Survey of Text Mining
Clustering, Classification, and Retrieval
Published on 9. September 2003
Book
Hardback
XVII, 244 pages
978-0-387-95563-6 (ISBN)
Description
As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. This survey volume draws upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. Reseachers, practitioners, and professionals in information retrieval who need to know the latest text-mining methods and algorithms will find the book an essential resource.
More details
Edition
2004 ed.
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Research
Illustrations
46 s/w Abbildungen
XVII, 244 p. 46 illus.
Dimensions
Height: 23.5 cm
Width: 15.5 cm
Weight
576 gr
ISBN-13
978-0-387-95563-6 (9780387955636)
DOI
10.1007/978-1-4757-4305-0
Schweitzer Classification
Other editions
New editions
Michael W. Berry | Malu Castellanos
Survey of Text Mining II
Clustering, Classification, and Retrieval
Book
03/2008
Springer
€53.49
Shipment within 15-20 days
Additional editions
E-Book
03/2013
Springer
€96.29
Available for download
Book
10/2011
Springer
€139.09
Shipment within 15-20 days
Content
I Clustering and Classification.- 1 Cluster-Preserving Dimension Reduction Methods for Efficient Classification of Text Data.- 2 Automatic Discovery of Similar Words.- 3 Simultaneous Clustering and Dynamic Keyword Weighting for Text Documents.- 4 Feature Selection and Document Clustering.- II Information Extraction and Retrieval.- 5 Vector Space Models for Search and Cluster Mining.- 6 HotMiner: Discovering Hot Topics from Dirty Text.- 7 Combining Families of Information Retrieval Algorithms Using Metalearning.- III Trend Detection.- 8 Trend and Behavior Detection from Web Queries.- 9 A Survey of Emerging Trend Detection in Textual Data Mining.