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Volumn 8, Issue 6, 2016, Pages

Mining λ-maximal cliques from a fuzzy graph

Author keywords

Degree of membership; Fuzzy concept analysis; Fuzzy cut; Fuzzy graph; Sustainability; maximal cliques

Indexed keywords

ALGORITHM; DATA MINING; EXPERIMENTAL STUDY; FEASIBILITY STUDY; FUZZY MATHEMATICS; GRAPHICAL METHOD; NATURAL RESOURCE; NUMERICAL METHOD; PLANNING METHOD; RESOURCE DEPLETION; SUSTAINABILITY; SUSTAINABLE DEVELOPMENT;

EID: 84976333429     PISSN: None     EISSN: 20711050     Source Type: Journal    
DOI: 10.3390/su8060553     Document Type: Article
Times cited : (17)

References (23)
  • 2
    • 84932644008 scopus 로고    scopus 로고
    • An efficient approach to generating location-sensitive recommendations in ad-hoc social network environments
    • Hao, F.; Li, S.; Min, G.; Kim, H.C.; Yau, S.S.; Yang, L.T. An efficient approach to generating location-sensitive recommendations in ad-hoc social network environments. IEEE Trans. Serv. Comput. 2015, 8, 520-533.
    • (2015) IEEE Trans. Serv. Comput. , vol.8 , pp. 520-533
    • Hao, F.1    Li, S.2    Min, G.3    Kim, H.C.4    Yau, S.S.5    Yang, L.T.6
  • 5
    • 84879133197 scopus 로고    scopus 로고
    • Performance improvement of a movie recommendation system based on personal propensity and secure collaborative filtering
    • Jeong, W.H.; Kim, S.J.; Park, D.S.; Kwak, J. Performance improvement of a movie recommendation system based on personal propensity and secure collaborative filtering. J. Inf. Process. Syst. 2013, 9, 157-172.
    • (2013) J. Inf. Process. Syst. , vol.9 , pp. 157-172
    • Jeong, W.H.1    Kim, S.J.2    Park, D.S.3    Kwak, J.4
  • 7
    • 84976278338 scopus 로고    scopus 로고
    • Dynamic fuzzy logic control of genetic algorithm probabilities
    • Guo, H.; Feng, Y.; Hao, F.; Zhong, S.; Li, S. Dynamic fuzzy logic control of genetic algorithm probabilities. J. Comput. 2014, 9, 22-27.
    • (2014) J. Comput. , vol.9 , pp. 22-27
    • Guo, H.1    Feng, Y.2    Hao, F.3    Zhong, S.4    Li, S.5
  • 9
    • 84908085418 scopus 로고    scopus 로고
    • MobiFuzzyTrust: An efficient fuzzy trust inference mechanism in mobile social networks
    • Hao, F.; Min, G.; Lin, M.; Luo, C.; Yang, L.T. MobiFuzzyTrust: An efficient fuzzy trust inference mechanism in mobile social networks. IEEE Trans. Parallel Distrib. Syst. 2014, 25, 2944-2955.
    • (2014) IEEE Trans. Parallel Distrib. Syst. , vol.25 , pp. 2944-2955
    • Hao, F.1    Min, G.2    Lin, M.3    Luo, C.4    Yang, L.T.5
  • 10
    • 85022185292 scopus 로고    scopus 로고
    • K-clique communities detection in social networks based on formal concept analysis
    • Hao, F.; Min, G.; Pei, Z.; Park, D.S.; Yang, L.T. K-clique communities detection in social networks based on formal concept analysis. IEEE Syst. J. 2015, 99, 1-10, doi:10.1109/JSYST.2015.2433294.
    • (2015) IEEE Syst. J. , vol.99 , pp. 1-10
    • Hao, F.1    Min, G.2    Pei, Z.3    Park, D.S.4    Yang, L.T.5
  • 11
    • 84994533747 scopus 로고    scopus 로고
    • A fuzzy FCA-based approach to conceptual clustering for automatic generation of concept hierarchy on uncertainty data
    • Ostrava, Czech Republic, 23-24 September
    • Quan, T.T.; Hui, S.C.; Cao, T.H. A fuzzy FCA-based approach to conceptual clustering for automatic generation of concept hierarchy on uncertainty data. In Proceedings of the CLA 2004 International Workshop on Concept Lattices and their Applications, Ostrava, Czech Republic, 23-24 September 2004; pp. 1-12.
    • (2004) Proceedings of the CLA 2004 International Workshop on Concept Lattices and their Applications , pp. 1-12
    • Quan, T.T.1    Hui, S.C.2    Cao, T.H.3
  • 12
    • 84867997005 scopus 로고    scopus 로고
    • A fast algorithm for the maximum clique problem
    • Ostergard, P.R. A fast algorithm for the maximum clique problem. Discret. Appl. Math. 2002, 120, 197-207.
    • (2002) Discret. Appl. Math. , vol.120 , pp. 197-207
    • Ostergard, P.R.1
  • 14
    • 33749468596 scopus 로고    scopus 로고
    • Finding community structure in networks using the eigenvectors of matrices
    • Newman, M.E. Finding community structure in networks using the eigenvectors of matrices. Phys. Rev. E 2006, 74, 036104, doi: 10.1103/PhysRevE.74.036104.
    • (2006) Phys. Rev. E , vol.74 , pp. 036104
    • Newman, M.E.1
  • 15
    • 77953882554 scopus 로고    scopus 로고
    • Network data
    • (accessed on 8 June).
    • Newman, M. Network data. Available online: http://www-personal.umich.edu/~mejn/netdata/ (accessed on 8 June 2016).
    • (2016)
    • Newman, M.1
  • 16
    • 37649031573 scopus 로고    scopus 로고
    • Detecting fuzzy community structures in complex networks with a Potts model
    • Reichardt, J.; Bornholdt, S. Detecting fuzzy community structures in complex networks with a Potts model. Phys. Rev. Lett. 2004, 93, 218701, doi: 10.1103/PhysRevLett.93.218701.
    • (2004) Phys. Rev. Lett. , vol.93 , pp. 218701
    • Reichardt, J.1    Bornholdt, S.2
  • 17
    • 84871189061 scopus 로고    scopus 로고
    • Uncovering the structure of heterogenous biological data: Fuzzy graph partitioning in the k-partite setting
    • Bielefeld, Germany, 20-22 September
    • Blochl, F.; Hartsperger, M.L.; Stumpflen, V.; Theis, F.J. Uncovering the structure of heterogenous biological data: Fuzzy graph partitioning in the k-partite setting. In Proceedings of the German Conference on Bioinformatics 2010, Bielefeld, Germany, 20-22 September 2010; pp. 31-40.
    • (2010) Proceedings of the German Conference on Bioinformatics 2010 , pp. 31-40
    • Blochl, F.1    Hartsperger, M.L.2    Stumpflen, V.3    Theis, F.J.4
  • 18
    • 38349126835 scopus 로고    scopus 로고
    • Fuzzy communities and the concept of bridgeness in complex networks
    • Nepusz, T.; Petroczi, A.; Negyessy, L.; Bazso, F. Fuzzy communities and the concept of bridgeness in complex networks. Phys. Rev. E 2008, 77, 016107, doi: 10.1103/PhysRevE.77.016107.
    • (2008) Phys. Rev. E , vol.77 , pp. 016107
    • Nepusz, T.1    Petroczi, A.2    Negyessy, L.3    Bazso, F.4
  • 21
    • 70349089696 scopus 로고    scopus 로고
    • A neuro-GA approach for the maximum fuzzy clique problem
    • Springer Berlin Heidelberg: Auckland, New Zealand
    • Bandyopadhyay, S.; Bhattacharyya, M. A neuro-GA approach for the maximum fuzzy clique problem. In Advances in Neuro-Information Processing; Springer Berlin Heidelberg: Auckland, New Zealand, 2009; pp. 605-612.
    • (2009) Advances in Neuro-Information Processing , pp. 605-612
    • Bandyopadhyay, S.1    Bhattacharyya, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.