By Spiros Sirmakessis (auth.), Dr. Spiros Sirmakessis (eds.)
The global of textual content mining is concurrently a minefield and a gold mine. textual content Mining is a quickly constructing purposes box and a space of clinical examine, utilizing suggestions from well-established medical fields corresponding to information mining, computer studying, details retrieval, average language processing, case-based reasoning, records and information administration. The booklet includes the papers provided through the 1st overseas Workshop on textual content Mining and its purposes held on the college of Patras, which used to be the release occasion of the actions of NEMIS, a community of excellence within the sector of textual content mining and its functions. The convention maintained a stability among theoretical concerns and outlines of case stories to advertise synergy among conception and perform within the box of textual content Mining. subject matters of curiosity integrated record processing and visualization ideas, internet mining, textual content mining and information administration, in addition to consumer facets and kinfolk to reliable statistics
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9. : Enhanced Hypertext Categorization Using Hyperlinks. In L. M. Haas and A. Tiwary, editors, SIGMOD 1998, Proceedings ACM SIGMOD International Conference on Management of Data, Seattle, Washington, USA (1998), 307318. 10. : Mining the Link Structure of the World Wide Web. IEEE Computer (1999),32(8),60-67. 33 I I. : Data Mining for Path Traversal Patterns in a Web Environment. In Proceedings of the 16th International Conference on Distributed Computing Systems (1996), 385-392. 12. : Web Usage Mining: Discovery and Application of Interesting Patterns from Web data.
Mining the Link Structure of the World Wide Web. IEEE Computer (1999),32(8),60-67. 33 I I. : Data Mining for Path Traversal Patterns in a Web Environment. In Proceedings of the 16th International Conference on Distributed Computing Systems (1996), 385-392. 12. : Web Usage Mining: Discovery and Application of Interesting Patterns from Web data. PhD thesis, Dept. of Computer Science, University of Minnesota (2000). 13. : Web Mining: Information and Pattern Discovery on the World Wide Web. In Proceedings of the 9th IEEE International Conference on Tools with Artificial Intelligence, ICT AI'97 (1997).
Algorithms to learn to extract information - BBN-the system as used for MUC-7. In: Proc. of MUC-7, 1998. [Mitkov02] R. Mitkov. Anaphora resolution. Longman 2002. [MonzOI] Christof Monz, Maarten de Rijke. Introduction to Infonnation Retrieval. In: ESSLI'O 1, Helsinki, Finland, August 200 I. [Ng94] Effective and efficient clustering methods for spatial data mining. In: Proc. of the 20 th conference on VLDB, 144-155, Santiago, Chile, 1994. W. Oard. The State-of-the-Art in Text Filtering. In: User Modeling and User Adaptation Techniques, 7(2):141-178,1997.