Hypernym discovery based on distributional similarity and hierarchical structures
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Content hole search in community-type content using Wikipedia
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
Extracting concerns and reports on crimes in blogs
AMT'10 Proceedings of the 6th international conference on Active media technology
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With this research we present a system that suggests valuable complementary information relevant to a user's topic of interest, in the form of keywords. For this purpose we have automatically constructed a Web search directory called TORISHIKI-KAI from a large collection of Web documents, using state of the art knowledge acquisition methods. TORISHIKI-KAI maps out the use context of the terms input by the user, and classifies topically related search terms according to semantic categories such as potential troubles, methods or tools in order to help the user find potentially valuable "unknown unknowns".