REFERENCES

data mining: opportunities and challenges
Chapter XX - Critical and Future Trends in Data Mining A Review of Key Data Mining Technologies/Applications
Data Mining: Opportunities and Challenges
by John Wang (ed) 
Idea Group Publishing 2003
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Arlitt, M. & Williamson, C. (1997). Internet Web servers: Workload characterization and performance implications. IEEE/ACM Transactions on Networking, 5,5. Stanford, CA: AAAI, pp. 76-89.

Armstrong, S., Freitag, D., Joachims, T., & Mitchell, T. (1995). Webwatcher: A learning apprentice for the World Wide Web. In Proceedings of AAAI Spring Symposium on Information Gathering from Heterogeneous, Distributed Environment.

Baeza-Yates, R. & Ribeiro-Neto, B. (1999). Modern information retrieval. Boston, MA: Addison-Wesley Longman.

Bedard, Y., Merrett, T., & Han, J. (2001). Fundamentals of geospatial data warehousing for geographic knowledge discovery. In H. Miller & J.Han (eds.), Geographic data mining and knowledge discovery. London: Taylor and Francis.

Billsus, D. & Pazzani, M. (1999). A hybrid user model for news story classification. In Proceedings of the Seventh International Conference on User Modeling, Banff, Canadaz: Springer, pp. 127-139.

Borges, J. & M. Leveen, (1999). Mining of user navigation patterns. In Proceedings of WebKDD'99, New York, NY: ACM, pp. 23-29.

Brachman, R.J., Selfridge, P.G., Terveen, L.G., Altman, B., Borgida, A., Halper, F., Kirk, T., Lazar, A., McGuinness, D.L., & Resnick, L.A. (1993). Integrated support for data archaeology. International Journal of Intelligent and Cooperative Information Systems, 2(2), 159-185.

Brin, S. & Page, L. (1998). The anatomy of a large scale hypertextual Web search engine. Seventh International World Wide Web Conference, Brisbane, Australia:. WWW Consortium, pp. 107-115.

Buchner, A. & Mulvenna, M. (1998). Discovering marketing intelligence through online analytical Web usage mining. SIGMOD Record, 27:4.

Catledge, L. & Pitkow, J. (1995). Characterizing browsing behaviors on the World Wide Web. Computer Networks and ISDN Systems, 27:6.

Chakrabarti, S. (2000). Data mining for hypertext. SIGKDD Explorations, 1(2).

Chakrabarti, S., Dom, B. E., Gibson, D., Kleinberg, J. M., Kumar, S. R., Raghavan, P., Rajagopolan, S., & Tomkins, A. (1999). Mining the link structure of the World Wide Web. IEEE Computer, 32,8: 60-67, August.

Chakrabarti, S., van den Berg, M. H., & Dom, B. E. (1999). Distributed hypertext resource discovery through examples. In Proceedings of the 25th VLDB (International Conference on Very Large Data Bases), Edinburgh, Scotland, pp. 375-386.

Chalifa-Caspi, V., Prilusky, J. & Lancet, D. (1998). The Unified Database. Weizmann Institute of Science, Bioinformatics Unit and Genome Center (Rehovot, Israel). Retrieved on January 12, 2002 from http://bioinfo.weizmann.ac.il/.

Chawathe, H., Garcia-Molina, J., Hammer, K., Irland, Y., Papakonstantinou, J.D., Ulman, J., & Widom, J. (1994). The tsimmis project: Integration of heterogeneous information sources. In Proceedings of the IPSJ Conference, Tokyo: Information Processing Society of Japan, pp. 114-133.

Chen, M., Park, J.S., & Yu, P.S. (1996). Data mining for path traversal patterns in a web environment. In Proceedings of the 16th International Conference on Distributed Computing Systems, ICDCS, pp. 385-392.

Cheung, D., Hwang, C., Fu, A., & Han, J. (2000). Efficient rule-based attributed-oriented induction for data mining. Journal of Intelligent Information Systems, 15(2), 175-200.

Craven, M., DiPasquo, D., Freitag, D., McCallum, A., Mitchell, T., Nigam, K., & Slattery, S. (1998). Learning to extract symbolic knowledge from the World Wide Web. In Proceedings of AAAI Conference, AAAI.

Crimmins, S. & Smeator, A. (1999). Information Discovery on the Internet, IEEE Intelligent Systems, 14, 4.

Delmater, R. & Hancock, M. (2001). Data mining explained: A manager's guide to customer-centric intelligence. Burlington, MA: Digital Press.

Doorenbos, R.B., Etzioni, O., & Weld, D.S. (1996). A scalable comparison shopping agent for the World Wide Web. Technical Report 96-01-03, University of Washington, Dept. of Computer Science and Engineering, Seattle, WA.

Dorre, J., Gerstl, P., & Seiffert, R. (1999). Text mining: Finding nuggets in mountains of textual data. In KDD-99 Proceedings, San Diego, CA: ACM, pp. 398-401.

Dyche, J. (2001). The CRM handbook. Reading, MA: Addison-Wesley.

Etzioni, O. (1996). The World Wide Web: Quagmire or gold mine. Communications of the ACM, 39, 11.

Frank, E., Paynter, G.W., Witten, I.H., Gutwin, C., & Nevill-Manning, C.G. (1998). Domain-specific key phrase extraction. In Proceedings of 16th Joint Conference on AI. pp. 668-673, Stockholm, Sweden.

Garofalis, M.N., Rastogi, R., Seshadri, S. & Shim, K. (1999). Data mining and the Web. Workshop on Web Information and Data Management, Workshop in Data Mining WIDM'99, 43-47.

Greenberg, P. (2001). CRM at the speed of light. New York: McGraw-Hill.

Han, J., Dong, G., & Yin, Y. (1999). Efficient mining of partial periodic patterns in time-series database. In Proceedings International Conference on Data Engineering ICDE'99, Sydney, Australia: IEEE, pp. 45-52.

Han, J., Jamil, Y., Lu, L., Chen, L., Liao, Y., & Pei, J. (2001). DNA-Miner: A system prototype for mining DNA sequences. In Proceedings of the 2001 ACM-SIGMOD, Santa Barbara, CA: ACM, pp. 211-217.

Han, J. & Kamber, M. (2001). Data mining: Concepts and techniques. San Mateo, CA: Morgan Kaufmann.

Han, J., Kamber, M., & Tung, A.K.H. (2001). Spatial clustering methods in data mining: A survey. In H. Miller & J. Han (eds.), Geographic data mining and knowledge discovery. London: Taylor and Francis.

Han, J., Koperski, K., & Stefanovic, N. (1997). GeoMiner: A system prototype for spatial data mining. In Proceedings of SIGMOD'97, Tucson, AZ: ACM, pp. 189-207.

Han, J., Lakshmanan, L.V.S., & Ng, R.T. (1999). Constraint-based, multidimensional data mining. COMPUTER (Special Issue on Data Mining), 32(8), 46-50.

Han, J., Pei, J., & Yin, Y. (2000). Mining frequent patterns without candidate generation. In Proceedings of 2000 ACM-SIGMOD Int. Conf. on Management of Data (SIGMOD'00), Dallas, TX: ACM, pp. 109-114.

Han, J., Pei, J., Mortazavi-Asl, B., Chen, Q., Dayal, U. & Hsu, M.-C. (2000). FreeSpan: Frequent pattern-projected sequential pattern mining. In Proceedings of the KDD'00, Boston, MA: ACM, pp. 88-97.

Han, J., Stefanovic, N., & Koperski, K. (1998). Selective materialization: An efficient method for spatial data cube construction. In Proceedings Pacific-Asia Conference in Knowledge Discovery and Data Mining, PAKDD'98, Melbourne, Australia. ACM, pp. 295-303.

Han, J., Zaiane, O.R., Chee, S.H.S., & Chiang, J.Y. (2000). Towards online analytical mining of the Internet for e-commerce. In W. Kou & Y. Yesha (eds.), Electronic commerce technology trends: Challenges and opportunities, IBM Press, 169-198.

Hearst, M.A. (1999). Untangling text data mining. In Proceedings of ACL'99: The 37th Annual Meeting of the Association for Computational Linguistics, University of Maryland, June 20-26, Association for Computational Linguistics, pp. 123-129.

Kargupta, H. & Joshi, A. (2001). Data mining to go: Ubiquitous KDD for mobile and distributed environments. Presentation at KDD-2001, San Francisco.

Kargupta, H., Park, B., Herschberger, D., & Johnson, E. (2000). Collective data mining. In H. Kargupta & P. Chan (eds.), Advances in distributed data mining. Boston, MA: MIT Press.

Kholsa, A., Kuhn, B., & Soparkar, N. (1996). Database search using information mining. In Proceedings of the 1996 ACM-SIGMOD International Conference on Management of Data, Montreal, Canada:. ACM, pp. 201-209.

Kim, E. D., Lam, J. M. W., & Han, J. (2000). AIM: Approximate intelligent matching for time-series data. In Proceedings of the 2000 International Conference on Data Warehouse and Knowledge Discovery (DaWaK'00), Greenwich, U.K.: IEEE, pp. 36-49.

King, & Novak, M. (1996). Supporting information infrastructure for distributed, heterogeneous knowledge discovery. In Proceedings of the SIGMOD 96 Workshop on Research Issues on Data Mining and Knowledge Discovery, Montreal, Canada: ACM, pp. 123-130.

Kleinberg, J. (1998). Authoritative sources in a hyperlinked environment. In Proceedings of the 9th ACM-SIAM Symposium on Discrete Algorithms, pp. 114-119.

Koperski, K., Adhikary, J., & Han, J. (1996). Spatial data mining: Progress and challenges. ACM SIGMOD'96 Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD'96), Montreal, Canada: ACM, pp. 80-87.

Koperski, K. & Han, J. (1995). Discovery of spatial association rules in geographic information databases. In Proceedings of ACM SIG Conference on Management of Data 1995, Portland, Maine: ACM, pp. 31-39.

Koperski, K., Han, J., & Marchisio, G.B. (1999). Mining spatial and image data through progressive refinement methods. Revue internationale de gomatique (European Journal of GIS and Spatial Analysis), 9(4), 425-440.

Koperski, K., Han, J., & Stefanovic, N. (1998). An efficient two-step method for classification of spatial data. International Symposium on Spatial Data Handling SDH'98, Vancouver, Canada: ISSDH, pp. 32-37.

Kosala, R. & Blockeel, H. (2000). Web mining research: A survey. SIGKDD Explorations, 2 (1).

Lakshmanan, L.V.S., Ng, R., Han, J. & Pang, A. (1999).Optimization of constrained frequent set queries with 2-variable constraints. Proceedings of the ACM Special Internet Group on Management of Data 1999, Philadelphia, PA: ACM, pp. 287-293.

Larson, R. (1996). Bibliometrics of the World Wide Web: An exploratory analysis of the intellectual structure of cyberspace. In ASIS '96: Proceedings of the 1996 Annual ASIS Meeting, Baltimore, MD: American Society for Information Science and Technology, pp. 65-71.

Lu, H., Feng, L. & Han, J. (2000). Beyond intra-transaction association analysis: Mining multi-dimensional inter-transaction association rules. ACM Transactions on Information Systems, 18, 4, October.

Lyons, D. & Tseytin, G. (1998). Phenomenal data mining and link analysis. In B. Jensen & F. Goldberg (eds.), Proceedings of the Artificial Intelligence and Link Analysis Fall Symposium, Phoenix, AZ: American Association for Artificial Intelligence, pp. 123-127.

Maarek, Y. S., & Ben Shaul, I. (1996). Automatically organizing bookmarks per content. In Proceedings of the 5th International World Wide Web Conference/Computer Networks 28(7-11): 1321-1334, Boston, MA.

Madria, S., Bhowmick, S., Ng, W. K., & Lim, E. P. (1999). Research issues in Web data mining. In Proceedings of Data Warehousing and Knowledge Discovery, First International Conference, DaWaK '99, Florence, Italy, pp. 303-312.

McCarthy, J. (2000). Phenomenal data mining, SIGKDD Explorations, 1 (2).

Mendelzon, A., Mihaila, G., & Milo, T. (1996). Querying the World Wide Web, In Proceedings of Conference on Parallel and Distributed Information Systems PDIS'96, Miami, FL, pp. 45-57.

Merialdo P., Atzeni, M., & Mecca, G. (1997). Semistructured and structured data in the Web: Going back and forth. In Proceedings of the Workshop on the Management of Semistructured Data (in conjunction with ACM SIGMOD), ACM, pp. 196-201.

Miller, H. & Han, J. (eds.). (2001). Geographic data mining and knowledge discovery. London: Taylor and Francis.

Mizruchi, M. S., Mariolis, P., Schwartz, M., & Mintz, B. (1986). Techniques for disaggregating centrality scores in social networks. In N. B. Tuma (ed.), Sociological Methodology, pp. 26-48, San Francisco, CA: Jossey-Bass.

Nahm, U. Y. & Mooney, R. J. (2000). A mutually beneficial integration of data mining and information extraction. In Proceedings of the Seventeenth National Conference on AI (AAAI-00), Austin, TX: AAAI, pp. 627-632.

Pazzani, M., Muramatsu, J., & Billsus. D. (1996). Syskill & Webert: Identifying interesting websites. In Proceedings of AAAI Spring Symposium on Machine Learning in Information Access, Portland, OR: AAAI, pp. 54-61.

Pei, J. & Han, J. (2000). Can we push more constraints into frequent pattern mining? In Proceedings of the ACM Conference on Knowledge Discovery for Databases, KDD'00, Boston, MA, pp. 196-207.

Pei, J., Han, J., & Lakshmanan, L.V.S. (2001). Mining frequent item sets with convertible constraints. In Proceedings of the 2001 International Conference on Data Engineering (ICDE'01), Heidelberg, Germany: IEEE, pp. 82-90.

Pei, J., Han, J., & Mao, R. (2000). CLOSET: An efficient algorithm of mining frequent closed itemsets for association rules. In Proceedings of the ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, DMKD'00, Dallas, TX: ACM, pp. 21-30.

Pei, J., Han, J., Pinto, H., Chen, Q., Dayal, U., & Hsu, M.-C. (2001). PrefixSpan: Mining sequential patterns efficiently by prefix-projected pattern growth. In Proceedings of the 2001 International Conference on Data Engineering (ICDE'01), Heidelberg, Germany: IEEE, pp. 245-259.

Pei, J., Tung, A., & Han, J. (2001). Fault-tolerant frequent pattern mining: Problems and challenges. In Proceedings of the 2001 ACM-SIGMOD, Santa Barbara, CA: ACM, pp. 33-40.

Rebhan, M., Chalifa-Caspi, V., Prilusky, J., Lancet, D. (1997). GeneCards: Encyclopedia for genes, proteins & diseases. Weizmann Institute of Science, Bioinformatics Unit & Genome Center (Rehovot, Israel). Retrieved on January 13, 2002 from http://bioinfo.weizmann.ac.il/.

Rennison, E. (1994). Galaxy of news: An approach to visualizing and understanding expansive news landscapes. In Proceedings of UIST 94, ACM Symposium on User Interface Software and Technology, pp. 3-12, New York: ACM.

Shavlik, J. & Eliassi-Rad, T. (1998). Intelligent agents for Web-based tasks. In Working Notes of the AAAI/ICML-98 Workshop on Learning for Text Categorization, Madison, WI: AAAI, pp. 111-119.

Srivastava, J., Cooley, R., Deshpe, M., & Tan, P. (2000). Web usage mining. SIGKDD Explorations, 1 (2).

Swift, R.S. (2000). Accelerating customer relationships: Using CRM and relationship technologies. Upper Saddle River, NJ: Prentice-Hall.

Tung, K.H., Han, J., Lakshmanan, L.V.S., & Ng, R.T. (2001). Constraint-based clustering in large databases. In Proceedings of the 2001 International Conference on Database Theory (ICDT'01), London, U.K.: ACM, pp. 23-31.

Tung, K. H., Hou, J., & Han, J. (2001). Spatial clustering in the presence of obstacles. In Proceedings of the 2001 International Conference on Data Engineering (ICDE'01), Heidelberg, Germany: IEEE, pp. 96-102.

Voorhees, E. M. (1994). Query expansion using lexical-semantic relations. In Proceedings of the 17th Annual International ACM/SIGIR Conference, pp. 61-69, Dublin, Ireland.

Wang, Zhou, S., & Han, J. (2000). Pushing support constraints into association mining. International Conference on Very Large Data Bases (VLDB'00), Cairo, Egypt.

Wang, W., Zhou, S., & Han, J. (2000). Pushing support constraints into association mining. International Conference on Very Large Data Bases (VLDB'00), Cairo, Egypt: Morgan Kaufmann, pp. 87-96.

Wang, K., He, Y., & Han, J. (2000). Mining frequent itemsets using support constraints. In Proceedings of the 2000 International Conference on Very Large Data Bases (VLDB'00), pp. 43-52, Cairo, Egypt, 43-52.

Weiss, F., Velez, B., Sheldon, M.A., Namprempre, C., Szilagyi, P., Duda, A., & Gifford, D.K. (1996). Hypursuit: A hierarchical network search engine that exploits content-link hypertext clustering In Hypertext'96: The Seventh ACM Conference on Hypertext, ACM, pp. 211-218.

Wise, J. A., Thomas, J. J., Pennock, K., Lantrip, D., Pottier, M. & Schur, A. (1995). Visualizing the non-visual: Spatial analysis and interaction with information from text documents. In Proceedings of the Information Visualization Symposium 95, pp. 51-58, IEEE Computer Society Press.

Xu, J. & Croft, W.B. (1996). Query expansion using local & global document analysis. In SIGIR '96: Proceedings of the 19th Annual International ACM SIGIR Conference on Research & Development in Information Retrieval, 4-11.

Zaiane, O., Han, J., Li, W., & Hou, J. (1998). Mining multimedia data. In Proceedings of Meeting Of Minds, CASCON '98, Toronto, Canada: IBM.

Zaiane, O., Han, J., & Zhu, H. (2000). Mining recurrent items in multimedia with progressive resolution refinement. In Proceedings of the International Conference on Data Engineering ICDE'00, San Diego, CA: IEEE, pp. 15-28.

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Data Mining(c) Opportunities and Challenges
Data Mining: Opportunities and Challenges
ISBN: 1591400511
EAN: 2147483647
Year: 2003
Pages: 194
Authors: John Wang

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