A probabilistic model of information retrieval: development and comparative experiments Part 1

被引:285
作者
Sparck-Jones, K
Walker, S
Robertson, SE
机构
[1] Univ Cambridge, Comp Lab, Cambridge CB2 3QG, England
[2] Microsoft Res Ltd, Cambridge CB2 3NH, England
[3] City Univ London, Dept Informat Sci, London EC1V 0HB, England
关键词
information retrieval; retrieval history; probabilistic model; term weighting; experiments;
D O I
10.1016/S0306-4573(00)00015-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The paper combines a comprehensive account of a 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 ave given in Part 1. Key results are summarised in Part 2. (C) 2000 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:779 / 808
页数:30
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