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: Knowledge-Based Intelligent Information and Engineering Systems
    sub title: 7th International Conference, KES 2003, Oxford, UK, September 3-5, 2003, Proceedings, Part I
  name:
    name part: Palade, Vasile.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2003
    edition: 1st ed. 2003.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: CII, 1476 p. online resource.
  abstract: 2.1 Text Summarization "Text summarization is the process of distilling the most important information from a source (or sources) to produce an abridged version for a particular user (or users) and task (or tasks)" [3]. Basic and classical articles in text summarization appear in "Advances in automatic text summarization" [3]. A literature survey on information extraction and text summarization is given by Zechner [7]. In general, the process of automatic text summarization is divided into three stages: (1) analysis of the given text, (2) summarization of the text, (3) presentation of the summary in a suitable output form. Titles, abstracts and keywords are the most common summaries in Academic papers. Usually, the title, the abstract and the keywords are the first, second, and third parts of an Academic paper, respectively. The title usually describes the main issue discussed in the study and the abstract presents the reader a short description of the background, the study and its results. A keyword is either a single word (unigram), e.g.: 'learning', or a collocation, which means a group of two or more words, representing an important concept, e.g.: 'machine learning', 'natural language processing'. Retrieving collocations from text was examined by Smadja [5] and automatic extraction of collocations was examined by Kita et al. [1].
  table of contents: Keynote Lectures -- General Session Papers -- Invited Sessions Papers.
  note: edited by Vasile Palade.
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computer communication systems
  subject:
    topic: Information storage and retrieval
  subject:
    topic: Application software
  subject:
    topic: User interfaces (Computer systems)
  subject:
    topic: Information technology
  subject:
    topic: Business-Data processing
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Computer Communication Networks
  subject:
    topic: Information Storage and Retrieval
  subject:
    topic: Information Systems Applications (incl. Internet)
  subject:
    topic: User Interfaces and Human Computer Interaction
  subject:
    topic: IT in Business
  classification: Q334-342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Artificial Intelligence ; 2773
  identifier: 9783540452249
  identifier: https://doi.org/10.1007/978-3-540-45224-9
  record info:
    record creation date: 131124
    record change date: 20191024041059.0
    record identifier: 978-3-540-45224-9