Next Article in Journal
A Novel Combined Model Based on an Artificial Intelligence Algorithm—A Case Study on Wind Speed Forecasting in Penglai, China
Next Article in Special Issue
Leadership of Information Security Manager on the Effectiveness of Information Systems Security for Secure Sustainable Computing
Previous Article in Journal
Philanthropic Fundraising of Higher Education Institutions: A Review of the Malaysian and Australian Perspectives
Previous Article in Special Issue
Sustainable Wearables: Wearable Technology for Enhancing the Quality of Human Life

Mining λ-Maximal Cliques from a Fuzzy Graph

Department of Computer Software Engineering, Soonchunhyang University, 22 Soonchunhyang-ro, Shinchang-myeon, Asan 31538, Korea
Department of Theoretical and Applied Sciences (DiSTA), University of Insubria, Via Mazzini 5, Varese 21100, Italy
Author to whom correspondence should be addressed.
Academic Editors: James Park and Han-Chieh Chao
Sustainability 2016, 8(6), 553;
Received: 30 April 2016 / Revised: 3 June 2016 / Accepted: 3 June 2016 / Published: 14 June 2016
(This article belongs to the Special Issue Advanced IT based Future Sustainable Computing)
The depletion of natural resources in the last century now threatens our planet and the life of future generations. For the sake of sustainable development, this paper pioneers an interesting and practical problem of dense substructure (i.e., maximal cliques) mining in a fuzzy graph where the edges are weighted by the degree of membership. For parameter 0 λ 1 (also called fuzzy cut in fuzzy logic), a newly defined concept λ-maximal clique is introduced in a fuzzy graph. In order to detect the λ-maximal cliques from a fuzzy graph, an efficient mining algorithm based on Fuzzy Formal Concept Analysis (FFCA) is proposed. Extensive experimental evaluations are conducted for demonstrating the feasibility of the algorithm. In addition, a novel recommendation service based on an λ-maximal clique is provided for illustrating the sustainable usability of the problem addressed. View Full-Text
Keywords: sustainability; λ-maximal cliques; fuzzy graph; fuzzy concept analysis; degree of membership; fuzzy cut sustainability; λ-maximal cliques; fuzzy graph; fuzzy concept analysis; degree of membership; fuzzy cut
Show Figures

Figure 1

MDPI and ACS Style

Hao, F.; Park, D.-S.; Li, S.; Lee, H.M. Mining λ-Maximal Cliques from a Fuzzy Graph. Sustainability 2016, 8, 553.

AMA Style

Hao F, Park D-S, Li S, Lee HM. Mining λ-Maximal Cliques from a Fuzzy Graph. Sustainability. 2016; 8(6):553.

Chicago/Turabian Style

Hao, Fei, Doo-Soon Park, Shuai Li, and Hwa M. Lee 2016. "Mining λ-Maximal Cliques from a Fuzzy Graph" Sustainability 8, no. 6: 553.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop