Deutsch Intern
    Data Science Chair

    Prof. Dr. Andreas Hotho

    Head of Data Science Chair and Founding Spokesman of CAIDAS 

    Chair of Data Science (Informatik X)
    University of Würzburg
    Am Hubland
    97074 Würzburg

    Email: hotho[at]informatik.uni-wuerzburg.de
    Phone:(+49 931) 31 - 88453
    Fax: (+49 931) 31 - 86732

    Office: Room B012 (Computer Science Building M2)
    Office Hours: By appointment only

    About me

    I am a professor at the University of Würzburg and the head of the data science chair (former DMIR group) and the founding spokesman of the Center for Artificial Intelligence and Data Science. Prior, I was a senior researcher at the University of Kassel. I started my research at the AIFB Institute at the University of Karlsruhe where I was working on text mining, ontology learning and semantic web related topics. My previous work also involved working at the KDE group of the University of Kassel on topics like data mining, semantic web mining and social media analysis. For a couple of years I've been a member of the L3S Research Center located in Hannover.

    Research interests

    In general, my current research focus is on data science (formerly known as data mining), text mining and semantic web. 

    Meanwhile, for many years I have followed the idea to combine the processing of natural language with the explicitly represented knowledge known today as knowledge graphs. This naturally leads to research on a combination of Text Mining and NLP methods like representation learning, information extraction, metric learning and ontology learning with research on Semantic Web, or Web Science. To reach these goals, I use and adopt NLP, machine learning and data mining methods. Beside that, I also work on Sentiment Analysis, genre classification and quotation detection. I have applied these methods on historic literature, but also on Social Media data, most recently on chat messages from Twitch.tv

    Other areas I’m interested in and working on are ranking, recommendation and behavior analysis methods. Additionally, my research interests include Anomaly Detection and the analysis of Time Series mostly on the web but recently also on ERP and environmental data. Since many of these problems can be approached by black box machine learning and deep learning methods, another research area of mine is on explainable AI, to gather insights and understand the models.

    To demonstrate my results, my group is working on different application systems: BibSonomy, Everyaware and We4Bee.  




    • SWSA Ten-Year Award: "Semantic Grounding of Tag Relatedness in Social Bookmarking Systems", Ciro Cattuto, Dominik Benz, Andreas Hotho, Gerd Stumme at the International Semantic Web Conference 2018 (link )
    • Best paper award: “Philipp Singer, Denis Helic, Andreas Hotho and Markus Strohmaier, HypTrails: A Bayesian Approach for Comparing Hypotheses About Human Trails on the Web” at WWW Conference 2015 (link)
    • Honorable mention of the paper: “Ciro Cattuto, Dominik Benz, Andreas Hotho and Gerd Stumme, Semantic Grounding of Tag Relatedness in Social Bookmarking Systems” at ISWC 2008 (link)
    • The 7 years most influential paper award: “Information Retrieval in Folksonomies: Search and Ranking”, Andreas Hotho, Robert Jäschke, Christoph Schmitz, Gerd Stumme at ESWC 2013 (link )

    Selected Publications

    • iNALU: Improved Neural Ar... - Download
      iNALU: Improved Neural Arithmetic Logic Unit. Schlör, Daniel; Ring, Markus; Hotho, Andreas in Frontiers in Artificial Intelligence (2020). 3 71.
    • Emote-Controlled: Obtaining Implicit Viewer Feedback through Emote based Sentiment Analysis on Comments of Popular Twitch.tv Channels. Kobs, Konstantin; Zehe, Albin; Bernstetter, Armin; Chibane, Julian; Pfister, Jan; Tritscher, Julian; Hotho, Andreas in ACM Transactions on Social Computing (2020). 3(2) 1–34.
    • Participatory Patterns in... - Download
      Participatory Patterns in an International Air Quality Monitoring Initiative. Sîrbu, Alina; Becker, Martin; Caminiti, Saverio; De Baets, Bernard; Elen, Bart; Francis, Louise; Gravino, Pietro; Hotho, Andreas; Ingarra, Stefano; Loreto, Vittorio; Molino, Andrea; Mueller, Juergen; Peters, Jan; Ricchiuti, Ferdinando; Saracino, Fabio; Servedio, Vito D. P.; Stumme, Gerd; Theunis, Jan; Tria, Francesca; Van den Bossche, Joris in PLoS ONE (2015). 10(8) e0136763.
    • Hyptrails: A bayesian app... - Download
      Hyptrails: A bayesian approach for comparing hypotheses about human trails. Singer, P.; Helic, D.; Hotho, A.; Strohmaier, M. (2015).
    • Awareness and Learning in... - Download
      Awareness and Learning in Participatory Noise Sensing. Becker, Martin; Caminiti, Saverio; Fiorella, Donato; Francis, Louise; Gravino, Pietro; Haklay, Mordechai (Muki); Hotho, Andreas; Loreto, Vittorio; Mueller, Juergen; Ricchiuti, Ferdinando; Servedio, Vito D. P.; Sîrbu, Alina; Tria, Francesca in PLoS ONE (2013). 8(12) e81638.
    • Collective Information Ex... - Download
      Collective Information Extraction with Context-Specific Consistencies. Klügl, Peter; Toepfer, Martin; Lemmerich, Florian; Hotho, Andreas; Puppe, Frank in Lecture Notes in Computer Science, P. A. Flach, T. D. Bie, N. Cristianini (eds.) (2012). (Vol. 7523) 728–743.
    • The Social Bookmark and P... - Download
      The Social Bookmark and Publication Management System BibSonomy. Benz, Dominik; Hotho, Andreas; Jäschke, Robert; Krause, Beate; Mitzlaff, Folke; Schmitz, Christoph; Stumme, Gerd in The VLDB Journal (2010). 19(6) 849–875.
    • Tag Recommendations in So... - Download
      Tag Recommendations in Social Bookmarking Systems. Jäschke, Robert; Marinho, Leandro; Hotho, Andreas; Schmidt-Thieme, Lars; Stumme, Gerd in AI Communications, (E. Giunchiglia, ed.) (2008). 21(4) 231–247.
    • Learning Ontologies to Im... - Download
      Learning Ontologies to Improve Text Clustering and Classification. Bloehdorn, Stephan; Cimiano, Philipp; Hotho, Andreas in From Data and Information Analysis to Knowledge Engineering (2006). 334–341.
    • Learning Concept Hierarch... - Download
      Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis. Cimiano, Philipp; Hotho, Andreas; Staab, Steffen in Journal on Artificial Intelligence Research (2005). 24 305–339.