Fuzzy tolerance relations and relational maps applied to information retrieval

L. Kóczy, Tamás D. Gedeon, Judit A. Kóczy

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

One of the major problems in automatic indexing and retrieval of documents is that usually it cannot be guaranteed that the user queries include (all) of the actual words that occur in the documents that should be retrieved. Also it often happens that words with several meanings occur in a document, but in a rather different context from that expected by the querying person. In order to achieve better recall and higher precision, fuzzy tolerance and similarity relations have been introduced based on the counted or estimated values of (hierarchical) co-occurrence frequencies. This study addresses the problem of how these relations can be generated from the occurrence frequencies, especially as these are based on possibilistic rather than probabilistic measures, and also how the relations can be implemented by fuzzy relevance matrices.

Original languageEnglish
Pages (from-to)49-61
Number of pages13
JournalFuzzy Sets and Systems
Volume126
Issue number1
DOIs
Publication statusPublished - Feb 16 2002

Fingerprint

Automatic indexing
Tolerance Relation
Fuzzy Relation
Information retrieval
Information Retrieval
Similarity Relation
Indexing
Person
Retrieval
Query
Tolerance

ASJC Scopus subject areas

  • Statistics and Probability
  • Electrical and Electronic Engineering
  • Statistics, Probability and Uncertainty
  • Information Systems and Management
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Artificial Intelligence

Cite this

Fuzzy tolerance relations and relational maps applied to information retrieval. / Kóczy, L.; Gedeon, Tamás D.; Kóczy, Judit A.

In: Fuzzy Sets and Systems, Vol. 126, No. 1, 16.02.2002, p. 49-61.

Research output: Contribution to journalArticle

Kóczy, L. ; Gedeon, Tamás D. ; Kóczy, Judit A. / Fuzzy tolerance relations and relational maps applied to information retrieval. In: Fuzzy Sets and Systems. 2002 ; Vol. 126, No. 1. pp. 49-61.
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