Text Categorization With Support

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Text Categorization with Support Vector Machines: Learning ...

    https://link.springer.com/content/pdf/10.1007%2FBFb0026683.pdf
    Text Categorization with Support Vector Machines: Learning with Many Relevant Features Thorsten Joachims Universit£t Dortmund lnformatik LS8, Baroper Str. 301 44221 Dortmund, Germany Abstract. This paper explores the use of Support Vector Machines (SVMs) for learning text classifiers from examples. It analyzes the par-Cited by: 10558

Text categorization with Support Vector Machines: Learning ...

    https://link.springer.com/chapter/10.1007%2FBFb0026683
    Jun 16, 2005 · This paper explores the use of Support Vector Machines (SVMs) for learning text classifiers from examples. It analyzes the particular properties of learning with text data and identifies why SVMs are appropriate for this task. Empirical results support the theoretical findings.Cited by: 10558

ecml98 - Cornell University

    https://www.cs.cornell.edu/people/tj/publications/joachims_98a.pdf
    tional text classi cation metho ds SVMs will pro etobe v ery robust, eliminating the need for exp ensiv e parameter tuning. 2 T ext Categorization The goal of text categorization is the classi cation of do cumen ts in to a xed n um b er of prede ned categories. Eac h do cumen t can b e in m ultiple, exactly one, or no category at all. Using mac

Text categorization with Support Vector Machines ...

    https://dl.acm.org/doi/10.1007/BFb0026683
    Text categorization with support vector machines: Learning with many relevant features. Technical Report 23, Universität Dortmund, LS VIII, 1997. Google Scholar; J. Kivinen, M. Warmuth, and P. Auer. The perceptron algorithm vs. winnow: Linear vs. logarithmic mistake bounds when …

Text Categorization With Support Vector Machines: Learning ...

    http://www.ist.temple.edu/~vucetic/cis525spring2004/meghneel.ppt
    Text Categorization With Support Vector Machines: Learning With Many Relevant Features By Thornsten Joachims Presented By Meghneel Gore Goal of Text Categorization Classify documents into a number of pre-defined categories.

Text categorization - SlideShare

    https://www.slideshare.net/kanimozhiu/text-datamining-txtcat
    Aug 03, 2015 · Text categorization 1. Text Categorization (part 1) 2. Categorization 2 Text categorization (TC) - given a set of categories (subjects, topics) and a collection of text documents, the process of finding the correct topic (or topics) for each document.

Solved: Text Categorization Rule - SAS Support Communities

    https://communities.sas.com/t5/SAS-Text-and-Content-Analytics/Text-Categorization-Rule/td-p/127920
    Oct 29, 2013 · Hi, I am doing the document categorization in the SAS text miner 12.1. After the training process done in the text rule builder, I got the following part of rules in the Content Categorization Code window and the Rules Obtained Results windows, F_L2 =Social :: (OR , (AND, (OR, "facebook...

Text Categorization with Support Vector Machines: Learning ...

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.6124
    CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): This paper explores the use of Support Vector Machines (SVMs) for learning text classifiers from examples. It analyzes the particular properties of learning with text data and identifies, why SVMs are appropriate for this task. Empirical results support the theoretical findings.

Text Categorization with Support Vector Machines: Learning ...

    https://www.semanticscholar.org/paper/Text-Categorization-with-Support-Vector-Machines%3A-Joachims/40212e9474c3ddf3d8c6ffd13dd3211ec9406c49
    This paper explores the use of Support Vector Machines (SVMs) for learning text classifiers from examples. It analyzes the particular properties of learning with text data and identifies why SVMs are appropriate for this task. Empirical results support the theoretical findings. SVMs achieve substantial improvements over the currently best performing methods and behave robustly over a variety ...



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