A probabilistic model of information retrieval: development and comparative experiments: Part 2 |
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| Authors: | K Sparck Jones S Walker S E Robertson |
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| Institution: | a Computer Laboratory, University of Cambridge, New Museums Site, Pembroke Street, Cambridge CB2 3QG, UK;b Microsoft Research Limited, St George House, 1 Guildhall Street, Cambridge CB2 3NH, UK;c Department of Information Science, City University, London, UK |
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| Abstract: | The paper combines a comprehensive account of the probabilistic model of retrieval with new systematic experiments on TREC Programme material. It presents the model from its foundations through its logical development to cover more aspects of retrieval data and a wider range of system functions. Each step in the argument is matched by comparative retrieval tests, to provide a single coherent account of a major line of research. The experiments demonstrate, for a large test collection, that the probabilistic model is effective and robust, and that it responds appropriately, with major improvements in performance, to key features of retrieval situations.Part 1 covers the foundations and the model development for document collection and relevance data, along with the test apparatus. Part 2 covers the further development and elaboration of the model, with extensive testing, and briefly considers other environment conditions and tasks, model training, concluding with comparisons with other approaches and an overall assessment.Data and results tables for both parts are given in Part 1. Key results are summarised in Part 2. |
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| Keywords: | Information retrieval Retrieval theory Probabilistic model Term weighting Experiments |
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