Formal context coverage based on isolated labels: An efficient solution for text feature extraction

  • Authors:

  • Fethi Ferjani;Samir Elloumi;Ali Jaoua;Sadok Ben Yahia;Sahar Ismail;Sheikha Ravan

  • Affiliations:

  • Qatar University, Dept. of Computer Science and Engineering, P.O. Box 2713, Doha, Qatar;Qatar University, Dept. of Computer Science and Engineering, P.O. Box 2713, Doha, Qatar and Faculté des Sciences de Tunis, Département des Sciences de l'Informatique, Tunis, Tunisia;Qatar University, Dept. of Computer Science and Engineering, P.O. Box 2713, Doha, Qatar;Faculté des Sciences de Tunis, Département des Sciences de l'Informatique, Tunis, Tunisia;Qatar University, Dept. of Computer Science and Engineering, P.O. Box 2713, Doha, Qatar;Qatar University, Dept. of Computer Science and Engineering, P.O. Box 2713, Doha, Qatar

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2012

Quantified Score

Hi-index 0.07

Visualization

Abstract

Different available data as images, texts, or database may be mapped into an equivalent or approximate binary relation. A text may be considered as a binary relation relating sentences to words, while a numerical table may be represented by a binary relation after using some scaling approach. A social network may be also represented by a formal context. The objective of this paper is to present an original approach for covering a binary relation by formal concepts based on isolated single or multiple properties, i.e., those belonging to only one concept. As a matter of fact, isolated properties are efficiently used for discriminating and labeling concepts. The latter are used for browsing in a corpora, or in a document by navigating through associated labels. By using fringe relations, the presented approach compared to those of the literature has the advantage of offering a relevant feature of a context by significant labels. Carried out experiments show the benefits of the introduced approach.