the Workshop on Learning in Web Search (LWS 2005) S. Bloehdorn; W. Buntine; A. Hotho (2005).
    2004[ to top ]
    • A roadmap for web mining:...
      A roadmap for web mining: From web to semantic web B. Berendt; A. Hotho; D. Mladenic; M. Van Someren; M. Spiliopoulou; G. Stumme in Web Mining: From Web to Semantic Web (2004). 1–22.
    • A workshop report: mining for and from the Semantic Web at KDD 2004. A. Hotho; Y. Sure; L. Getoor in SIGKDD Explorations (2004). 6(2) 142–143.
    • Usage Mining for and on the Semantic Web. B. Berendt; A. Hotho; G. Stumme in Data Mining Next Generation Challenges and Future Directions, H. Kargupta, A. Joshi, K. Sivakumar, Y. Yesha (Eds.) (2004). 461–481.
    • Clustern mit Hintergrundwissen. Technical Report (PhD dissertation), A. Hotho PhD thesis, University of Karlsruhe, Universität Karlsruhe (TH), Institut AIFB, D-76128 Karlsruhe. (2004).
    • Clustern mit Hintergrundw...
      Clustern mit Hintergrundwissen A. Hotho in Diski (2004). (Vol. 286) Akademische Verlagsgesellschaft Aka GmbH, Berlin.
    • Conceptual Knowledge Proc...
      Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies P. Cimiano; A. Hotho; G. Stumme; J. Tane in LNCS (2004). (Vol. 2961)
    • Web Mining: From Web to Semantic Web B. Berendt; A. Hotho; D. Mladenic; M. van Someren; M. Spiliopoulou; G. Stumme in LNAI (2004). (Vol. 3209) Springer, Heidelberg.
    • Learning Concept Hierarch...
      Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis P. Cimiano; A. Hotho; S. Staab (2004).
    • Comparing Conceptual, Divise and Agglomerative Clustering for Learning Taxonomies from Text P. Cimiano; A. Hotho; S. Staab R. L. de Mántaras, L. Saitta (Eds.) (2004). 435–439.
    • Personalized Information ...
      Personalized Information Access in a Bibliographic Peer-to-Peer System P. Haase; M. Ehrig; A. Hotho; B. Schnizler (2004). 1–12.
    • Boosting for Text Classif...
      Boosting for Text Classification with Semantic Features S. Bloehdorn; A. Hotho (2004). 70–87.
    • International Workshop on Mining for and from the Semantic Web (MSW2004) A. Hotho; Y. Sure; L. Getoor (2004).
    • Boosting for Text Classification with Semantic Features (reprint) S. Bloehdorn; A. Hotho (2004).
    • Semantic Web Personalization B. Mobasher; S. S. Anand; B. Berendt; A. Hotho (2004).
    • Text Classification by Bo...
      Text Classification by Boosting Weak Learners based on Terms and Concepts S. Bloehdorn; A. Hotho (2004). 331–334.
    • Clustering Ontologies from Text P. Cimiano; A. Hotho; S. Staab (2004).
    2003[ to top ]
    • Text Clustering Based on ...
      Text Clustering Based on Background Knowledge A. Hotho; S. Staab; G. Stumme (2003).
    • Automatic multi-label subject indexing in a multilingual environment B. Lauser; A. Hotho in LNCS (2003). (Vol. 2769) 140–151.
    • Ontologies Improve Text D...
      Ontologies Improve Text Document Clustering A. Hotho; S. Staab; G. Stumme (2003). 541–544.
    • Conceptual User Tracking
      Conceptual User Tracking D. Oberle; B. Berendt; A. Hotho; J. Gonzalez in Lecture Notes in Artificial Intelligence, E. M. Ruiz, J. Segovia, P. S. Szczepaniak (Eds.) (2003). (Vol. 2663) 142–154.
    • Semantic Web - State of the art and future directions R. Studer; R. Volz; G. Stumme; A. Hotho in KI Heft, Special Issue on the Semantic Web (2003). 3 5–9.
    • WordNet improves text doc...
      WordNet improves text document clustering A. Hotho; S. Staab; G. Stumme (2003).
    • On Knowledgeable Unsupervised Text Mining A. Hotho; A. Maedche; S. Staab; V. Zacharias in Text Mining (2003). 131–152.
    • Explaining Text Clusterin...
      Explaining Text Clustering Results using Semantic Structures A. Hotho; S. Staab; G. Stumme in LNCS (2003). (Vol. 2838) 217–228.
    • Building and Using the Semantic Web R. Studer; G. Stumme; S. Handschuh; A. Hotho; B. Motik (2003). 31–34.
    • Proceedings of the 1st European Web Mining Forum (EWMF 2003) B. Berendt; A. Hotho; D. Mladenic; M. van Someren; M. Spiliopoulou; G. Stumme (2003). Workshop at the 14th Europ. Conf. on Machine Learning (ECML’03) / 7th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD’03), Cavtat/Dubrovnik, Croatia.
    • Lehren -- Lernen -- Wissen -- Adaptivität (LLWA 2003) A. Hotho; G. Stumme (2003). Universität Karlsruhe.
    • Ontology-based Text Docum...
      Ontology-based Text Document Clustering. S. Staab; A. Hotho (2003). 451–452.
    2002[ to top ]
    • Text Clustering Based on Good Aggregations A. Hotho; A. Maedche; S. Staab in Künstliche Intelligenz (KI) (2002). 16(4) 48–54.
    • Semantic Web Mining for Building Information Portals (Position Paper) J. Hartmann; A. Hotho; G. Stumme (2002). 34–38.
    • Towards Semantic Web Mini...
      Towards Semantic Web Mining B. Berendt; A. Hotho; G. Stumme in Lecture Notes in Computer Science (LNCS), I. Horrocks, J. A. Hendler (Eds.) (2002). (Vol. 2342) 264–278.
    • KAON - Towards a Large Scale Semantic Web E. Bozsak; M. Ehrig; S. Handschuh; A. Hotho; A. Maedche; B. Motik; D. Oberle; C. Schmitz; S. Staab; L. Stojanovic; N. Stojanovic; R. Studer; G. Stumme; Y. Sure; J. Tane; R. Volz; V. Zacharias in LNCS, K. Bauknecht, A. M. Tjoa, G. Quirchmayr (Eds.) (2002). (Vol. 2455) 304–313.
    • Usage Mining for and on t...
      Usage Mining for and on the Semantic Web G. Stumme; B. Berendt; A. Hotho (2002). 77–86.
    • Conceptual Clustering of Text Clusters A. Hotho; G. Stumme (2002). 37–45.
    • On Knowledgeable Unsupervised Text Mining A. Hotho; A. Maedche; S. Staab; V. Zacharias (2002).
    • Semantic Web Mining B. Berendt; A. Hotho; G. Stumme (2002). Workshop at 13th Europ. Conf. on Machine Learning (ECML’02) / 6th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD’02), Helsinki.
    • KAON - Towards a large sc...
      KAON - Towards a large scale Semantic Web M. Ehrig; S. Handschuh; A. Hotho; A. Maedche; B. Motik; D. Oberle; C. Schmitz; S. Staab; L. Stojanovic; N. Stojanovic; R. Studer; G. Stumme; Y. Sure; J. Tane; R. Volz; V. Zacharias in LNCS, K. Bauknecht, A. M. Tjoa, G. Quirchmayr (Eds.) (2002).
    2001[ to top ]
    • Semantic Web Mining G. Stumme; A. Hotho; B. Berendt (2001). Workshop at 12th Europ. Conf. on Machine Learning (ECML’01) / 5th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD’01), Freiburg.
    • Analyse von Wettbewerbsverlusten im Telekommunikationsmarkt und mögliche Gegenmaßnahmen A. Hotho (2001).
    • Ontology-based Text Clustering A. Hotho; A. Maedche; S. Staab (2001).
    • Text Clustering Based on Good Aggregations A. Hotho; A. Maedche; S. Staab (2001). 607–608.
    • SEAL-II --- The Soft Spot between Richly Structured and Unstructured Knowledge A. Hotho; A. Maedche; S. Staab; R. Studer in Journal of Universal Computer Science (J.UCS) (2001). 7(7) 566–590.
    2000[ to top ]
    • AI for the Web - Ontology-based Community Web Portals S. Staab; J. Angele; S. Decker; A. Hotho; A. Maedche; H.-P. Schnurr; R. Studer; Y. Sure (2000).
    • Semantic Community Web Po...
      Semantic Community Web Portals S. Staab; J. Angele; S. Decker; M. Erdmann; A. Hotho; A. Maedche; H.-P. Schnurr; R. Studer; Y. Sure (2000). 473–491.
    • Enhancing Preprocessing in Data-Intensive Domains using Online-Analytical Processing A. Maedche; A. Hotho; M. Wiese in LNCS (2000). (Vol. 1874) 258–264.
    • Analyse von Wettbewerbsverlusten im Telekommunikationsmarkt und mögliche Gegenmaßnahmen A. Hotho (2000).