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Language Model Adaptation for Relevance Feedback in Information Retrieval
2008
2008 6th International Symposium on Chinese Spoken Language Processing
Language model is a popular method of exploiting linguistic regularities for document retrieval. To improve retrieval performance, the scheme of relevance feedback is adopted by adjusting the query language model using the information feedback from the retrieved documents. This study presents a new Bayesian learning approach to instantaneous and unsupervised adaptation of language model for adaptive information retrieval. We aim to compensate the domain mismatch between query and documents by
doi:10.1109/chinsl.2008.ecp.84
dblp:conf/iscslp/ChangC08
fatcat:j2dwhlzabfggbij7bkqlcu6trm