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Text categorization with Support Vector Machines: Learning with many relevant features

Thorsten Joachims · Lecture notes in computer science · 1998

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Author / responsible party
Thorsten Joachims
Publisher
Lecture notes in computer science
Year
1998
Language
English

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APA 7

Joachims, T. (1998). Text categorization with Support Vector Machines: Learning with many relevant features. Lecture notes in computer science. https://doi.org/10.1007/bfb0026683

MLA

Joachims, Thorsten. Text categorization with Support Vector Machines: Learning with many relevant features. Lecture notes in computer science, 1998. https://doi.org/10.1007/bfb0026683.

Chicago

Joachims, Thorsten. 1998. Text categorization with Support Vector Machines: Learning with many relevant features. Lecture notes in computer science. https://doi.org/10.1007/bfb0026683.

Harvard

Joachims, T. 1998, Text categorization with Support Vector Machines: Learning with many relevant features, Lecture notes in computer science, available at: https://doi.org/10.1007/bfb0026683 [Accessed 5 Aug. 2026].

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Title
Text categorization with Support Vector Machines: Learning with many relevant features
Author / contributors
Thorsten Joachims
Publisher
Lecture notes in computer science
Publication year
1998
Language
English

Subjects

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Support vector machine; Computer science; Machine learning; Artificial intelligence; Categorization; Text categorization; Task (project management); Variety (cybernetics); Empirical research; Relevance vector machine; Mathematics; Statistics
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