Combining and selecting characteristics of information use
Ian Ruthven, Mounia Lalmas, Keith van Rijsbergen
Abstract
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Ian Ruthven, Mounia Lalmas, Keith van Rijsbergen
Abstract
Open-access reader
Abstract In this article we report on a series of experiments designed to investigate the combination of term and document weighting functions in information retrieval. We describe a series of weighting functions, each of which is based on how information is used within documents and collections, and use these weighting functions in two types of experiments: one based on combination of evidence for ad hoc retrieval, the other based on selective combination of evidence within a relevance feedback situation. We discuss the difficulties involved in predicting good combinations of evidence for ad hoc retrieval, and suggest the factors that may lead to the success or failure of combination. We also demonstrate how, in a relevance feedback situation, the relevance assessments can provide a good indication of how evidence should be selected for query term weighting. The use of relevance information to guide the combination process is shown to reduce the variability inherent in combination of evidence.
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Abstract In this article we report on a series of experiments designed to investigate the combination of term and document weighting functions in information retrieval. We describe a series of weighting functions, each of which is based on how information is used within documents and collections, and use these weighting functions in two types of experiments: one based on combination of evidence for ad hoc retrieval, the other based on selective combination of evidence within a relevance feedback situation. We discuss the difficulties involved in predicting good combinations of evidence for ad hoc retrieval, and suggest the factors that may lead to the success or failure of combination. We also demonstrate how, in a relevance feedback situation, the relevance assessments can provide a good indication of how evidence should be selected for query term weighting. The use of relevance information to guide the combination process is shown to reduce the variability inherent in combination of evidence.
Key concepts: Weighting, Relevance (law), Computer science, Information retrieval, Term (time), Relevance feedback, Process (computing), Data mining