Survey of Text Mining II Clustering, Classification, and Retrieval /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Berry, Michael W. (Editor), Castellanos, Malu (Editor)
• Format: Electronic eBook
• Language: English
• Published: London : Springer London, 2008.
• Subjects: Computer science.; Data structures (Computer science).; Information storage and retrieval.; Multimedia information systems.; Text processing (Computer science).; Applied mathematics.; Engineering mathematics.; Computer Science.; Data Structures, Cryptology and Information Theory.; Document Preparation and Text Processing.; Information Storage and Retrieval.; Information Systems Applications (incl. Internet).; Multimedia Information Systems.; Applications of Mathematics.

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 incr...

Table of Contents:

• Clustering
• Cluster-Preserving Dimension Reduction Methods for Document Classification
• Automatic Discovery of SimilarWords
• Principal Direction Divisive Partitioning with Kernels and k-Means Steering
• Hybrid Clustering with Divergences
• Text Clustering with Local Semantic Kernels
• Document Retrieval and Representation
• Vector Space Models for Search and Cluster Mining
• Applications of Semidefinite Programming in XML Document Classification
• Email Surveillance and Filtering
• Discussion Tracking in Enron Email Using PARAFAC
• Spam Filtering Based on Latent Semantic Indexing
• Anomaly Detection
• A Probabilistic Model for Fast and Confident Categorization of Textual Documents
• Anomaly Detection Using Nonnegative Matrix Factorization
• Document Representation and Quality of Text: An Analysis.