Regression Rank: Learning to Meet the Opportunity of Descriptive Queries
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
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We present two simple but effective smoothing techniqes for the standard language model (LM) approach to information retrieval [12]. First, we extend the unigram Dirichlet smoothing technique popular in IR [17] to bigram modeling [16]. Second, we propose a method of collection expansion for more robust estimation of the LM prior, particularly intended for sparse collections. Retrieval experiments on the MALACH archive [9] of automatically transcribed and manually summarized spontaneous speech interviews demonstrates strong overall system performance and the relative contribution of our extensions.