Commenced in January 2007
Paper Count: 30578
A Novel Approach to Improve Users Search Goal in Web Usage Mining
Abstract:Web mining is to discover and extract useful Information. Different users may have different search goals when they search by giving queries and submitting it to a search engine. The inference and analysis of user search goals can be very useful for providing an experience result for a user search query. In this project, we propose a novel approach to infer user search goals by analyzing search web logs. First, we propose a novel approach to infer user search goals by analyzing search engine query logs, the feedback sessions are constructed from user click-through logs and it efficiently reflect the information needed for users. Second we propose a preprocessing technique to clean the unnecessary data’s from web log file (feedback session). Third we propose a technique to generate pseudo-documents to representation of feedback sessions for clustering. Finally we implement k-medoids clustering algorithm to discover different user search goals and to provide a more optimal result for a search query based on feedback sessions for the user.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1108819Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1691
 Weiyao Lin, Member, IEEE, and Zhaohui Zheng, "A New Algorithm for Inferring User Search Goals with Feedback Sessions." IEEE Transactions on Knowledge and Data Engineering, vol. 25, no. 3, March 2013.
 B. Uma Maheswari, Dr. P.Sumathi,”A New Clustering and Preprocessing for Web Log Mining”, World Congress on Computing and Communication Technologies 2014.
 Castellano, G., A. M. Fanelli, “A Log Data Preprocessor for mining Web browsing patterns”. Proceedings of the 6th WSEAS Int. Conf. on Artificial Intelligence, Knowledge Engineering and Data Bases, Corfu Island, Greece, February 16-19 , 2007.
 Khasawneh, N. and Chan, “Active User-Based and Ontology-Based Web Log Data Preprocessing for Web Usage Mining”. Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings) (WI'06) 0-7695-2747- 7/06© 2006.
 Li. X, Y.-Y Wang, and A. Acero, “Learning Query Intent from Regularized Click Graphs,” Proc. 31st Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR ’08), pp. 339-346, 2008.
 Murata, T. and K. Saito. “Extracting Users' Interests from Web Log Data”, Proceedings of IEEE/WIC/ACM Conference on Web Intelligence (WI 2006 Main Conference Proceedings) (WI'06) 0-7695-2747-7/06, 2006.
 Nicolas Labroche, “Learning Web Users Profiles with Relational Clustering Algorithms” In IADIS International WWW/Internet Conference, 503–510, 2010.
 Noor Kamal Kaur, Usvir Kaur, Dr. Dheerendra Singh, “K-Medoid Clustering Algorithm- A Review”, International Journal of Computer Application and Technology (IJCAT) Volume 1 Issue 1 ISSN: 2349- 1841, April 2014.
 O. A. Mohamed Jafar, R. Sivakumar, “A Study on Possibilistic and Fuzzy Possibilistic C-Means Clustering Algorithms for Data Clustering” - International Conference on Emerging Trends in Science, Engineering and Technology2012.
 Pabarskaite, Z, “Implementing Advanced Cleaning and End - User Interpretability Technologies in Web Log Mining”. 24th Int. Conf. information Technology Interfaces/ TI, Cavtat, Croatia, June 24-27, 2002.
 Raghavi Chouhan, Abhishek Chauhan “An Ameliorated Partitioning Clustering Algorithm for Large Data Sets”, International Journal of Advanced Research in Computer and Communication Engineering Vol. 3, Issue 7, July 2014.
 Rupinder Kaur, Simarjeet Kaur, “A Review: Techniques for Clustering of Web Usage Mining”, International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064, 2012.
 Suneetha, K. R. and D. R. Krishnamoorthi, "Identifying User Behaviour by Analyzing Web Server Access Log File." Published in IJCSNS International Journal of Computer Science and Network Security, vol.9 No.4, April 2009.
 Uichin Lee, Zhenyu Liu, Junghoo Cho “Automatic Identification of User Goals in Web Search” In Proceedings of VLDB '04, 2004.
 Wahab, M. H. A., M. N. H. Mohd, et al, “Data Preprocessing on Web Server Logs for Generalized Association Rules Mining Algorithm”. World Academy of Science, Engineering and Technology 48 2008.
 Xuanhui Wang, Cheng Xiang Zhai, “Learn from Web Search Logs to Organize Search Results” Journal of Graph Algorithms and Applications, 2010.
 Yuan, F., L.-J. Wang, et al. Study on “Data Preprocessing Algorithm in Web Log Mining”. Proceedings of the Second International Conference on Machine Learning and Cybernetics Wan, 2-5 November 2003.