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A bayesian logistic regression model for active relevance feedback
2008
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '08
Relevance feedback, which traditionally uses the terms in the relevant documents to enrich the user's initial query, is an effective method for improving retrieval performance. The traditional relevance feedback algorithms lead to overfitting because of the limited amount of training data and large term space. This paper introduces an online Bayesian logistic regression algorithm to incorporate relevance feedback information. The new approach addresses the overfitting problem by projecting the
doi:10.1145/1390334.1390375
dblp:conf/sigir/XuA08
fatcat:qu6alsscqngozgqfocau7fvmuy