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International Journal of Neutrosophic Science
Volume 18 , Issue 2, PP: 186-198 , 2022 | Cite this article as | XML | Html |PDF

Title

Network user interest mining method based on Neutrosophic cluster analysis

  Abedallah Zaid Abualkishik 1 * ,   Anqi Li 2

1  American University in the Emirates, UAE
    (abedallah.abualkishik@aue.ae)

2  Tianjin University of Commerce, China
    (lianqi@tjcu.edu.cn)


Doi   :   https://doi.org/10.54216/IJNS.180203

Received: November 10, 2021 Accepted: March 04, 2022

Abstract :

These days’ user interests have become more critical for companies and firms to introduce their content due to the growth in networks and the internet. So this method used neutrosophic sets for network user interest. In this paper, we proposed five main criteria and seventeen sub-criteria to show user interest in the network. The multi-criteria decision-making (MCDM) method is used to deal with various criteria and sub-criteria. So the Analytical Hierarchal Process (AHP) is used to show weights of criteria and sub-criteria to present the user interest in the network. An illustrative example provides to show calculations of the proposed method.

Keywords :

AHP , Neutrosophic , Network , Mining , User Interest , Cluster algorithm

References :

[1]         C. Xu, S. Chen, and J. Cheng, “Network user interest pattern mining based on entropy clustering algorithm,” in 2015 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, 2015, pp. 200–204.

[2]         Y.-H. Wu, Y.-C. Chen, and A. L. P. Chen, “Enabling personalized recommendation on the web based on user interests and behaviors,” in Proceedings Eleventh International Workshop on Research Issues in Data Engineering. Document Management for Data Intensive Business and Scientific Applications. RIDE 2001, 2001, pp. 17–24.

[3]         R. Yan, “Researches on hybrid algorithm for moving target detection and tracking in sports video,” Cluster Comput., vol. 22, no. 2, pp. 3543–3552, 2019.

[4]         F. Gasparetti, “Modeling user interests from web browsing activities,” Data Min. Knowl. Discov., vol. 31, no. 2, pp. 502–547, 2017.

[5]         H.-L. Kim, J. G. Breslin, S. Decker, and H.-G. Kim, “Mining and representing user interests: The case of tagging practices,” IEEE Trans. Syst. Man, Cybern. A Syst. Humans, vol. 41, no. 4, pp. 683–692, 2011.

[6]         M. Wallace and G. Stamou, “Towards a context aware mining of user interests for consumption of multimedia documents,” in Proceedings. IEEE International Conference on Multimedia and Expo, 2002, vol. 1, pp. 733–736.

[7]         L. Limam, D. Coquil, H. Kosch, and L. Brunie, “Extracting user interests from search query logs: A clustering approach,” in 2010 Workshops on Database and Expert Systems Applications, 2010, pp. 5–9.

[8]         S. Volkova, Y. Bachrach, and B. Van Durme, “Mining user interests to predict perceived psycho-demographic traits on twitter,” in 2016 IEEE Second International Conference on Big Data Computing Service and Applications (BigDataService), 2016, pp. 36–43.

[9]         T. Wang, H. Liu, J. He, and X. Du, “Mining user interests from information sharing behaviors in social media,” in Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2013, pp. 85–98.

[10]       D.-Y. Chang, “Applications of the extent analysis method on fuzzy AHP,” Eur. J. Oper. Res., vol. 95, no. 3, pp. 649–655, 1996.

[11]       C. Kahraman, U. Cebeci, and Z. Ulukan, “Multiā€criteria supplier selection using fuzzy AHP,” Logist. Inf. Manag., 2003.

[12]       M. C. Y. Tam and V. M. R. Tummala, “An application of the AHP in vendor selection of a telecommunications system,” Omega, vol. 29, no. 2, pp. 171–182, 2001.

[13]       T. L. Saaty, “Decision-making with the AHP: Why is the principal eigenvector necessary,” Eur. J. Oper. Res., vol. 145, no. 1, pp. 85–91, 2003.

[14]       K. M. A.-S. Al-Harbi, “Application of the AHP in project management,” Int. J. Proj. Manag., vol. 19, no. 1, pp. 19–27, 2001.

[15]       L. Jin, C. Zhang, X. Wen, C. Sun, and X. Fei, “A neutrosophic set-based TLBO algorithm for the flexible job-shop scheduling problem with routing flexibility and uncertain processing times,” Complex Intell. Syst., pp. 1–21, 2021.

[16]       A. Chakraborty, S. P. Mondal, A. Ahmadian, N. Senu, S. Alam, and S. Salahshour, “Different forms of triangular neutrosophic numbers, de-neutrosophication techniques, and their applications,” Symmetry (Basel)., vol. 10, no. 8, p. 327, 2018.

[17]       S. Alkhazaleh, “Time-neutrosophic soft set and its applications,” J. Intell. Fuzzy Syst., vol. 30, no. 2, pp. 1087–1098, 2016.


Cite this Article as :
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MLA Abedallah Zaid Abualkishik , Anqi Li. "Network user interest mining method based on Neutrosophic cluster analysis." International Journal of Neutrosophic Science, Vol. 18, No. 2, 2022 ,PP. 186-198 (Doi   :  https://doi.org/10.54216/IJNS.180203)
APA Abedallah Zaid Abualkishik , Anqi Li. (2022). Network user interest mining method based on Neutrosophic cluster analysis. Journal of International Journal of Neutrosophic Science, 18 ( 2 ), 186-198 (Doi   :  https://doi.org/10.54216/IJNS.180203)
Chicago Abedallah Zaid Abualkishik , Anqi Li. "Network user interest mining method based on Neutrosophic cluster analysis." Journal of International Journal of Neutrosophic Science, 18 no. 2 (2022): 186-198 (Doi   :  https://doi.org/10.54216/IJNS.180203)
Harvard Abedallah Zaid Abualkishik , Anqi Li. (2022). Network user interest mining method based on Neutrosophic cluster analysis. Journal of International Journal of Neutrosophic Science, 18 ( 2 ), 186-198 (Doi   :  https://doi.org/10.54216/IJNS.180203)
Vancouver Abedallah Zaid Abualkishik , Anqi Li. Network user interest mining method based on Neutrosophic cluster analysis. Journal of International Journal of Neutrosophic Science, (2022); 18 ( 2 ): 186-198 (Doi   :  https://doi.org/10.54216/IJNS.180203)
IEEE Abedallah Zaid Abualkishik, Anqi Li, Network user interest mining method based on Neutrosophic cluster analysis, Journal of International Journal of Neutrosophic Science, Vol. 18 , No. 2 , (2022) : 186-198 (Doi   :  https://doi.org/10.54216/IJNS.180203)