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:
a [ Acts as an important benchmark in the development of current
and future approaches to mining textual information
a [ Serves as an excellent companion text for courses in text
and data mining, information retrieval and computational
statistics
a [ Experts from academia and industry share their experiences
in solving large-scale retrieval and classification problems
a [ Presents an overview of current methods and software for
text mining
a [ Highlights open research questions in document
categorization and clustering, and trend detection
a [ 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 stateof 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.
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