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

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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Berry, Michael W. (Editor ), Castellanos, Malu (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Springer London : Imprint: Springer, 2008.
Edición:1st ed. 2008.
Temas:
Data structures (Computer science).
Information theory.
Natural language processing (Computer science).
Information storage and retrieval systems.
Application software.
Multimedia systems.
Mathematics.
Data Structures and Information Theory.
Natural Language Processing (NLP).
Information Storage and Retrieval.
Computer and Information Systems Applications.
Multimedia Information Systems.
Applications of Mathematics.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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