Survey of Text Mining: Clustering, Classification, and Retrieval

✍ Scribed by Michael W. Berry

Publisher: Springer, Berlin
Year: 2003
Tongue: English
Leaves: 252
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

I: CLUSTERING & CLASSIFICATION: * Cluster-preserving dimension reduction methods for efficient classification of text data * Automatic discovery of similar words * Simultaneous clustering and dynamic keyword weighting for text documents * Feature selection and document clustering II: INFORMATION EXTRACTION & RETRIEVAL: * Vector space models for search and cluster mining * HotMiner--Discovering hot topics from dirty text * Combining families of information retrieval algorithms using meta-learning III: TREND DETECTION: * Trend and behavior detection from Web queries * A survey of emerging trend detection in textual data mining * Index

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