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A comprehensive review on updating concept lattices and its application in updating association rules
Author(s) -
Shemis Ebtesam,
Mohammed Ammar
Publication year - 2021
Publication title -
wiley interdisciplinary reviews: data mining and knowledge discovery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.506
H-Index - 47
eISSN - 1942-4795
pISSN - 1942-4787
DOI - 10.1002/widm.1401
Subject(s) - lattice miner , association rule learning , formal concept analysis , computer science , lattice (music) , basis (linear algebra) , association (psychology) , representation (politics) , data mining , theoretical computer science , data science , algorithm , mathematics , epistemology , philosophy , physics , geometry , politics , acoustics , political science , law
Formal concept analysis (FCA) visualizes formal concepts in terms of a concept lattice. Usually, it is an NP‐problem and consumes plenty of time and storage space to update the changes of the lattice. Thus, introducing an efficient way to update and maintain such lattices is a significant area of interest within the field of FCA and its applications. One of those vital FCA applications is the association rule mining (ARM), which aims at generating a loss‐less nonredundant compact Association Rule‐basis (AR‐basis). Currently, the real‐world data rapidly overgrow that asks the need for updating the existing concept lattice and AR‐basis upon data change continually. Intuitively, updating and maintaining an existing concept‐lattice or AR‐basis is much more efficient and consistent than reconstructing them from scratch, particularly in the case of massive data. So far, the area of updating both concept lattice and AR‐basis has not received much attention. Besides, few noncomprehensive studies have focused only on updating the concept lattice. From this point, this article comprehensively introduces basic knowledge regarding updating both concept lattices and AR‐basis with new illustrations, formalization, and examples. Also, the article reviews and compares recent remarkable works and explores the emerging future research trends. This article is categorized under: Algorithmic Development > Association Rules Fundamental Concepts of Data and Knowledge > Knowledge Representation Technologies > Association Rules