Query expansion using lexical-semantic relations
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Textual context analysis for information retrieval
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Combining multiple evidence from different types of thesaurus for query expansion
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
On Relevance, Probabilistic Indexing and Information Retrieval
Journal of the ACM (JACM)
Argumentative feedback: a linguistically-motivated term expansion for information retrieval
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Selecting good expansion terms for pseudo-relevance feedback
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Selecting Effective Terms for Query Formulation
AIRS '09 Proceedings of the 5th Asia Information Retrieval Symposium on Information Retrieval Technology
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The objective of this paper is to provide a framework and computational model for automatic query expansion using psuedo relevance feedback. We expect that our model can be helpful in dealing with many important aspects in automatic query expansion in an efficient way. We have performed experiments based on our model using TREC data set. Results are encouraging as they indicate improvement in retrieval efficiency after applying query expansion.