Scalable Mining of Frequent Tri-concepts from Folksonomies

Trabelsi, Chiraz; Jelassi, Nader; Yahia, Sadok Ben

doi:10.1007/978-3-642-30220-6_20

Cited by 19 publications

(12 citation statements)

References 9 publications

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“…Subsequently, FCA is extended into different Mining similar concepts Aswani Kumar, 2011b Knowledge discovery Aswani Kumar, 2012 Rule mining Belohlavek et al, 2011aIPAQ questionnaires Belohlavek et al, 2013b Background knowledge Dau, 2013 Analyzing a triple store Fowler, 2013 Order in taxonomy Galitsky et al, 2013 Pattern on parse thickets Macko, 2013 Fuzzy FCA Missaoui and Kwuida, 2011 Triadic rules Nguyen et al, 2011 Mathematical search Nguyen and Yamamoto, 2012 Learning from graph Li et al, 2011b Symbolic data analysis Pavlovic, 2012 Quantitative data analysis Rouane et al, 2013 Multi relational data Li and Tsai, 2013 Sentiments analysis Trabelsi et al, 2012 Analyzing folksonomies Vityaev et al, 2012 Probabilistic concepts Watmough, 2014 ERP analysis Yang et al, 2011b Decision-making Zhao and Liu, 2011…”

Section: Discussionmentioning

confidence: 99%

A comprehensive survey on formal concept analysis, its research trends and applications

Singh

Cherukuri

Gani

2016

International Journal of Applied Mathematics and Computer Science

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In recent years, FCA has received significant attention from research communities of various fields. Further, the theory of FCA is being extended into different frontiers and augmented with other knowledge representation frameworks. In this backdrop, this paper aims to provide an understanding of the necessary mathematical background for each extension of FCA like FCA with granular computing, a fuzzy setting, interval-valued, possibility theory, triadic, factor concepts and handling incomplete data. Subsequently, the paper illustrates emerging trends for each extension with applications. To this end, we summarize more than 350 recent (published after 2011) research papers indexed in Google Scholar, IEEE Xplore, ScienceDirect, Scopus, SpringerLink, and a few authoritative fundamental papers.

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Section: Discussionmentioning

confidence: 99%

A comprehensive survey on formal concept analysis, its research trends and applications

Singh

Cherukuri

Gani

2016

International Journal of Applied Mathematics and Computer Science

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“…Proof. One can find the proof of extensivity and idempotency in (Trabelsi et al, 2012). It is easy to see that every formal triconcept is a fixpoint of h(·) and every triset (…”

Section: Non-monotonicity Of Tricons Concept Forming Operatormentioning

confidence: 99%

“…An interesting approach from (Spyropoulou et al, 2014) can be used to enumerate formal triconcepts as the maximal fixpoints of a set system of closed and connected sets (CCS) but suffers from presence of phantom hyperedges because of the lossy k-partite graph encoding. In this paper, we show how to define a proper triset system for the concept forming operator from (Trabelsi et al, 2012) that makes it a closure operator, describe the family of closure operators of this type and investigate their properties, and prove that there is no an associated closure operator on the whole triset system for a given tricontext. We also introduce a notion of (maximal) switching generator -a triset resulting in different closed patterns that contain it.…”

Section: Introductionmentioning

confidence: 99%

On closure operators related to maximal tricliques in tripartite hypergraphs

Ignatov

2018

Discrete Applied Mathematics

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Triadic Formal Concept Analysis (3FCA) was introduced by Lehman andWille almost two decades ago. And many researchers work in Data Mining and Formal Concept Analysis using the notions of closed sets, Galois and closure operators, closure systems, but up-to-date even though that different researchers actively work on mining triadic and n-ary relations, a proper closure operator for enumeration of triconcepts, i.e. maximal triadic cliques of tripartite hypergaphs, was not introduced. In this paper we show that the previously introduced operators for obtaining triconcepts and maximal connected and complete sets (MCCSs) are not always consistent and provide the reader with a definition of valid closure operator and associated set system. Moreover, we study the difficulties of related problems from order-theoretic and combinatorial point view as well as provide the reader with justifications of the complexity classes of these problems.

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“…Several authors generalized bi‐ and triclustering to the n ‐dimensional clustering. Trabelsi et al152 propose novel methods for improving scalability of frequent triconcepts mining from Folksonomies. Voutsadakis99 extended triadic concept analysis to n ‐dimensional case.…”

Section: Extensions Of Fcamentioning

confidence: 99%

Knowledge representation and processing with formal concept analysis

Kuznetsov

Poelmans

2013

WIREs Data Min & Knowl

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During the last three decades, formal concept analysis (FCA) became a well‐known formalism in data analysis and knowledge discovery because of its usefulness in important domains of knowledge discovery in databases (KDD) such as ontology engineering, association rule mining, machine learning, as well as relation to other established theories for representing knowledge processing, like description logics, conceptual graphs, and rough sets. In early days, FCA was sometimes misconceived as a static crisp hardly scalable formalism for binary data tables. In this paper, we will try to show that FCA actually provides support for processing large dynamical complex (may be uncertain) data augmented with additional knowledge. © 2013 Wiley Periodicals, Inc. This article is categorized under: Fundamental Concepts of Data and Knowledge > Key Design Issues in Data Mining Fundamental Concepts of Data and Knowledge > Knowledge Representation Technologies > Computational Intelligence

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Scalable Mining of Frequent Tri-concepts from Folksonomies

Cited by 19 publications

References 9 publications

A comprehensive survey on formal concept analysis, its research trends and applications

A comprehensive survey on formal concept analysis, its research trends and applications

On closure operators related to maximal tricliques in tripartite hypergraphs

Knowledge representation and processing with formal concept analysis

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