Text Mining and its Applications: Results of the NEMIS by Spiros Sirmakessis (auth.), Dr. Spiros Sirmakessis (eds.)

By Spiros Sirmakessis (auth.), Dr. Spiros Sirmakessis (eds.)

The international of textual content mining is concurrently a minefield and a gold mine. textual content Mining is a swiftly constructing purposes box and a space of medical learn, utilizing innovations from well-established clinical fields reminiscent of facts mining, desktop studying, info retrieval, normal language processing, case-based reasoning, data and data administration. The e-book includes the papers offered through the 1st overseas Workshop on textual content Mining and its functions held on the college of Patras, which was once the release occasion of the actions of NEMIS, a community of excellence within the region of textual content mining and its functions. The convention maintained a stability among theoretical matters and outlines of case stories to advertise synergy among idea and perform within the box of textual content Mining. themes of curiosity incorporated record processing and visualization innovations, net mining, textual content mining and information administration, in addition to person facets and relatives to legitimate statistics

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Advances in Automated Text Summarization. 1999. [Smyth96] P. Smyth. Clustering Using Monte Carlo Cross-Validation. Proc. of the KDD Conference 1996. [Strzalkowski99] T. Strzalkowski et al. Evaluating Natural Language Processing Techniques in Infonnation Retrieval. ). Natural Language Information Retrieval, Kluwer Ac. Publishers, 1999. [SullivanOl] D. Sullivan. Document Warehousing and Text Mining. ISBN: 0-471-39959-0. W. Wiley, 2001. [Uszkoreit02] H. Uszkoreit. New chances for deep linguistic processing.

In Journal of Intelligent Information Systems. 17(2-3):107-145,2001. [HanOI] J. Han and M. Kamber. Data Mining. Morgan Kaufmann Publishers. 2001. J. Hand, H. Mannila, P. Smyth. Principles of Data Mining: Adaptive Computation and Machine Learning. ISBN: 026208290X. MIT Press, 2001 [Hartigan75] J. Hartigan. Clustering Algorithms. John Willey & Sons. New York, 1975. [HastieOl] T. Hastie, R. H. Friedman. The Elements of Statistical Learning: Data Mining, Inference and Prediction. ISBN: 0387952845, Springer Verlag, 2001.

Advances in Automated Text Summarization. 1999. [Smyth96] P. Smyth. Clustering Using Monte Carlo Cross-Validation. Proc. of the KDD Conference 1996. [Strzalkowski99] T. Strzalkowski et al. Evaluating Natural Language Processing Techniques in Infonnation Retrieval. ). Natural Language Information Retrieval, Kluwer Ac. Publishers, 1999. [SullivanOl] D. Sullivan. Document Warehousing and Text Mining. ISBN: 0-471-39959-0. W. Wiley, 2001. [Uszkoreit02] H. Uszkoreit. New chances for deep linguistic processing.

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