SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using lexical-semantic relations
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Query expansion using local and global document analysis
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Fuzzy information systems: managing uncertainty in databases and information retrieval systems
Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
Supporting web query expansion efficiently using multi-granularity indexing and query processing
Data & Knowledge Engineering
Information Processing and Management: an International Journal - Special issue on interactivity at the text retrieval conference (TREC)
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Context-Sensitive Semantic Query Expansion
ICAIS '02 Proceedings of the 2002 IEEE International Conference on Artificial Intelligence Systems (ICAIS'02)
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Modern Information Retrieval Systems match the terms contained in a user's query with available documentsthrough the use of an index. In this work, we propose a method for expanding the query with its associated terms, in order to increase the system recall. The proposed method is based on a novel fuzzy clustering of the index terms, using their common occurrence in documents as clustering criterion. The clusters which are relevant to the terms of the query form the query context. The terms of the clusters that belong to the context are used to expand the query. Clusters participate in the expansion according to their degree of relevance to the query. Precision of the result is thus improved. This statistical approach for query expansion is useful when no a priori semantic knowledge is available.