Improve the Search and Ranking with Neural Networks

Yu Wen Chen; Ju Zhang; Kun Hua Zhong; Lei Feng Liu; Yuan Yao

doi:10.4028/www.scientific.net/AMM.441.721

Paper Titles

Personal Identification Using Finger-Knuckle-Print Based on Local Binary Pattern
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Color and Texture Features Based Image Retrieval
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A Study on Approximation Performances of General Regression Neural Network
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The Research of Data Stream Classification Based on Rough Set Theory-Neural Network Integration
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Improve the Search and Ranking with Neural Networks
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Design Method of Beam Forming Using Genetic Algorithm
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Decision Tree Generation Algorithm without Pruning
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Application of Probabilistic Neural Network in Pattern Classification
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Complete Convergence of Generalized Pairwise NQD Sequences
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 441Improve the Search and Ranking with Neural...

Improve the Search and Ranking with Neural Networks

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.

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Periodical:

Applied Mechanics and Materials (Volume 441)

Pages:

721-726

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.441.721

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Online since:

December 2013

Authors:

Yu Wen Chen, Ju Zhang, Kun Hua Zhong, Lei Feng Liu, Yuan Yao

Keywords:

Click-Tracking, Neural Network (NN), Ranking, Search

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