Abstract
In this paper, we discuss utilization of data mining techniques in realizing intuitive display for search engines toward fast detection of peculiar WWW pages. A search engine can be regarded as a telescope for WWW because it serves as a means to find relevant information in the huge cyberspace. Most of the current display styles of search engines are, however, just text-based rankings thus are far from intuitive. They are also inadequate for certain activities such as browsing for unexpected Web pages. Detection of peculiar WWW pages is expected to lead to making profits and to stimulating our creativity. Our visualization method DPITT (Detecting Peculiar WWW pages from Image, Topic and Term) is based on several data mining techniques and outperforms that of Google in a problem setting which largely favors Google. In this paper, we mainly present our DPITT and we introduce our latest system GEMVIG.
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References
Ando, S., Suzuki, E.: Distributed Multi-objective GA for Generating Comprehensive Pareto Front in Deceptive Multi-Objective Problems. In: Proc. 2006 IEEE Congress on Evolutionary Computation (IEEE CEC), pp. 5718–5725 (2006)
Card, S.K., Makinlay, J.D., Shneiderman, B. (eds.): Readings in Information Visualization. Morgan Kaufmann, San Francisco (1999)
Durand, N., Cremilleux, B., Suzuki, E.: Visualizing Transactional Data with Multiple Clusterings for Knowledge Discovery. In: Esposito, F., Raś, Z.W., Malerba, D., Semeraro, G. (eds.) ISMIS 2006. LNCS (LNAI), vol. 4203, pp. 47–57. Springer, Heidelberg (2006)
Fayyad, U., Grinstein, G.G., Wierse, A. (eds.): Information Visualization in Data Mining and Knowledge Discovery. Morgan Kaufmann, San Francisco (2002)
Hirose, M., Suzuki, E.: Using WWW-Distribution of Words in Detecting Peculiar Web Pages. In: Suzuki, E., Arikawa, S. (eds.) DS 2004. LNCS (LNAI), vol. 3245, pp. 355–362. Springer, Heidelberg (2004)
Hirose, M., Suzuki, E.: DPITT: Multi-viewpoint Visualization System for Detecting Unexpected WWW Pages Rapidly. In: 2006 IEEE International Conference on Granular Computing (IEEE-GrC 2006), pp. 538–541 (2006)
Hirose, N., Suzuki, E.: Engineering Web Log for Detecting Malicious Sessions to a Web Site by Visual Inspection. WSEAS Transactions on Computers 10(4), 1249–1258 (2005)
Hofmann, T.: Probabilistic Latent Semantic Indexing. In: Proc. 22nd International Conference on Research and Development in Information Retrieval (SIGIR), pp. 50–57 (1999)
Jumi, M.: Research on Multi-viewpoint and Multi-granularity Visualization of a Set of Searched Web Pages Based on Hierarchical Clustering. Master of Engineering Dissertation, Department of Electrical and Computer Engineering, Division of Advanced Physics, Electrical and Computer Engineering, Graduate School of Engineering, Yokohama National University, Japan (in Japanese) (2006)
Kosala, R., Blockeel, H.: Web Mining Research: A Survey. ACM SIGKDD Exploration 2, 1–15 (2000)
Liu, J.: Web Intelligence (WI): What Makes Wisdom Web? In: Proc. Eighteenth International Joint Conference on Artificial Intelligence (IJCAI), pp. 1596–1601 (2003)
Renteria, J.C., Lodha, S.K.: WebVis: a Hierarchical Web Homepage Visualizer. In: Proc. SPIE, vol. 3960, pp. 50–61 (2000)
Salton, G., McGill, M.J. (eds.): Introduction to Modern Information Retrieval. McGraw-Hill, New York (1983)
Suzuki, E.: Undirected Discovery of Interesting Exception Rules. International Journal of Pattern Recognition and Artificial Intelligence 16(8), 1065–1086 (2002)
Suzuki, E., Watanabe, T., Yokoi, H., Takabayashi, K.: Detecting Interesting Exceptions from Medical Test Data with Visual Summarization. In: Proc. Third IEEE International Conference on Data Mining (ICDM), pp. 315–322 (2003)
Toyoda, M., Kitsuregawa, M.: Extracting Evolution of Web Communities from a Series of Web Archives. In: Proc. Fourteenth ACM Conference on Hypertext and Hypermedia (Hypertext), pp. 28–37 (2003)
Yao, Y.Y., Zhong, N., Liu, J., Ohsuga, S.: Web Intelligence (WI): Research Challenges and Trends in the New Information Age. In: Zhong, N., Yao, Y., Ohsuga, S., Liu, J. (eds.) WI 2001. LNCS (LNAI), vol. 2198, pp. 1–17. Springer, Heidelberg (2001)
Zhong, N.: Impending Brain Informatics (BI) Research from Web Intelligence (WI) Perspective. International Journal of Information Technology and Decision Making 5(4), 713–727 (2006)
Zhong, N., Liu, J. (eds.): Intelligent Technologies for Information Analysis. Springer, Heidelberg (2004)
Zhong, N., Liu, J., Yao, Y.Y.: In Search of the Wisdom Web. IEEE Computer 35(11), 27–31 (2002)
Zhong, N., Liu, J., Yao, Y.Y. (eds.): Web Intelligence. Springer, Heidelberg (2003)
Zhong, N., Liu, J., Yao, Y.Y.: Envisioning Intelligent Information Technologies (iIT) from the Stand-Point of Web Intelligence (WI). Communications of the ACM 50(3), 89–94 (2007)
Zhong, N., Liu, J., Yao, Y.Y., Ohsuga, S.: Web Intelligence (WI). In: Proc. the 24th IEEE Computer Society International Computer Software and Applications Conference (COMPSAC), pp. 469–470 (2000)
Zhong, N., Yao, Y., Ohsuga, S., Liu, J. (eds.): WI 2001. LNCS (LNAI), vol. 2198. Springer, Heidelberg (2001)
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Suzuki, E., Ando, S., Hirose, M., Jumi, M. (2007). Intuitive Display for Search Engines Toward Fast Detection of Peculiar WWW Pages. In: Zhong, N., Liu, J., Yao, Y., Wu, J., Lu, S., Li, K. (eds) Web Intelligence Meets Brain Informatics. WImBI 2006. Lecture Notes in Computer Science(), vol 4845. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77028-2_20
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DOI: https://doi.org/10.1007/978-3-540-77028-2_20
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