Knowledge discovery in social networks by using a logic-based treatment of implications

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1 January 2015

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Knowl. Based Syst. vol. 87 , pages 16–25.

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Please, cite this work as:

[Cor+15] P. Cordero, M. Enciso, Á. Mora, et al. “Knowledge discovery in social networks by using a logic-based treatment of implications”. In: Knowl. Based Syst. 87 (2015), pp. 16-25. DOI: 10.1016/J.KNOSYS.2015.07.018. URL: https://doi.org/10.1016/j.knosys.2015.07.018.

@Article{Cordero2015,
     author = {Pablo Cordero and Manuel Enciso and {’A}ngel Mora and Manuel Ojeda-Aciego and Carlos Rossi},
     journal = {Knowl. Based Syst.},
     title = {Knowledge discovery in social networks by using a logic-based treatment of implications},
     year = {2015},
     pages = {16–25},
     volume = {87},
     bibsource = {dblp computer science bibliography, https://dblp.org},
     biburl = {https://dblp.org/rec/journals/kbs/CorderoEMOR15.bib},
     doi = {10.1016/J.KNOSYS.2015.07.018},
     timestamp = {Fri, 23 Sep 2022 01:00:00 +0200},
     url = {https://doi.org/10.1016/j.knosys.2015.07.018},
}

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  • CrossRef - Citation Indexes: 22
  • Scopus - Citation Indexes: 34
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Cites

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Papers citing this work

The following is a non-exhaustive list of papers that cite this work:

[1] O. Addam, A. Chen, W. Hoang, et al. “Foreign exchange data crawling and analysis for knowledge discovery leading to informative decision making”. In: Knowledge-Based Systems 102 (Jun. 2016), p. 1–19. ISSN: 0950-7051. DOI: 10.1016/j.knosys.2016.03.005. URL: http://dx.doi.org/10.1016/j.knosys.2016.03.005.

[2] Ľ. Antoni, P. Eliaš, J. Guniš, et al. “Bimorphisms and attribute implications in heterogeneous formal contexts”. In: International Journal of Approximate Reasoning 172 (Sep. 2024), p. 109245. ISSN: 0888-613X. DOI: 10.1016/j.ijar.2024.109245. URL: http://dx.doi.org/10.1016/j.ijar.2024.109245.

[3] R. G. Aragón, J. Medina, and E. Ramírez-Poussa. “Identifying Non-Sublattice Equivalence Classes Induced by an Attribute Reduction in FCA”. In: Mathematics 9.5 (Mar. 2021), p. 565. ISSN: 2227-7390. DOI: 10.3390/math9050565. URL: http://dx.doi.org/10.3390/math9050565.

[4] F. Benito‐Picazo, M. Enciso, C. Rossi, et al. “Enhancing the conversational process by using a logical closure operator in phenotypes implications”. In: Mathematical Methods in the Applied Sciences 41.3 (Feb. 2017), p. 1089–1100. ISSN: 1099-1476. DOI: 10.1002/mma.4338. URL: http://dx.doi.org/10.1002/mma.4338.

[5] I. P. Cabrera, P. Cordero, F. Garcia-Pardo, et al. “Galois Connections Between a Fuzzy Preordered Structure and a General Fuzzy Structure”. In: IEEE Transactions on Fuzzy Systems 26.3 (Jun. 2018), p. 1274–1287. ISSN: 1941-0034. DOI: 10.1109/tfuzz.2017.2718495. URL: http://dx.doi.org/10.1109/tfuzz.2017.2718495.

[6] P. Cordero, M. Enciso, Á. Mora, et al. “A Formal Concept Analysis Approach to Cooperative Conversational Recommendation”. In: International Journal of Computational Intelligence Systems 13.1 (2020), p. 1243. ISSN: 1875-6883. DOI: 10.2991/ijcis.d.200806.001. URL: http://dx.doi.org/10.2991/ijcis.d.200806.001.

[7] P. Cordero, M. Enciso, A. Mora, et al. “Parameterized simplification logic I: reasoning with implications and classes of closure operators”. In: International Journal of General Systems 49.7 (Oct. 2020), p. 724–746. ISSN: 1563-5104. DOI: 10.1080/03081079.2020.1831484. URL: http://dx.doi.org/10.1080/03081079.2020.1831484.

[8] D. Dubois, J. Medina, H. Prade, et al. “Disjunctive attribute dependencies in formal concept analysis under the epistemic view of formal contexts”. In: Information Sciences 561 (Jun. 2021), p. 31–51. ISSN: 0020-0255. DOI: 10.1016/j.ins.2020.12.085. URL: http://dx.doi.org/10.1016/j.ins.2020.12.085.

[9] C. Huang, B. Hu, G. Jiang, et al. “Modeling of agent-based complex network under cyber-violence”. In: Physica A: Statistical Mechanics and its Applications 458 (Sep. 2016), p. 399–411. ISSN: 0378-4371. DOI: 10.1016/j.physa.2016.03.066. URL: http://dx.doi.org/10.1016/j.physa.2016.03.066.

[10] H. Jelodar, Y. Wang, M. Rabbani, et al. “A NLP framework based on meaningful latent-topic detection and sentiment analysis via fuzzy lattice reasoning on youtube comments”. In: Multimedia Tools and Applications 80.3 (Sep. 2020), p. 4155–4181. ISSN: 1573-7721. DOI: 10.1007/s11042-020-09755-z. URL: http://dx.doi.org/10.1007/s11042-020-09755-z.

[11] F. Kardoš, J. Pócs, and J. Pócsová. “On concept reduction based on some graph properties”. In: Knowledge-Based Systems 93 (Feb. 2016), p. 67–74. ISSN: 0950-7051. DOI: 10.1016/j.knosys.2015.11.003. URL: http://dx.doi.org/10.1016/j.knosys.2015.11.003.

[12] T. Liu, H. Zhang, and H. Zhang. “The Impact of Social Media on Risk Communication of Disasters—A Comparative Study Based on Sina Weibo Blogs Related to Tianjin Explosion and Typhoon Pigeon”. In: International Journal of Environmental Research and Public Health 17.3 (Jan. 2020), p. 883. ISSN: 1660-4601. DOI: 10.3390/ijerph17030883. URL: http://dx.doi.org/10.3390/ijerph17030883.

[13] X. Luo. “The Logic of Homophily Dynamics in Heterogeneous Networks: Axiomatization, Model Checking and Validity Checking”. In: Mathematics 11.16 (Aug. 2023), p. 3484. ISSN: 2227-7390. DOI: 10.3390/math11163484. URL: http://dx.doi.org/10.3390/math11163484.

[14] A. Majeed and I. Rauf. “Graph Theory: A Comprehensive Survey about Graph Theory Applications in Computer Science and Social Networks”. In: Inventions 5.1 (Feb. 2020), p. 10. ISSN: 2411-5134. DOI: 10.3390/inventions5010010. URL: http://dx.doi.org/10.3390/inventions5010010.

[15] J. Mangaiyarkkarasi, J. Shanthalakshmi Revathy, and S. Mehta. “Introduction to Graph Theory”. In: Neural Networks and Graph Models for Traffic and Energy Systems. IGI Global, Feb. 2025, p. 65–82. ISBN: 9798337302928. DOI: 10.4018/979-8-3373-0290-4.ch003. URL: http://dx.doi.org/10.4018/979-8-3373-0290-4.ch003.

[16] J. Medina, K. Pakhomova, and E. Ramirez-Poussa. “Interpreting and analyzing a location-based social network by fuzzy formal contexts”. In: 2017 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, Nov. 2017, p. 1–6. DOI: 10.1109/ssci.2017.8285282. URL: http://dx.doi.org/10.1109/ssci.2017.8285282.

[17] J. Medina, K. Pakhomova, and E. Ramírez-Poussa. “Recommendation Solution for a Locate-Based Social Network via Formal Concept Analysis”. In: Trends in Mathematics and Computational Intelligence. Springer International Publishing, Oct. 2018, p. 131–138. ISBN: 9783030004859. DOI: 10.1007/978-3-030-00485-9_15. URL: http://dx.doi.org/10.1007/978-3-030-00485-9_15.

[18] S. M. Neto, S. Dias, R. Missaoui, et al. “Identification of substructures in complex networks using formal concept analysis”. In: International Journal of Web Information Systems 14.3 (Aug. 2018), p. 281–298. ISSN: 1744-0084. DOI: 10.1108/ijwis-10-2017-0067. URL: http://dx.doi.org/10.1108/ijwis-10-2017-0067.

[19] M. Ojeda-Hernández, I. P. Cabrera, and P. Cordero. “Quasi-closed elements in fuzzy posets”. In: Journal of Computational and Applied Mathematics 404 (Apr. 2022), p. 113390. ISSN: 0377-0427. DOI: 10.1016/j.cam.2021.113390. URL: http://dx.doi.org/10.1016/j.cam.2021.113390.

[20] F. Pérez-Gámez, P. Cordero, M. Enciso, et al. “Computing the Mixed Concept Lattice”. In: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Springer International Publishing, 2022, p. 87–99. ISBN: 9783031089718. DOI: 10.1007/978-3-031-08971-8_8. URL: http://dx.doi.org/10.1007/978-3-031-08971-8_8.

[21] P. Raissa, S. Dias, M. Song, et al. “Minimal implications base for social network analysis”. In: International Journal of Web Information Systems 14.1 (Apr. 2018), p. 62–77. ISSN: 1744-0084. DOI: 10.1108/ijwis-04-2017-0028. URL: http://dx.doi.org/10.1108/ijwis-04-2017-0028.

[22] E. Rodríguez-Lorenzo, P. Cordero, M. Enciso, et al. “Canonical dichotomous direct bases”. In: Information Sciences 376 (Jan. 2017), p. 39–53. ISSN: 0020-0255. DOI: 10.1016/j.ins.2016.10.004. URL: http://dx.doi.org/10.1016/j.ins.2016.10.004.

[23] P. R. Silva, S. M. Dias, W. C. Brandão, et al. “Professional Competence Identification Through Formal Concept Analysis”. In: Enterprise Information Systems. Springer International Publishing, 2018, p. 34–56. ISBN: 9783319933757. DOI: 10.1007/978-3-319-93375-7_3. URL: http://dx.doi.org/10.1007/978-3-319-93375-7_3.

[24] S. S. Singh, S. Muhuri, S. Mishra, et al. “Social Network Analysis: A Survey on Process, Tools, and Application”. In: ACM Computing Surveys 56.8 (Apr. 2024), p. 1–39. ISSN: 1557-7341. DOI: 10.1145/3648470. URL: http://dx.doi.org/10.1145/3648470.

[25] Y. Zhou, J. Li, H. Yang, et al. “Knowledge structures construction and learning paths recommendation based on formal contexts”. In: International Journal of Machine Learning and Cybernetics 15.4 (Oct. 2023), p. 1605–1620. ISSN: 1868-808X. DOI: 10.1007/s13042-023-01985-5. URL: http://dx.doi.org/10.1007/s13042-023-01985-5.