Abstract
Search engine technology builds on theoretical and empirical research results in the area of information retrieval (IR). This dissertation makes a contribution to the field of language modeling (LM) for IR, which views both queries and documents as instances of a unigram language model and defines the matching function between a query and each document as the probability that the query terms are generated by the document language model. The work described is concerned with three research issues.
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