Mining ontology for automatically acquiring Web user information needs

It is not easy to obtain the right information from the Web for a particular Web user or a group of users due to the obstacle of automatically acquiring Web user profiles. The current techniques do not provide satisfactory structures for mining Web user profiles. This paper presents a novel approach for this problem. The objective of the approach is to automatically discover ontologies from data sets in order to build complete concept models for Web user information needs. It also proposes a method for capturing evolving patterns to refine discovered ontologies. In addition, the process of assessing relevance in ontology is established. This paper provides both theoretical and experimental evaluations for the approach. The experimental results show that all objectives we expect for the approach are achievable.

[1]  Rudolf Kruse,et al.  Uncertainty and Vagueness in Knowledge Based Systems , 1991, Artificial Intelligence.

[2]  Robert A. Hummel,et al.  On the Use of the Dempster Shafer Model in Information Indexing and Retrieval Applications , 1993, Int. J. Man Mach. Stud..

[3]  Umeshwar Dayal,et al.  From User Access Patterns to Dynamic Hypertext Linking , 1996, Comput. Networks.

[4]  Heikki Mannila,et al.  Discovering Generalized Episodes Using Minimal Occurrences , 1996, KDD.

[5]  Philip S. Yu,et al.  Data mining for path traversal patterns in a web environment , 1996, Proceedings of 16th International Conference on Distributed Computing Systems.

[6]  Javed Mostafa,et al.  A multilevel approach to intelligent information filtering: model, system, and evaluation , 1997, TOIS.

[7]  Yonatan Aumann,et al.  Maximal Association Rules: A New Tool for Mining for Keyword Co-Occurrences in Document Collections , 1997, KDD.

[8]  Ophir Frieder,et al.  Information Retrieval: Algorithms and Heuristics , 1998 .

[9]  Tom M. Mitchell,et al.  Learning to Extract Symbolic Knowledge from the World Wide Web , 1998, AAAI/IAAI.

[10]  Sourav S. Bhowmick,et al.  Research Issues in Web Data Mining , 1999, DaWaK.

[11]  Stephen E. Robertson,et al.  The TREC-8 Filtering Track Final Report , 1999, TREC.

[12]  Kyuseok Shim,et al.  Data mining and the Web: past, present and future , 1999, WIDM '99.

[13]  Karen Spärck Jones,et al.  Information Retrieval and Artificial Intelligence , 1999, Artif. Intell..

[14]  Tom M. Mitchell,et al.  Learning to construct knowledge bases from the World Wide Web , 2000, Artif. Intell..

[15]  Chengqi Zhang,et al.  An information filtering model on the Web and its application in JobAgent , 2000, Knowl. Based Syst..

[16]  Oren Etzioni,et al.  Adaptive Web sites , 2000, CACM.

[17]  Jaideep Srivastava,et al.  Web usage mining: discovery and applications of usage patterns from Web data , 2000, SKDD.

[18]  Mark A. Musen,et al.  PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment , 2000, AAAI/IAAI.

[19]  James A. M. McHugh,et al.  Mining the World Wide Web: An Information Search Approach , 2001 .

[20]  Steffen Staab,et al.  Ontology Learning for the Semantic Web , 2002, IEEE Intell. Syst..

[21]  Qiang Yang,et al.  Mining web logs for prediction models in WWW caching and prefetching , 2001, KDD '01.

[22]  James A. M. McHugh,et al.  Mining the World Wide Web , 2001, The Information Retrieval Series.

[23]  Soon Myoung Chung,et al.  Multipass Algorithms for Mining Association Rules in Text Databases , 2001, Knowledge and Information Systems.

[24]  Hinrich Schütze,et al.  Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.

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

[26]  Ning Zhong,et al.  Representation and Construction of Ontologies for Web Intelligence , 2002, Int. J. Found. Comput. Sci..

[27]  Ning Zhong,et al.  In Search of the Wisdom Web , 2002, Computer.

[28]  Yiyu Yao,et al.  User Profile Model: A View from Artificial Intelligence , 2002, Rough Sets and Current Trends in Computing.

[29]  Gabriella Kazai,et al.  Overview of the Initiative for the Evaluation of XML retrieval (INEX) 2002 , 2002, INEX Workshop.

[30]  Zdzislaw Pawlak,et al.  In Pursuit of Patterns in Data Reasoning from Data - The Rough Set Way , 2002, Rough Sets and Current Trends in Computing.

[31]  Fabrizio Sebastiani,et al.  Machine learning in automated text categorization , 2001, CSUR.

[32]  Ning Zhong,et al.  In search of the wisdom web , 2002, Computer.

[33]  Ryszard Janicki.  Towards a Mereological System for Direct Products and Relations , 2002, Rough Sets and Current Trends in Computing.

[34]  Tsau Young Lin,et al.  Database Mining on Derived Attributes , 2002, Rough Sets and Current Trends in Computing.

[35]  Steffen Staab,et al.  Ontology Learning Part One - On Discoverying Taxonomic Relations from the Web , 2002 .

[36]  Kun Chang Lee,et al.  Fuzzy cognitive map approach to web-mining inference amplification , 2002, Expert Syst. Appl..

[37]  Zdzislaw Pawlak,et al.  Rough sets and intelligent data analysis , 2002, Inf. Sci..

[38]  Yuefeng Li,et al.  Extended Random Sets for Knowledge Discovery in Information Systems , 2003, RSFDGrC.

[39]  Yuefeng Li,et al.  Interpretations of association rules by granular computing , 2003, Third IEEE International Conference on Data Mining.

[40]  Jiawei Han,et al.  TSP: mining top-K closed sequential patterns , 2003, Third IEEE International Conference on Data Mining.

[41]  Shusaku Tsumoto,et al.  Visualization of rule's similarity using multidimensional scaling , 2003, Third IEEE International Conference on Data Mining.

[42]  B. Liu,et al.  Learning to Classify Texts Using Positive and Unlabeled Data , 2003, IJCAI.

[43]  David A. Bell,et al.  The rough set approach to association rule mining , 2003, Third IEEE International Conference on Data Mining.

[44]  Yiyu Yao,et al.  Web Log Mining , 2003 .

[45]  Y. Li,et al.  Ontology-based Web mining model: representations of user profiles , 2003, Proceedings IEEE/WIC International Conference on Web Intelligence (WI 2003).

[46]  Kevin Chen-Chuan Chang,et al.  Editorial: special issue on web content mining , 2004, SKDD.

[47]  Ophir Frieder,et al.  Information Retrieval: Algorithms and Heuristics (The Kluwer International Series on Information Retrieval) , 2004 .

[48]  Heiner Stuckenschmidt,et al.  Handbook on Ontologies , 2004, Künstliche Intell..

[49]  Yuefeng Li,et al.  Web mining model and its applications for information gathering , 2004, Knowl. Based Syst..

[50]  Ido Dagan,et al.  Mining Text Using Keyword Distributions , 1998, Journal of Intelligent Information Systems.

[51]  Yue Xu,et al.  Automatic Pattern-Taxonomy Extraction for Web Mining , 2004, IEEE/WIC/ACM International Conference on Web Intelligence (WI'04).

[52]  Yuefeng Li,et al.  Capturing Evolving Patterns for Ontology-based Web Mining , 2004, IEEE/WIC/ACM International Conference on Web Intelligence (WI'04).

[53]  Masayuki Numao,et al.  Active Mining , 2007, New Generation Computing.