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- W2106264700 abstract "The full text retrieval system can receive constant feedback in the form of user behavior. In the case of a search engine, each user will immediately provide information about how much he likes the results for a given search by clicking on one result and choosing not to click on the others. This paper will look at a way to record when a user clicks on a result after a query, and design a Click-Tracking Network. Then training it with BP neural networks to intelligently improve the rankings of the results for users. Finally, we implement a search and ranking system content-based ranking and improve the search and ranking with neural network. By experiments we have shown good results." @default.
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- W2106264700 date "2013-12-01" @default.
- W2106264700 modified "2023-10-16" @default.
- W2106264700 title "Improve the Search and Ranking with Neural Networks" @default.
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- W2106264700 doi "https://doi.org/10.4028/www.scientific.net/amm.441.721" @default.
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