Concept Lattice Theory in Data Mining and its Applications

  • KANINDA MUSUMBU Université Nouveaux Horizons
  • Pascal SUNGU
  • Nathalie WANDJI African Institute of Mathematical Science
DOI: https://doi.org/10.53555/cse.v5i7.2951
Keywords: Formal concept, Frequent pattern, Association rules

Abstract

Concept lattice has been proven to be a very eective tool and architecture for data mining in general. It is widely used for data analysis and knowledge discovery and various concept lattice based approaches are used depending on the type of data. This paper aims at presenting one application of the lattice theory : the text mining. In this approach, we applied the notion of lattice theory by using one of its components mostly used in data mining, the formal concept analysis which has a powerful method, the association rule extraction which helps to nd in a database patterns which appear frequently together.

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Author Biographies

KANINDA MUSUMBU, Université Nouveaux Horizons

Maître de Conférences, Université Bordeaux, Université Nouveaux Horizons

Pascal SUNGU

Master student, Computational Mathematics, Pan African University of Science, Technology and Innovation. Assistant Université Nouveaux Horizons

Nathalie WANDJI, African Institute of Mathematical Science

PhD student, Tutor at AIMS (African Institute of Mathematical Science) Cameroon

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Cherfi, Hacene and Toussaint, Yannick. ; Adéquation d’indices statistiques à l’interprétation de règles d’association; 6èmes Journées internationales d’Analyse statistique des Données Textuelles-JADT 2002; 233–244; 2002.

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Published
2019-07-13
How to Cite
MUSUMBU, K., SUNGU, P., & WANDJI, N. (2019). Concept Lattice Theory in Data Mining and its Applications. IJRDO -Journal of Computer Science Engineering, 5(7), 01-10. https://doi.org/10.53555/cse.v5i7.2951
Issue
Vol. 5 No. 7 (2019): IJRDO - Journal of Computer Science Engineering | ISSN: 2456-1843
Section
Articles

Copyright (c) 2019 IJRDO - Journal of Computer Science Engineering (ISSN: 2456-1843)

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