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- W2296977009 abstract "Classically, information retrieval systems have been static, meaning they perform the same sequence of actions on every query. In this paper we examine the possibility of using machine learning techniques to create a dynamic information retrieval system. Specifically, it is shown that by using artificial neural networks to predict whether or not a particular information retrieval technique will be helpful on a given query, it is possible to improve the overall quality of documents returned by the system and reduce the CPU time necessary to do the retrieval. To do this we introduce threshold training, where neural networks are trained on a select subset of the available instances in order to improve prediction performance." @default.
- W2296977009 created "2016-06-24" @default.
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- W2296977009 date "2001-08-01" @default.
- W2296977009 modified "2023-09-26" @default.
- W2296977009 title "Predicting the Benefits of Information Retrieval Techniques TITLE2" @default.
- W2296977009 hasPublicationYear "2001" @default.
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