Term Weighting in Information Retrieval Using the Term Precision Model
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The ability to effectively rank retrieved documents in order of their probable relevance to a query is a critical factor in statistically-based keyword retrieval systems. This paper summarizes a set of experiments with different methods of term weighting for documents, using measures of term importance within an entire document collection, term importance within a given document, and document length. It is shown that significant improvements over no term weighting can be made using a combination of weighting measures and normalizing for document length.