A probabilistic model of information retrieval: development and comparative experiments
Information Processing and Management: an International Journal
Language model information retrieval with document expansion
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
A Comparative Study of Utilizing Topic Models for Information Retrieval
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
The ESA retrieval model revisited
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Using wiktionary for computing semantic relatedness
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Concept-based feature generation and selection for information retrieval
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Using Wikipedia and Wiktionary in domain-specific information retrieval
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Insights into explicit semantic analysis
Proceedings of the 20th ACM international conference on Information and knowledge management
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In this paper, we complement the term frequency, which is used in many bag-of-words based information retrieval models, with information about the semantic relatedness of query and document terms. Our experiments show that when employed in the standard probabilistic retrieval model BM25, the additional semantic information significantly outperforms the standard term frequency, and also improves the effectiveness when additional query expansion is applied. We further analyze the impact of different lexical semantic resources on the IR effectiveness.