Computer Science ›› 2016, Vol. 43 ›› Issue (3): 305-308.doi: 10.11896/j.issn.1002-137X.2016.03.057

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Retrieval Intention Modeling Based on Perception Hash Algorithm and Browsing Preferences

SHI Hong-bin and GUO Ke-hua   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Aiming at the problem of commodity retrieval and ranking,the ranking method based on user’s query request and browsing preferences was proposed.The objective is to improve user’s satisfaction to the retrieval result without increasing input requests.The commodity records from database were selected and ranked primly according to the query requests.Based on this,user’s interest degree was analyzed by their browsing behavior and the user preference model was refined from browsing history.Then the similarity of the attribute information of commodities and preference model was calculated,and the ranking result was adjusted.The experimental result shows that the retrieval result taking user’s preference into consideration is more fit to their retrieval intention.

Key words: User preference,Personalized retrieval,Ranking algorithm,E-commerce

[1] Liu Q,Tan C C,Wu J,et al.Towards Differential Query Servi-ces in Cost-Efficient Clouds[J].IEEE Transactions on Parallel & Distributed Systems,2014,25(6):1648-1658
[2] Chen Ming-jing,Yao Jian-rong,Tang Zhi-hao.Researching onAlgorithm of Searching Engine for E-Commerce[J].Computer Engineering and Application,2006,42(3):209-211(in Chinese) 陈明晶,姚建荣,唐志豪.电子商务系统的商品搜索算法研究[J].计算机工程与应用,2006,42(3):209-211
[3] Chen L,L’Abbate M,Thiel U,et al.Increasing the customer’s choice:query expansion based on the layer-seeds method and its application in e-commerce[C]∥ IEEE International Conference on E-Technology,E-Commerce and E-Service.2004:317-324
[4] Zhou D,Lawless S,Wade V.Improving search via personalized query expansion using social media[J].Information Retrieval,2012,15(3/4):218-242
[5] Eakins J,Graham M,Franklin T.Content-based image retrieval [R].JISC Technology Applications Programme Report,1999
[6] Chen Zhi-gang,Wang Jiang-tao,Deng Xiao-heng.A trust model based on semantic distance for pervasive environments[J].Security & Communication Networks,2014,7(9):1322-1330
[7] Liu Q,Tan C C,Wu J,et al.Cooperative private searching inclouds[J].Journal of Parallel & Distributed Computing,2012,72(8):1019-1031
[8] Wang Y,Li H X,Yen G,et al.MOMMOP:Multiobjective Optimization for Locating Multiple Optimal Solutions of Multimodal Optimization Problems[J].IEEE Transactions on Cybernetics,2015,45(4):830-843
[9] Speretta M,Gauch S.Personalized search based on user search histories[C]∥The 2005 IEEE/WIC/ACM International Conference on Web Intelligence,2005.IEEE,2005:622-628
[10] Tang Xiao-ling,He Tian-yun.A Research on Topic Preference- Based Personalized Search Model[J].Journal of Intelligence,2011,30(4):133-136(in Chinese) 唐晓玲,何天云.基于主题偏好的个性化检索模型研究[J].情报杂志,2011,30(4):133-136
[11] Liang T P,Lai H J.Discovering User Interests from Web Browsing Behavior:An Application to Internet News Services[C]∥Proceedings of Annual Hawaii International Conference on System Sciences.Hicss,2002:2718-2727
[12] Mac Aoidh E,Bertolotto M,Wilson D C.Analysis of implicit interest indicators for spatial data[C]∥Proceedings of the 15th Annual ACM International Symposium on Advances in Geographic Information Systems.ACM,2007:1-4
[13] Claypool M,Le P,Wased M.Implicit interest indicators[C]∥Proceedings of the 6th International Conference on Intelligent User Interfaces.ACM,2001:33-40
[14] Ma Z,Pant G,Sheng O R L.Interest-based personalized search[J].ACM Transactions on Information Systems (TOIS),2007,25(1):5
[15] Teevan J,Morris M R,Bush S.Discovering and using groups to improve personalized search[C]∥Proceedings of the Second ACM International Conference on Web Search and Data Mi-ning.ACM,2009:15-24
[16] Lu D,Li Q.Personalized search on Flickr based on searcher’s preference prediction[C]∥Proceedings of the 20th International Conference Companion on World Wide Web.ACM,2011:81-82
[17] Kumar R,Sharan A.Personalized Web search using browsinghistory and domain knowledge[C]∥2014 International Confe-rence on Issues and Challenges in Intelligent Computing Techniques (ICICT).IEEE,2014:493-497

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