A model for extracting keywords of document using term frequency and distribution

Jae Woo Lee, Doo Kwon Baik

Research output: Chapter in Book/Report/Conference proceedingChapter

6 Citations (Scopus)

Abstract

In information retrieval systems, it is very important that indexing is defined very well by appropriate terms about documents. In this paper, we propose a simple retrieval model based on terms distribution characteristics besides term frequency in documents. We define the keywords distribution characteristics using a statistics, standard deviation. We can extract document keywords that term frequency is great and standard deviation is great. And if term frequency is great and standard deviation is small, the terms can be defined as paragraph keywords. Applying our proposed retrieval model we can search many documents or knowledge using the document keywords and paragraph keywords.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsAlexander Gelbukh
PublisherSpringer Verlag
Pages437-440
Number of pages4
ISBN (Print)3540210067, 9783540210061
DOIs
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2945
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Lee, J. W., & Baik, D. K. (2004). A model for extracting keywords of document using term frequency and distribution. In A. Gelbukh (Ed.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 437-440). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2945). Springer Verlag. https://doi.org/10.1007/978-3-540-24630-5_53