SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
A cooccurrence-based thesaurus and two applications to information retrieval
Information Processing and Management: an International Journal
Information retrieval as statistical translation
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Modern Information Retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Biterm language models for document retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Improving pseudo-relevance feedback in web information retrieval using web page segmentation
WWW '03 Proceedings of the 12th international conference on World Wide Web
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Enterprise Search: Tough Stuff
Queue - Search Engines
Using mutual information to resolve query translation ambiguities and query term weighting
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Active feedback in ad hoc information retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using term relationships in language models for information retrieval
Proceedings of the 14th ACM international conference on Information and knowledge management
Semantic term matching in axiomatic approaches to information retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Context-dependent term relations for information retrieval
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
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Term relations analysis has been used to improve performance in information retrieval. However, it is difficult to choose the appropriate related terms. Co-occurrence analysis and WordNet have been used to obtain mutual information between terms in re-ranking retrieval results and performing query expansion, but it didn't improve the performance as expected. It is difficult to avoid involving noise information and inappropriate related terms with ambiguous sense in the process of finding related terms and computing mutual information. To solve this problem, we propose to add context information in a document when choosing related terms by clustering method, and use Mahalanobis distance instead of Euclidean distance in re-ranking query result with term mutual information. The approach presented in this paper can improve the precision and relevance in enterprise information retrieval significantly to satisfy user's needs.