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- W2355404275 abstract "This paper uses methods of machine learning to enhance the exactness of search engine. It aims to submit a character string which is similar to users' interesting. Decision-tree is used to learn the users' interesting. There are several problems using decision-tree in web pages: how to deal with when the samples have not enough characters; many characters have different importance, how to reflect it in decision-tree; when and how to recreate the decision-tree; perfect tree problem; when we delete character string from decision-tree, which should be chosen; These situations are investigated and solved. Performance of new decision-tree is: validity has enhanced from 70% to 75.4%." @default.
- W2355404275 created "2016-06-24" @default.
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- W2355404275 date "2006-01-01" @default.
- W2355404275 modified "2023-09-25" @default.
- W2355404275 title "Individual Search Agent Based on Machine Learning" @default.
- W2355404275 hasPublicationYear "2006" @default.
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