Please wait a minute...
New Technology of Library and Information Service  2012, Vol. 28 Issue (1): 58-62    DOI: 10.11925/infotech.1003-3513.2012.01.10
Current Issue | Archive | Adv Search |
Query Semantic Relation Mining from Web Log and Its Application
Duan Jianyong, Xu Jichao, Zhang Mei
College of Information Engineering, North China University of Technology, Beijing 100144, China
Download:
Export: BibTeX | EndNote (RIS)      
Abstract  By mining semantic relation between Web log query terms, this paper puts the HowNet semantic knowledge into clustering algorithm to achieve search engine optimization.In order to understand user needs better, the method uses machine learning algorithms to analyze query log deeply,and puts query items into the depth of analysis.The paper makes the back page more reasonable and presents more accurate Web results to the users.
Key wordsWeb log      Optimization algorithm      Web mining     
Received: 28 November 2011      Published: 26 February 2012
: 

TP391

 

Cite this article:

Duan Jianyong, Xu Jichao, Zhang Mei. Query Semantic Relation Mining from Web Log and Its Application. New Technology of Library and Information Service, 2012, 28(1): 58-62.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2012.01.10     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2012/V28/I1/58

[1] Sharma A K,Aggarwal N, Duhan N,et al.Web Search Result Optimization by Mining the Search Engine Query Logs[C].In:Proceedings of 2010 International Conference on Methods and Models in Computer Science(ICM2CS-2010).2010:39-45.

[2] Meij E, Bron M, Huurnik B, et al.Learning Semantic Query Suggestions[C].In: Proceedings of the 8th International Semantic Web Conference(ISWC 2009).2009:424-440.

[3] Ma H,Yang H,King I,et al.Learning Latent Semantic Relations from Click Through Data for Query Suggestion[C].In: Proceeding of the 17th ACM Conference on Information and Knowledge Management. 2008:709-718.

[4] Brin S,Page L.The Anatomy of a Large-scale Hypertextual Web Search Engine[J].Computer Networks and ISDN Systems, 1998,30(1):1-7.

[5] Mo Y F.A Study on Tactics for Corporate Website Development Aiming at Search Engine Optimization[C].In:Proceedings of the 2nd International Workshop on Education Technology and Computer Science.2010:673-675.

[6] 黄志栋,员巧云.基于PageRank算法的索索引擎优化策略[J]. 情报探索 ,2011(1):34-37.

[7] 马晓玲,吴永和.对于搜索引擎优化(SEO)的研究[J]. 情报杂志 ,2005,24(12):119-121.

[8] 费巍,黄如花.基于用户行为分析的搜索引擎优化策略[J]. 图书情报工作 ,2005,49(10):75-77.

[9] 张振幸,李金厚.一种基于义原重合度的词语相似度计算[J]. 信阳师范学院学报:自然科学版 ,2010,23(2):296-299.

[10] 刘群,李素建.基于《知网》的词汇语义相似度的计算[C].见: 第三汉语词汇语义学研讨会 ,台北,中国.2002:59-76.

[11] Wu B, Zhang D F, Lan Q H,et al.An Efficient Frequent Patterns Mining Algorithm Based on Apriori Algorithm and the FP-tree Structure[C].In:Proceedings of the 3rd International Conference on Convergence and Hybrid Information Technology.2008:1099-1102.

[12] Zhang Z T, Yang M Y, Li S,et al.Sogou Query Log Analysis:A Case Study for Collaborative Recommendation or Personalized IR[C].In:Proceedings of 2009 International Conference on Asian Language Processing.2009:304-307.
[1] Wen Tingxin,Li Yangzi,Sun Jingshuang. Extracting Text Features with Improved Fruit Fly Optimization Algorithm[J]. 数据分析与知识发现, 2018, 2(5): 59-69.
[2] Zhan Chunxia,Wang Rongbo,Huang Xiaoxi,Chen Zhiqun. Application of Text Clustering Method Based on Improved CFSFDP Algorithm[J]. 数据分析与知识发现, 2017, 1(4): 94-99.
[3] Gao Changyuan,Yu Jianping,He Xiaoyan. Knowledge Search for Cloud Computing Industry Alliance: An Algorithm Based on Improved Particle Swarm Optimization[J]. 数据分析与知识发现, 2017, 1(3): 81-89.
[4] Jiang Shuhao, Pan Xuhua, Xue Fuliang. An Independent Recommendation Diversity Optimization Algorithm Based on Item Clustering[J]. 现代图书情报技术, 2015, 31(5): 34-41.
[5] Qiang Shaohua, Wu Peng. The Research of Spatial Measure of Users' Mental Model of Website Category from the View of Regional Differences[J]. 现代图书情报技术, 2015, 31(11): 68-74.
[6] Tang Tianbo,Gao Feng. The Application of Visualization Technology in Link Analysis[J]. 现代图书情报技术, 2009, 3(2): 78-82.
[7] Guo Zhenying,Zhao Wenbing,Wei Yuhui. Analysis and Design on Electronic Resource Log Statistic System[J]. 现代图书情报技术, 2008, 24(9): 102-106.
[8] Ding Yi. on the Specific Topic on Web[J]. 现代图书情报技术, 2005, 21(6): 26-29.
[9] Pu Xiaoge. Design an Information Mining System Based on Web[J]. 现代图书情报技术, 2005, 21(4): 27-30.
[10] Pan Youneng,Deng Sanhong. Web Mining Research Based on XML and Association Rules[J]. 现代图书情报技术, 2004, 20(7): 30-34.
[11] Zou Yuan,Niu Zhendong. Website Selfadjustment Strategy for Distance  Learning Using Fuzzy Clustering[J]. 现代图书情报技术, 2004, 20(3): 5-9.
[12] Liu Shengguo. Research on Data Preprocessing Method in Web Log Mining[J]. 现代图书情报技术, 2004, 20(12): 55-57.
[13] Wang Yan. The Application of Data Mining in Digital Library[J]. 现代图书情报技术, 2002, 18(5): 8-10.
[14] Gao Yan,Hu Jingtao. Principles、Methods and Application of Web Mining[J]. 现代图书情报技术, 2002, 18(3): 51-53.
[15] Chen Dingquan. An Review of Web Information Retrieval[J]. 现代图书情报技术, 2002, 18(2): 39-41.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn