Using Costumer Behavior to Build Social Network Based on Mole-Algorithm
Saba M. Hussain1, Ghaidaa A. Al-Sultany2
1Saba M. Hussain, University of Babylon, Department of Information Network, College of Information Technology, Babil, Iraq.
2Ghaidaa A. Al-Sultany University of Babylon, Department of Information Network, College of Information Technology, Babil, Iraq.
Manuscript received on November 11, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on 30 November, 2019. | PP: 4324-4328 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8156118419/2019©BEIESP | DOI: 10.35940/ijrte.D8156.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The modern technology has great interring on building relationships between users on social networking. Therefore, it is possible to promote goods, advertisements and rumors among people easily. A trust network is created for each member. With this model, Members are represented as nodes in the graph, and trust relationships are represented between members according to the directed edges.This approach is based on the premise the neighbors with higher trust ratings are likely to agree with each other about the trustworthiness.The question here is: how can trust networks be built between users? This work proposed to build a social network based on the Mole algorithm. The user’s behavior is extracted to be use instead of user’s rates in the original mole algorithm. The outcomes of this method were of a higher satisfactory level and a remarkably increased accuracy value by 15% over traditional Mole algorithm.
Keywords: Social Network, Mole Trust, Recommender System, Data mining.
Scope of the Article: Data Mining.