User modeling for personalized Web search with self-organizing map

The widely used Web search engines index and recommend individual Web pages in response to a few keywords queries to assist users in locating relevant documents. However, the Web search engines give different users the same answer set, although the users may have different preferences. A personalized Web search would carry out the search for each user according to his or her preferences. To conduct the personalized Web search, the authors provide a novel approach to model the user profile with a self-organizing map (SOM). Their results indicate that SOM is capable of helping the user to find the related category for each query used in the Web search to make a personalized Web search effective.

[1]  Robert Kass,et al.  Modeling users' interests in information filters , 1992, CACM.

[2]  Andreas Rauber,et al.  The growing hierarchical self-organizing map: exploratory analysis of high-dimensional data , 2002, IEEE Trans. Neural Networks.

[3]  Sun-Yuan Kung,et al.  Principal Component Neural Networks: Theory and Applications , 1996 .

[4]  Wei-Ying Ma,et al.  Query Expansion by Mining User Logs , 2003, IEEE Trans. Knowl. Data Eng..

[5]  James C. Bezdek,et al.  A note on self-organizing semantic maps , 1995, IEEE Trans. Neural Networks.

[6]  Hinrich Schütze,et al.  Personalized search , 2002, CACM.

[7]  Henry Lieberman,et al.  Letizia: An Agent That Assists Web Browsing , 1995, IJCAI.

[8]  Wei-Ying Ma,et al.  Improving pseudo-relevance feedback in web information retrieval using web page segmentation , 2003, WWW '03.

[9]  Douglas B. Terry,et al.  Using collaborative filtering to weave an information tapestry , 1992, CACM.

[10]  I. Jolliffe.  Principal Component Analysis , 2002 .

[11]  Yoav Shoham,et al.  Learning Information Retrieval Agents: Experiments with Automated Web Browsing , 1995 .

[12]  Clement T. Yu,et al.  Personalized Web search for improving retrieval effectiveness , 2004, IEEE Transactions on Knowledge and Data Engineering.

[13]  Masatoshi Yoshikawa,et al.  Adaptive web search based on user profile constructed without any effort from users , 2004, WWW '04.

[14]  Michael Lesk,et al.  Word-word associations in document retrieval systems , 1969 .

[15]  Sang-Hui Park,et al.  Self-creating and organizing neural networks , 1994, IEEE Trans. Neural Networks.

[16]  C. Lee Giles,et al.  A system for automatic personalized tracking of scientific literature on the Web , 1999, DL '99.

[17]  Yanchun Zhang,et al.  Effectively Finding Relevant Web Pages from Linkage Information , 2003, IEEE Trans. Knowl. Data Eng..

[18]  Michael Q. Zhang,et al.  Evaluation and comparison of clustering algorithms in analyzing es cell gene expression data , 2002 .

[19]  T. Landauer,et al.  Indexing by Latent Semantic Analysis , 1990 .

[20]  P. W. Foltz,et al.  Using latent semantic indexing for information filtering , 1990, COCS '90.

[21]  Ehud Rivlin,et al.  Placing search in context: the concept revisited , 2002, TOIS.

[22]  Sriram Raghavan,et al.  Searching the Web , 2001, ACM Trans. Internet Techn..

[23]  Susan T. Dumais,et al.  Personalized information delivery: an analysis of information filtering methods , 1992, CACM.

[24]  Samuel Kaski,et al.  Self organization of a massive document collection , 2000, IEEE Trans. Neural Networks Learn. Syst..

[25]  Gerard Salton,et al.  A vector space model for automatic indexing , 1975, CACM.

[26]  Stephen E. Robertson,et al.  Relevance weighting of search terms , 1976, J. Am. Soc. Inf. Sci..

[27]  Gerard Salton,et al.  Improving Retrieval Performance by Relevance Feedback , 1997 .

[28]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[29]  Thorsten Joachims,et al.  Web Watcher: A Tour Guide for the World Wide Web , 1997, IJCAI.

[30]  Katia P. Sycara,et al.  WebMate: a personal agent for browsing and searching , 1998, AGENTS '98.

[31]  Anthony Scime.  WebSifter: an ontology-based personalizable search agent for the Web , 2000, Proceedings 2000 Kyoto International Conference on Digital Libraries: Research and Practice.

[32]  C. Lee Giles,et al.  Self-adaptive user profiles for large-scale data delivery , 2000, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073).

[33]  Sankar K. Pal,et al.  Web mining in soft computing framework: relevance, state of the art and future directions , 2002, IEEE Trans. Neural Networks.