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The Text Mining Handbook

剑桥大学出版社 The Text Mining Handbook - Advanced Approaches in Analyzing Ustructured Data (2007)
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The Text Mining Handbook
Text mining is a new and exciting area of computer science research that tries to
solve the crisis of information overload by combining techniques from data mining,
machine learning, natural language processing, information retrieval, and knowledge
management. Similarly, link detection – a rapidly evolving approach to the analysis of
text that shares and builds on many of the key elements of text mining – also provides
new tools for people to better leverage their burgeoning textual data resources. Link
detection relies on a process of building up networks of interconnected objects through
various relationships in order to discover patterns and trends. The main tasks of link
detection are to extract, discover, and link together sparse evidence from vast amounts
of data sources, to represent and evaluate the significance of the related evidence, and
to learn patterns to guide the extraction, discovery, and linkage of entities.
The Text Mining Handbook presents a comprehensive discussion of the state of the art
in text mining and link detection. In addition to providing an in-depth examination of core
text mining and link detection algorithms and operations, the work examines advanced
preprocessing techniques, knowledge representation considerations, and visualization
approaches. Finally, the book explores current real-world, mission-critical applications
of text mining and link detection in such varied fields as corporate finance business
intelligence, genomics research, and counterterrorism activities.
Dr. Ronen Feldman is a Senior Lecturer in the Mathematics and Computer Science
Department of Bar-Ilan University and Director of the Data and Text Mining Laboratory.
Dr. Feldman is cofounder, Chief Scientist, and President of ClearForest, Ltd., a leader
in developing next-generation text mining applications for corporate and government
clients. He also recently served as an Adjunct Professor at New York University’s Stern
School of Business. A pioneer in the areas of machine learning, data mining, and unstruc-
tured data management, he has authored or coauthored more than 70 published articles
and conference papers in these areas.
James Sanger is a venture capitalist, applied technologist, and recognized industry expert
in the areas of commercial data solutions, Internet applications, and IT security products.
He is a partner at ABS Ventures, an independent venture firm founded in 1982 and
originally associated with technology banking leader Alex. Brown and Sons. Immediately
before joining ABS Ventures, Mr. Sanger was a Managing Director in the New York
offices of DB Capital Venture Partners, the global venture capital arm of Deutsche Bank.
Mr. Sanger has been a board member of several thought-leading technology companies,
including Inxight Software, Gomez Inc., and ClearForest, Inc.; he has also served as an
official observer to the boards of AlphaBlox (acquired by IBM in 2004), Intralinks, and
Imagine Software and as a member of the Technical Advisory Board of Qualys, Inc.
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THE TEXT
MINING HANDBOOK
Advanced Approaches in
Analyzing Unstructured Data
Ronen Feldman
Bar-Ilan University, Israel
James Sanger
ABS Ventures, Waltham, Massachusetts
iii

CAMBRIDGE UNIVERSITY PRESS
Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, São Paulo
Cambridge University Press
The Edinburgh Building, Cambridge CB2 8RU, UK
First published in print format
ISBN-13 978-0-521-83657-9
ISBN-13 978-0-511-33507-5
© Ronen Feldman and James Sanger 2007
2006
Information on this title: www.cambridge.org/9780521836579
This publication is in copyright. Subject to statutory exception and to the provision of
relevant collective licensing agreements, no reproduction of any part may take place
without the written
p
ermission of Cambrid
g
e University Press.
ISBN-10 0-511-33507-5
ISBN-10 0-521-83657-3
Cambridge University Press has no responsibility for the persistence or accuracy of urls
for external or third-party internet websites referred to in this publication, and does not
g
uarantee that any content on such websites is, or will remain, accurate or a
pp
ro
p
riate.
Published in the United States of America by Cambridge University Press, New York
www.cambridge.org
hardback
eBook (NetLibrary)
eBook (NetLibrary)
hardback
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