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.
Auflage
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Research
Illustrationen
46
46 s/w Abbildungen
XVII, 244 p. 46 illus.
Maße
Höhe: 23.5 cm
Breite: 15.5 cm
Gewicht
ISBN-13
978-0-387-95563-6 (9780387955636)
DOI
10.1007/978-1-4757-4305-0
Schweitzer Klassifikation
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.
