Learning and optimization of an aspect hidden Markov model for query language model generation


The Relevance Model (RM) incorporates pseudo relevance feedback to derive query language model and has shown a good performance. Generally, it is based on uni-gram models of individual feedback documents from which query terms are sampled independently. In this paper, we present a new method to build the query model with latent state machine (LSM) which… (More)


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