Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Finding parts in very large corpora
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Automatic detection of causal relations for Question Answering
MultiSumQA '03 Proceedings of the ACL 2003 workshop on Multilingual summarization and question answering - Volume 12
The distributional inclusion hypotheses and lexical entailment
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Extraction of hierarchies based on inclusion of co-occurring words with frequency information
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Acquisition of a New Type of Lexical-Semantic Relation from German Corpora
Proceedings of the 2008 conference on New Trends in Multimedia and Network Information Systems
A method of extraction and visualisation for relationships among objects on web
International Journal of Intelligent Systems Technologies and Applications
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At least two kinds of relations exist among related words: taxonomical relations and thematic relations. Both relations identify related words useful to language understanding and generation, information retrieval, and so on. However, although words with taxonomical relations are easy to identify from linguistic resources such as dictionaries and thesauri, words with thematic relations are difficult to identify because they are rarely maintained in linguistic resources. In this paper, we sought to extract thematically (non-taxonomically) related word sets among words in documents by employing case-marking particles derived from syntactic analysis. We then verified the usefulness of word sets with non-taxonomical relation that seems to be a thematic relation for information retrieval.