Semantic Information Management

Semantic Information Management (SIM) leverages semantic processing techniques for adding structure to unstructured information for more accurate, high-precision and high-recall information search and retrieval.

Information comes in various forms and formats, including business documents, web pages, user manuals, FAQs, and software documentation. In an ever-increasing mass of information, finding the right piece of information is becoming more and more difficult.

Feel free to download our SIM Flyer.

Projects in Semantic Information Management

  • Theseus-TEXO: Community-enabled semantic service retrieval for the future Internet of services.
  • Theseus-MEDICO: Semantically enhanced intelligent image retrieval in the medical domain.
  • SIR – Semantic Information Retrieval: Enhancing conventional IR by integrating lexical-semantic knowledge.
  • DKPro: Ready-to-use robust NLP components based on IBM's UIMA Framework.
  • SIGMUND: Semantics- and Emotion-Based Conversation Management in Customer Support.

Selected publications

Iryna Gurevych, Christof Müller, Torsten Zesch:

What to be? Electronic Career Guidance Based on Semantic Relatedness. In: Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL 2007). pp. 1032–1039, Association for Computational Linguistics, 2007.

Torsten Zesch, Christof Müller, Iryna Gurevych:
Extracting Lexical Semantic Knowledge from Wikipedia and Wiktionary. In: Proceedings of the Conference on Language Resources and Evaluation (LREC), 2008.

Christof Müller, Iryna Gurevych, Max Mühlhäuser:
Integrating Semantic Knowledge into Text Similarity and Information Retrieval. In: Proceedings of the First IEEE International Conference on Semantic Computing (ICSC). pp. 257–264, IEEE Press, New York, NY, 2007.


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