Triadic Formal Concept Analysis Research Articles

Who and where: context-aware advertisement recommendation on Twitter

Advertising is becoming a business on social networks. Billions of people around the world use social media, and fastly, it has become one of the defining technologies of our time. Social platforms like Twitter are one of the primary means of communication and information dissemination and can capture the interest of potential customers. Therefore, it is crucial to select suitable advertisements to users in specific times and locations for capturing their attention, profitably. In this paper, we propose a context-aware advertising recommendation system that, by analyzing the users’ tweets and movements along a timeline, infers the personal interests of users and provides attractive ads to users through the triadic formal concept analysis theory.

Role based access control design using three-way formal concept analysis

Role based access control (RBAC) is one of the popular access control models. On representing the policy behind RBAC, the literatures investigate the use of various knowledge representation techniques such as Descriptive logics, Formal Concept Analysis (FCA), Ontology etc. Based on the input of binary access control table, the existing knowledge representation techniques on RBAC derives two-way decisions whether to permit the access request or not. It works well when single element in the set of elements of a constituent of RBAC initiates the access request. Consider the scenario of multiple distinct elements in the set of elements of a constituent of RBAC initiate the collective access request to a set of elements in other constituent of RBAC. In many cases of this scenario, some elements possess but not all of the elements possess the permission to access all elements in other subset of a constituent of RBAC. On this situation, the collective access decision to those multiple distinct elements in the set of elements of a RBAC constituent appears in three forms such as permit, deny and non-commitment. Three-way formal concept analysis (3WCA) is an emerging knowledge representation technique which provides two types of three-way concepts and their lattices to enable three-way decisions from the binary information table. At this juncture, it is more suitable to apply 3WCA on representing the RBAC policy to enable three-way decisions instead of existing two-way decisions in classical FCA and triadic FCA. The main objective of this paper is to propose a methodology for modelling RBAC using 3WCA and attain its distinctive merits. Our discussion is on two lines of inquiry. We present on how 3WCA can provide suitable representation of RBAC policy and whether this representation follows role hierarchy and constraints of RBAC.

On closure operators related to maximal tricliques in tripartite hypergraphs

Triadic Formal Concept Analysis (3FCA) was introduced by Lehman and Wille almost two decades ago. Many researchers work in Data Mining and Formal Concept Analysis using the notions of closed sets, Galois and closure operators, and closure systems. However, a proper closure operator for enumeration of triconcepts, i.e. maximal triadic cliques of tripartite hypergraphs, 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.

Role based access control design using triadic concept analysis

Role based access control is one of the widely used access control models. There are investigations in the literature that use knowledge representation mechanisms such as formal concept analysis (FCA), description logics, and Ontology for representing access control mechanism. However, while using FCA, investigations reported in the literature so far work on the logic that transforms the three dimensional access control matrix into dyadic formal contexts. This transformation is mainly to derive the formal concepts, lattice structure and implications to represent role hierarchy and constraints of RBAC. In this work, we propose a methodology that models RBAC using triadic FCA without transforming the triadic access control matrix into dyadic formal contexts. Our discussion is on two lines of inquiry. We present how triadic FCA can provide a suitable representation of RBAC policy and we demonstrate how this representation follows role hierarchy and constraints of RBAC on sample healthcare network available in the literature.

K-Cliques mining in dynamic social networks based on triadic formal concept analysis

Internet of Things (IoT), an emerging computing paradigm which interconnects various ubiquitous things is facilitating the advancement of computational intelligence. This paper aims at investigating the computation intelligence extraction approach with focus on the dynamic k-clique mining that is an important issue in social network analysis. The k-clique detection problem as one of the fundamental problems in computer science, can assist us to understand the organization style and behavioral patterns of users in social networks. However, real social networks usually evolve over time and it remains a challenge to efficiently detect the k-cliques from dynamic social networks. To address this challenge, this paper proposes an efficient k-clique dynamic detection theorem based on triadic formal concept analysis (TFCA) with completed mathematical proof. With this proposed detection theorem, we prove that the k-cliques detection problem is equivalent to finding the explicit k-cliques generated from k-triadic equiconcepts plus the implicit k-cliques derived from its high-order triadic equiconcepts. Theoretical analysis and experimental results illustrate that the proposed detection algorithm is efficient for finding the k-cliques and exploring the dynamic characteristics of the sub-structures in social networks.