Inductive Inference for Large Scale Text Classification: Kernel Approaches and Techniques

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Catarina Silva Bernadete Ribeiro

Inductive Inference for Large Scale Text Classification

Kernel Approaches and Techniques

Catarina Silva, Bernadete Ribeiro

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English

Springer-Verlag Berlin and Heidelberg GmbH & Co. K
13 November 2009

Computational linguistics; Maths for engineers; Desktop publishing; Artificial intelligence

Series: Studies in Computational Intelligence

Summary
Details

Text classification is becoming a crucial task to analysts in different areas. In the last few decades, the production of textual documents in digital form has increased exponentially. Their applications range from web pages to scientific documents, including emails, news and books. Despite the widespread use of digital texts, handling them is inherently difficult - the large amount of data necessary to represent them and the subjectivity of classification complicate matters.

This book gives a concise view on how to use kernel approaches for inductive inference in large scale text classification; it presents a series of new techniques to enhance, scale and distribute text classification tasks. It is not intended to be a comprehensive survey of the state-of-the-art of the whole field of text classification. Its purpose is less ambitious and more practical: to explain and illustrate some of the important methods used in this field, in particular kernel approaches and techniques.

By: Catarina Silva, Bernadete Ribeiro
Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Country of Publication: Germany
Edition: 2010 ed.
Volume: 255
Dimensions: Height: 235mm, Width: 155mm, Spine: 11mm
Weight: 940g
ISBN: 9783642045325
ISBN 10: 3642045324
Series: Studies in Computational Intelligence
Pages: 155
Publication Date: 13 November 2009
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active