WordSieve: A method for real-time context extraction

被引:0
|
作者
Bauer, T [1 ]
Leake, DB [1 ]
机构
[1] Indiana Univ, Dept Comp Sci, Bloomington, IN 47405 USA
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In order to be useful. intelligent information retrieval agents must provide their users with context-relevant information. This paper presents WordSieve, all algorithm for automatically extracting information about the context in which documents are consulted during web browsing. Using information extracted from the stream of documents consulted by the user. WordSieve automatically builds context profiled which differentiate sets of documents that users tend to access in groups These profiles are used in a research-aiding system to index documents consulted in the current context and them to users ill similar future contexts. Ill initial experiments oil the capability to match documents to the task contexts ill which they were consulted. WordSieve indexing outperformed indexing based on Term Frequency/Inverse Document Frequency, a common document indexing approach for intelligent agents in information retrieval.
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页码:30 / 44
页数:15
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