A knowledge-based model using ontologies for personalized web information gathering

Web Intelligence and Agent Systems

Volumn 8, Issue 3, 2010, Pages 235-254

  Tao, Xiaohui ^a   Li, Yuefeng ^a   Zhong, Ning ^b  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

^b MAEBASHI INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

Knowledge based information gathering; local instance repository; ontology; user background knowledge; user information needs; world knowledge base

Indexed keywords

BACKGROUND KNOWLEDGE; INFORMATION GATHERING; KNOWLEDGE-BASED INFORMATION GATHERING; USER INFORMATION NEED; WORLD KNOWLEDGE;

INFORMATION SCIENCE; ONTOLOGY;

KNOWLEDGE BASED SYSTEMS;

EID: 77954916968     PISSN: 15701263     EISSN: None     Source Type: Journal    
DOI: 10.3233/WIA-2010-0189     Document Type: Article

References (85)

1. Muhammad Abulaish and Lipika Dey. Information extraction and imprecise query answering from web documents. Web Intelligence and Agent Systems, 4(4):407-429, January 2006.
2. G. Antoniou and F. Van Harmelen. A Semantic Web Primer. The MIT Press, 2004.
3. T. Berners-Lee, J. Hendler, and O. Lassila. The semantic Web. Scientific American, 5:29-37, 2001.
4. G. E. P. Box, J. S. Hunter, and W. G. Hunter. Statistics For Experimenters. John Wiley & Sons, 2005.
5. C. Buckley and E.M. Voorhees. Evaluating evaluationmeasure stability. In Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval, pages 33-40, 2000.
6. A. Budanitsky and G. Hirst. Evaluating WordNet-based measures of lexical semantic relatedness. Computational Linguistics, 32(1):13-47, 2006.
7. J. Chaffee and S. Gauch. Personal ontologies for Web navigation. In Proceedings of the ninth international conference on Information and knowledge management, pages 227-234, 2000.
8. P. A. Chirita, W. Nejdl, R. Paiu, and C. Kohlschütter. Using ODP metadata to personalize search. In Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, pages 178- 185. ACM Press, 2005.
9. W. C. Cho and D. Richards. Ontology construction and concept reuse with formal concept analysis for improved web document retrieval. Web Intelligence and Agent Systems, 5(1):109-126, January 2007.
10. K.-S. Choi, C.-H. Lee, and P.-K. Rhee. Document ontology based personalized filtering system (poster session). In MULTIMEDIA '00: Proceedings of the eighth ACM international conference on Multimedia, pages 362-364, New York, NY, USA, 2000. ACM Press.
11. R. M. Colomb. Information Spaces: The Architecture of Cyberspace. Springer, 2002.
12. K. Curran, C. Murphy, and S. Annesley. Web intelligence in information retrieval. In Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence, pages 409-412, 2003.
13. A. Doan, J. Madhavan, R. Dhamankar, P. Domingos, and A. Halevy. Learning to match ontologies on the semantic web. The International Journal on Very Large Data Bases, 12(4):303-319, 2003.
14. D. Dou, G. Frishkoff, J. Rong, R. Frank, A. Malony, and D. Tucker. Development of neuroelectromagnetic ontologies( NEMO): a framework for mining brainwave ontologies. In Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 270- 279, 2007.
15. C. Fellbaum, editor. WordNet: An Electronic Lexical Database. ISBN: 0-262-06197-X. MIT Press, Cambridge, MA, 1998.
16. E. Frank and G.W. Paynter. Predicting library of congress classifications from library of congress subject headings. Journal of the American Society for Information Science and Technology, 55(3):214-227, 2004.
17. A. Gangemi, N. Guarino, and A. Oltramari. Conceptual analysis of lexical taxonomies: the case of wordnet top-level. In FOIS '01: Proceedings of the international conference on Formal Ontology in Information Systems, pages 285-296, New York, NY, USA, 2001. ACM Press.
18. S. Gauch, J. Chaffee, and A. Pretschner. Ontology-based personalized search and browsing. Web Intelligence and Agent Systems, 1(3-4):219-234, 2003.
19. S. Gauch, J. M. Madrid, and S. Induri. Keyconcept: A conceptual search engine. Technical report, EECS Department, University of Kansas, 2004.
20. E. J. Glover, K. Tsioutsiouliklis, S. Lawrence, D. M. Pennock, and G. W. Flake. Using Web structure for classifying and describing Web pages. In WWW '02: Proceedings of the 11th international conference on World Wide Web, pages 562-569, New York, NY, USA, 2002. ACM Press.
21. D. Godoy and A. Amandi. Modeling user interests by conceptual clustering. Information Systems, 31(4):247-265, 2006.
22. C. Hung, S. Wermter, and P. Smith. Hybrid neural document clustering using guided self-organization and wordnet. Intelligent Systems, IEEE (see also IEEE Intelligent Systems and Their Applications), 19(2):68-77, 2004.
23. B. J. Jansen, A. Spink, J. Bateman, and T. Saracevic. Real life information retrieval: a study of user queries on the web. SIGIR Forum, 32(1):5-17, 1998.
24. J. J. Jiang and D.W. Conrath. Semantic similarity based on corpus statistics and lexical taxonomy. In Proceedings of the 10th International Conference Research on Computational Linguistics (ROCLING X), 1997, Taiwan, pages 19-33, Taiwan, 1997.
25. X. Jiang and A-H. Tan. Mining ontological knowledge from domain-specific text documents. In Proceedings of the Fifth IEEE International Conference on Data Mining, pages 665- 668, 2005.
26. W. Jin, R. K. Srihari, H. H. Ho, and X. Wu. Improving knowledge discovery in document collections through combining text retrieval and link analysis techniques. In Proceedings of the 2007 Seventh IEEE International Conference on Data Mining, pages 193-202, 2007.
27. T. Joachims. Transductive inference for text classification using support vector machines. In Ivan Bratko and Saso Dzeroski, editors, Proceedings of ICML-99, 16th International Conference on Machine Learning, pages 200-209, Bled, SL, 1999. Morgan Kaufmann Publishers, San Francisco, US.
28. I. Kaur and A. J. Hornof. A comparison of LSA, WordNet and PMI-IR for predicting user click behavior. In Proceedings of the SIGCHI conference on Human factors in computing systems, pages 51-60, New York, USA, 2005. ACM Press.
29. L. Khan and F. Luo. Ontology construction for information selection. In Proceedings of 14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002), pages 122-127, 2002.
30. L. Khan, D. McLeod, and E. Hovy. Retrieval effectiveness of an ontology-based model for information selection. The International Journal on Very Large Data Bases, 13(1):71-85, 2004.
31. J. D. King, Y. Li, X. Tao, and R. Nayak. Mining World Knowledge for Analysis of Search Engine Content. Web Intelligence and Agent Systems, 5(3):233-253, 2007.
32. K. Knight and S. K. Luk. Building a large-scale knowledge base for machine translation. In AAAI '94: Proceedings of the twelfth national conference on Artificial intelligence (vol. 1), pages 773-778, Menlo Park, CA, USA, 1994. American Association for Artificial Intelligence.
33. H. Kornilakis, M. Grigoriadou, K. A. Papanikolaou, and E. Gouli. Using WordNet to support interactive concept map construction. In Proceedings. IEEE International Conference on Advanced Learning Technologies, 2004, pages 600-604, 2004.
34. R. Kosala and H. Blockeel. Web mining research: A survey. ACM SIGKDD Explorations Newsletter, 2(1):1-15, 2000.
35. K. S. Lee, W. B. Croft, and J. Allan. A cluster-based resampling method for pseudo-relevance feedback. In Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, pages 235- 242, 2008.
36. D. D. Lewis, Y. Yang, T. G. Rose, and F. Li. RCV1: A New Benchmark Collection for Text Categorization Research. Journal of Machine Learning Research, 5:361-397, 2004.
37. X. Li and B. Liu. Learning to classify texts using positive and unlabeled data. In Proceedings of 8th International Joint Conference on Artificial Intelligence, pages 587-594, 2003.
38. Y. Li, S.-T.Wu, and X. Tao. Effective pattern taxonomy mining in text documents. In CIKM '08: Proceeding of the 17th ACM conference on Information and knowledge management, pages 1509-1510, New York, NY, USA, 2008. ACM.
39. Y. Li,W. Yang, and Y. Xu. Multi-tier granule mining for representations of multidimensional association rules. In Proceedings of the Sixth IEEE International Conference on Data Mining, pages 953-958, 2006.
40. Y. Li and N. Zhong. Capturing evolving patterns for ontology-based web mining. In Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence, pages 256-263, Washington, DC, USA, 2004. IEEE Computer Society.
41. Y. Li and N. Zhong. Web Mining Model and its Applications for Information Gathering. Knowledge-Based Systems, 17:207-217, 2004.
42. Y. Li and N. Zhong. Mining Ontology for Automatically Acquiring Web User Information Needs. IEEE Transactions on Knowledge and Data Engineering, 18(4):554-568, 2006.
43. Library of Congress. MARC 21 concise format for bibliographic data, 1999 Edition, Update No.1 (October 2001) through Update No. 8 (October 2007). Washington, D.C. : Library of Congress, 2007.
44. S.-Y. Lim, M.-H. Song, K.-J. Son, and S.-J. Lee. Domain ontology construction based on semantic relation information of terminology. In 30th Annual Conference of the IEEE Industrial Electronics Society, volume 3, pages 2213-2217 Vol. 3, 2004.
45. B. Liu. Web content mining. In Tutorial given at WWW-2005 and WISE-2005, 2005.
46. B. Liu, Y. Dai, X. Li, W. S. Lee, and P. S. Yu. Building text classifiers using positive and unlabeled examples. In Proceedings of the Third IEEE International Conference on Data Mining, ICDM2003, pages 179-186, 2003.
47. S. Liu, F. Liu, C. Yu, and W. Meng. An effective approach to document retrieval via utilizing WordNet and recognizing phrases. In SIGIR '04: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, pages 266-272, New York, NY, USA, 2004. ACM Press.
48. Z. Ma, G. Pant, and O. R. L. Sheng. Interest-based personalized search. ACM Transactions on Information Systems (TOIS), 25(1):5, 2007.
49. A. Maedche and S. Staab. Ontology learning for the Semantic Web. Intelligent Systems, IEEE, 16(2):72-79, 2001.
50. M. E. Maron. Probabilistic approaches to the document retrieval problem. In Proceedings of the 5th annual ACM conference on Research and development in information retrieval, pages 98-107. Springer-Verlag New York, Inc., West Berlin, Germany, 1982.
51. R. Navigli, P. Velardi, and A. Gangemi. Ontology learning and its application to automated terminology translation. Intelligent Systems, IEEE, 18:22-31, 2003.
52. G. Qiu, K. Liu, J. Bu, C. Chen, and Z. Kang. Quantify query ambiguity using odp metadata. In SIGIR '07: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, pages 697- 698, New York, NY, USA, 2007. ACM Press.
53. P. Resnik. Semantic similarity in a taxonomy: an informationbased measure and its application to problems of ambiguity and natural language. Journal of Artificial Intelligence Research, 11:95-130, 1999.
54. I. Rish. An empirical study of the naïve Bayes classifier. In IJCAI 2001 Workshop on Empirical Methods in Artificial Intelligence, 2001.
55. S. E. Robertson and I. Soboroff. The TREC 2002 filtering track report. In Text REtrieval Conference, 2002.
56. J. Rocchio. The smart retrieval system experiments in automatic document processing, chapter Relevance feedback in information retrieval. Englewood Cliffs, NJ, 1971.
57. M. Ruiz-Casado, E. Alfonseca, and P. Castells. Automatising the learning of lexical patterns: An application to the enrichment of WordNet by extracting semantic relationships from Wikipedia. Data & Knowledge Engineering, 61(3):484-499, June 2007.
58. S. Schocken and R. A. Hummel. On the use of the Dempster Shafer model in information indexing and retrieval applications. Internatinal Journal Man-Machine Studies, 39:843-879, 1993.
59. M. D. Smucker, J. Allan, and B. Carterette. A Comparison of Statistical Significance Tests for Information Retrieval Evaluation. In Proceedings of the sixteenth ACM conference on Conference on information and knowledge management, pages 623-632, 2007.
60. J. Song, W. Zhang, W. Xiao, G. Li, and Z. Xu. Ontology- Based Information Retrieval Model for the Semantic Web. In Proceedings of the 2005 IEEE International Conference on e- Technology, e-Commerce and e-Service, EEE '05, pages 152- 155, 2005.
61. A. Spink, D. Wolfram, M. B. J. Jansen, and T. Saracevic. Searching the Web: The public and their queries. Journal of the American Society for Information Science and Technology, 52(3):226-234, 2001.
62. J. Srivastava, P. Desikan, and V. Kumar. Web mining: Accomplishments and future directions. In Proc. US National Science Foundation Workshop on Next-Generation Data Mining (NGDM), Nationall Science Foundation, 2002, 2002.
63. X. Tao, Y. Li, N. Zhong, and R. Nayak. Ontology mining for personalzied web information gathering. In Proceedings of the 2007 IEEE/WIC/ACM International Conference of Web Intelligence, pages 351-358, 2007.
64. X. Tao, Y. Li, N. Zhong, and R. Nayak. A knowledge retrieval model using ontology mining and user profiling. Integrated Computer-Aided Engineering, 15(4):313-329, 2008.
65. X. Tao, Y. Li, N. Zhong, and R. Nayak. An ontology-based framework for knowledge retrieval. In Proceedings of the 2008 IEEE/WIC/ACM International Conference of Web Intelligence, pages 510-517, 2008.
66. T. Tran, P. Cimiano, S. Rudolph, and R. Studer. Ontologybased interpretation of keywords for semantic search. In Proceedins of the 6th International Conference on Semantic Web, pages 523-536, 2007.
67. TREC. Common evaluation measures. In The Eleventh Text REtrieval Conference (TREC 2002), 2002.
68. F. Van Harmelen. The semantic web: what, why, how, and when. Distributed Systems Online, IEEE, 5(3):-, 2004.
69. C. J. Van Rijsbergen. Information Retrieval. Butterworths, 1979.
70. G. Varelas, E. Voutsakis, P. Raftopoulou, E. G.M. Petrakis, and E. E. Milios. Semantic similarity methods in WordNet and their application to information retrieval on theWeb. In WIDM '05: Proceedings of the 7th annual ACM international workshop on Web information and data management, pages 10-16, New York, NY, USA, 2005. ACM Press.
71. P. Velardi, P. Fabriani, and M. Missikoff. Using text processing techniques to automatically enrich a domain ontology. In FOIS '01: Proceedings of the international conference on Formal Ontology in Information Systems, pages 270-284, New York, NY, USA, 2001. ACM Press.
72. E. M. Voorhees. Using WordNet to disambiguate word senses for text retrieval. In Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval, pages 171-180. ACM Press, Pittsburgh, Pennsylvania, United States, 1993.
73. E. M. Voorhees. Overview of TREC 2002. In The Text REtrieval Conference (TREC), 2002. Retrieved From: http://trec.nist.gov/pubs/trec11/papers/OVERVIEW. 11.pdf and http://trec.nist.gov/pubs/trec11/appendices/MEASURES.pdf.
74. S. Vrettos and A. Stafylopatis. A Fuzzy Rule-Based Agent for Web Retrieval-Filtering. In WI '01: Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development, pages 448-453, London, UK, 2001. Springer- Verlag.
75. J. Wang and M. C. Lee. Reconstructing DDC for interactive classification. In Proceedings of the sixteenth ACM conference on Conference on information and knowledge management, pages 137-146, New York, NY, USA, 2007. ACM.
76. C.-P. Wei, R. H. L. Chiang, and C.-C. Wu. Accommodating individual preferences in the categorization of documents: A personalized clustering approach. Journal of Management Information Systems, 23(2):173-201, 2006.
77. S.-T. Wu. Knowledge Discovery Using Pattern Taxonomy Model in Text Mining. PhD thesis, Faculty of Information Technology, Queensland University of Technology, 2007.
78. Y. Xu and Y. Li. Generating concise association rules. In CIKM '07: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management, pages 781- 790, New York, NY, USA, 2007. ACM.
79. W. Yang, Y. Li, J. Wu, and Y. Xu. Granule mining oriented data warehousing model for representations of multidimensional association rules. International Journal of Intelligent Information and Database Systems, 2(1):125-145, 2008.
80. Y. Yang and X. Liu. A re-examination of text categorization methods. In Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval, pages 42-49. ACM Press, 1999.
81. Y. Y. Yao, Y. Zeng, N. Zhong, and X. Huang. Knowedge retrieval (KR). In Proceedings of the 2007 IEEE/WIC/ACM International Conference of Web Intelligence, pages 729-735, 2007.
82. Z. Yu, Z. Zheng, S. Gao, and J. Guo. Personalized information recommendation in digital library domain based on ontology. In IEEE International Symposium on Communications and Information Technology, 2005. ISCIT 2005, volume 2, pages 1249-1252, 2005.
83. N. Zhong. Toward Web Intelligence. In Proceedings of 1st International Atlantic Web Intelligence Conference, pages 1- 14, 2003.
84. N. Zhong and N. Hayazaki. Roles of ontologies for web intelligence. In Proceedings of Foundations of Intelligent Systems: 13th International Symposium, ISMIS 2002, volume 2366, page 55, Lyon, France, June 27-29 2002.
85. C. Zhou, D. Frankowski, P. Ludford, S. Shekhar, and L. Terveen. Discovering personally meaningful places: An interactive clustering approach. ACM Transactions on Information Systems (TOIS), 25(3):12, 2007.