Survey of Text Mining II: Clustering, Classification, and Retrieval

ISBN 10: 184996713X / ISBN 13: 9781849967136

Verlag: Springer, 2010

In. Bestandsnummer des Verkäufers ria9781849967136_new

Inhaltsangabe:

The development of techniques for mining unstructured, semi-structured, and fully structured textual data has become critical in both academia and industry. This Second Edition brings readers thoroughly up to date with the emerging field of text mining, the application of techniques of machine learning in conjunction with natural language processing, information extraction, and algebraic/mathematical approaches to computational information retrieval. The book explores a broad range of issues, ranging from the development of new learning approaches to the parallelization of existing algorithms. In addition, it describes new application problems in areas such as email surveillance and anomaly detection. Presenting a comprehensive selection of topics within the field, this book is an indispensable resource for researchers, practitioners, and professionals involved in information retrieval, computational statistics, and datamining.

Von der hinteren Coverseite:

The proliferation of digital computing devices and their use in communication has resulted in an increased demand for systems and algorithms capable of mining textual data. Thus, the development of techniques for mining unstructured, semi-structured, and fully-structured textual data has become increasingly important in both academia and industry.

This second volume continues to survey the evolving field of text mining - the application of techniques of machine learning, in conjunction with natural language processing, information extraction and algebraic/mathematical approaches, to computational information retrieval. Numerous diverse issues are addressed, ranging from the development of new learning approaches to novel document clustering algorithms, collectively spanning several major topic areas in text mining.

Features:

Acts as an important benchmark in the development of current and future approaches to mining textual information

Serves as an excellent companion text for courses in text and data mining, information retrieval and computational statistics

Experts from academia and industry share their experiences in solving large-scale retrieval and classification problems

Presents an overview of current methods and software for text mining

Highlights open research questions in document categorization and clustering, and trend detection

Describes new application problems in areas such as email surveillance and anomaly detection

Survey of Text Mining II offers a broad selection in state-of-the art algorithms and software for text mining from both academic and industrial perspectives, to generate interest and insight into the state of the field. This book will be an indispensable resource for researchers, practitioners, and professionals involved in information retrieval, computational statistics, and data mining.

Michael W. Berry is a professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville.

Malu Castellanos is a senior researcher at Hewlett-Packard Laboratories in Palo Alto, California.

Bibliografische Details

Titel: Survey of Text Mining II: Clustering, ...
Verlag: Springer
Erscheinungsdatum: 2010
Einband: Softcover
Zustand: New