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: Natural Language Processing and Text Mining
  name:
    name part: Kao, Anne.
    role:
      role term: editor.
  name:
    name part: Poteet, Stephen R.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxk
    date issued: 2007
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 265 p. online resource.
  abstract: With the increasing importance of the Web and other text-heavy application areas, the demands for and interest in both text mining and natural language processing (NLP) have been rising. Researchers in text mining have hoped that NLP—the attempt to extract a fuller meaning representation from free text—can provide useful improvements to text mining applications of all kinds. Bringing together a variety of perspectives from internationally renowned researchers, Natural Language Processing and Text Mining not only discusses applications of certain NLP techniques to certain Text Mining tasks, but also the converse, i.e., use of Text Mining to facilitate NLP. It explores a variety of real-world applications of NLP and text-mining algorithms in comprehensive detail, placing emphasis on the description of end-to-end solutions to real problems, and detailing the associated difficulties that must be resolved before the algorithm can be applied and its full benefits realized. In addition, it explores a number of cutting-edge techniques and approaches, as well as novel ways of integrating various technologies. Nevertheless, even readers with only a basic knowledge of data mining or text mining will benefit from the many illustrative examples and solutions. Topics and features: • Describes novel and high-impact text mining and/or natural language applications • Points out typical traps in trying to apply NLP to text mining • Illustrates preparation and preprocessing of text data – offering practical issues and examples • Surveys related supporting techniques, problem types, and potential technique enhancements • Examines the interaction of text mining and NLP This state-of-the-art, practical volume will be an essential resource for professionals and researchers who wish to learn how to apply text mining and language processing techniques to real world problems. In addition, it can be used as a supplementary text for advanced students studying text mining and NLP.
  table of contents: Overview -- Extracting Product Features and Opinions from Reviews -- Extracting Relations from Text: From Word Sequences to Dependency Paths -- Mining Diagnostic Text Reports by Learning to Annotate Knowledge Roles -- A Case Study in Natural Language Based Web Search -- Evaluating Self-Explanations in iSTART: Word Matching, Latent Semantic Analysis, and Topic Models -- Textual Signatures: Identifying Text-Types Using Latent Semantic Analysis to Measure the Cohesion of Text Structures -- Automatic Document Separation: A Combination of Probabilistic Classification and Finite-State Sequence Modeling -- Evolving Explanatory Novel Patterns for Semantically-Based Text Mining -- Handling of Imbalanced Data in Text Classification: Category-Based Term Weights -- Automatic Evaluation of Ontologies -- Linguistic Computing with UNIX Tools.
  note: edited by Anne Kao, Stephen R. Poteet.
  subject:
    topic: Computer science
  subject:
    topic: Microprocessors
  subject:
    topic: Computers
  subject:
    topic: Information storage and retrieval
  subject:
    topic: Computational linguistics
  subject:
    topic: Computer Science
  subject:
    topic: Information Storage and Retrieval
  subject:
    topic: Computing Methodologies
  subject:
    topic: Computational Linguistics
  subject:
    topic: Processor Architectures
  subject:
    topic: Theory of Computation
  subject:
    topic: Information Systems Applications (incl. Internet)
  classification: QA75.5-76.95
  classification: 025.04
  related item:
    title info:
      title: Springer eBooks
  identifier: 9781846287541
  identifier: http://dx.doi.org/10.1007/978-1-84628-754-1
  record info:
    record creation date: 100301
    record change date: 20151204154939.0
    record identifier: 978-1-84628-754-1