KMS Chongqing Institute of Green and Intelligent Technology, CAS
| Improve the search and ranking with neural networks | |
Chen, Yu Wen; Zhang, Ju ; Zhong, Kun Hua; Liu, Lei Feng; Yao, Yuan
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| 2014 | |
| 摘要 | 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. © (2014) Trans Tech Publications, Switzerland. |
| 语种 | 英语 |
| DOI | 10.4028/www.scientific.net/AMM.441.721 |
| 会议(录)名称 | 2013 3rd International Conference on Machinery Electronics and Control Engineering, ICMECE 2013
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| 页码 | 721-726 |
| 收录类别 | EI |
| 会议地点 | Jinan, Shandong, China |
| 会议日期 | November 29, 2013 - November 30, 2013 |
