Semantic Web

The Data Science Chair researches semantic relations in the web and the real world. Relations exist for example between objects (the apple is in the basket), persons (Tom and Annie are friends) and general concepts (dogs are canines) and may be leveraged from different sources: link networks, hashtags, text, tags or user behaviour. We develop new methods to extract and classify semantic entities and relations and utilize them to build ontologies, which in turn can be applied to various tasks like language recognition or question answering systems.

Projects

We are currently working on the following projects:

Selected Publications

Here is a list of selected publications. You can find the full list here.

ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings. Hettinger, Lena; Dallmann, Alexander; Zehe, Albin; Niebler, Thomas; Hotho, Andreas in Proceedings of International Workshop on Semantic Evaluation (SemEval-2018) (2018).
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@inproceedings{hettinger2018semeval, address = {New Orleans, LA, USA}, author = {Hettinger, Lena and Dallmann, Alexander and Zehe, Albin and Niebler, Thomas and Hotho, Andreas}, booktitle = {Proceedings of International Workshop on Semantic Evaluation (SemEval-2018)}, keywords = {word}, title = {ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings}, year = 2018 }
Learning Semantic Relatedness from Human Feedback Using Relative Relatedness Learning. Niebler, Thomas; Becker, Martin; Pölitz, Christian; Hotho, Andreas in ISWC’17 (2017).
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@inproceedings{niebler2017learning_3, author = {Niebler, Thomas and Becker, Martin and Pölitz, Christian and Hotho, Andreas}, booktitle = {ISWC'17}, keywords = {semantics}, title = {Learning Semantic Relatedness from Human Feedback Using Relative Relatedness Learning}, year = 2017 }
Extracting Semantics from Unconstrained Navigation on Wikipedia. Niebler, Thomas; Schlör, Daniel; Becker, Martin; Hotho, Andreas in KI (2016). 30(2) 163–168.
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@article{journals/ki/NieblerS0H16, author = {Niebler, Thomas and Schlör, Daniel and Becker, Martin and Hotho, Andreas}, journal = {KI}, keywords = {wikipedia}, number = 2, pages = {163-168}, title = {Extracting Semantics from Unconstrained Navigation on Wikipedia}, volume = 30, year = 2016 }
Discovering Shared Conceptualizations in Folksonomies. Jäschke, Robert; Hotho, Andreas; Schmitz, Christoph; Ganter, Bernhard; Stumme, Gerd in Web Semantics: Science, Services and Agents on the World Wide Web (2008). 6(1) 38–53.
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Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.

@article{jaeschke2008discovering, abstract = {Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.}, author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd}, booktitle = {Semantic Web and Web 2.0}, journal = {Web Semantics: Science, Services and Agents on the World Wide Web}, keywords = {taggingsurvey}, month = {feb}, number = 1, pages = {38–53}, title = {Discovering Shared Conceptualizations in Folksonomies}, volume = 6, year = 2008 }
Ontologies Improve Text Document Clustering. Hotho, A.; Staab, S.; Stumme, G. in Proc. of the ICDM 03, The 2003 IEEE International Conference on Data Mining (2003). 541–544.
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@inproceedings{hotho_icdm03, author = {Hotho, A. and Staab, S. and Stumme, G.}, booktitle = {Proc. of the ICDM 03, The 2003 IEEE International Conference on Data Mining}, keywords = {text}, pages = {541-544}, title = {Ontologies Improve Text Document Clustering}, year = 2003 }

Projects

PoSTs I & II

Selected Publications

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