rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Survey of Text Mining II
    sub title: Clustering, Classification, and Retrieval
  name:
    name part: Berry, Michael W.
    role:
      role term: editor.
  name:
    name part: Castellanos, Malu.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxk
    date issued: 2008
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVI, 240 p. online resource.
  abstract: 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 increasingly important in both academia and industry. This second volume continues to survey the evolving field of text mining - the application of techniques of machine learning, in conjunction with natural language processing, information extraction and algebraic/mathematical approaches, to computational information retrieval. Numerous diverse issues are addressed, ranging from the development of new learning approaches to novel document clustering algorithms, collectively spanning several major topic areas in text mining. Features: • Acts as an important benchmark in the development of current and future approaches to mining textual information • Serves as an excellent companion text for courses in text and data mining, information retrieval and computational statistics • Experts from academia and industry share their experiences in solving large-scale retrieval and classification problems • Presents an overview of current methods and software for text mining • Highlights open research questions in document categorization and clustering, and trend detection • Describes new application problems in areas such as email surveillance and anomaly detection Survey of Text Mining II offers a broad selection in state-of-the art algorithms and software for text mining from both academic and industrial perspectives, to generate interest and insight into the state of the field. This book will be an indispensable resource for researchers, practitioners, and professionals involved in information retrieval, computational statistics, and data mining. Michael W. Berry is a professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. …
  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.
  note: edited by Michael W. Berry, Malu Castellanos.
  subject:
    topic: Computer science
  subject:
    topic: Data structures (Computer science)
  subject:
    topic: Information storage and retrieval
  subject:
    topic: Multimedia information systems
  subject:
    topic: Text processing (Computer science)
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Computer Science
  subject:
    topic: Data Structures, Cryptology and Information Theory
  subject:
    topic: Document Preparation and Text Processing
  subject:
    topic: Information Storage and Retrieval
  subject:
    topic: Information Systems Applications (incl. Internet)
  subject:
    topic: Multimedia Information Systems
  subject:
    topic: Applications of Mathematics
  classification: QA76.9.D35
  classification: 005.74
  related item:
    title info:
      title: Springer eBooks
  identifier: 9781848000469
  identifier: http://dx.doi.org/10.1007/978-1-84800-046-9
  record info:
    record creation date: 100301
    record change date: 20151204164412.0
    record identifier: 978-1-84800-046-9