Abstract: The numerous activities related to e-commerce are carried out in social networks, in which trust plays an important role in decision making of customers. Suggestion by a friend is a common service that has been provided by almost all of the social networks, and evaluation of trust between users improves the quality of suggestions. Social networks have become the main infrastructure of today’s daily activities of people during the last decade. In these networks, users interact with each other, share their interests on resources and present their opinions about these resources or spread their information. Since each user has a limited knowledge of other users and most of them are anonymous, the trust factor plays an important role on recognizing a suitable product or specific user. The inference mechanism of trust in social media refers to utilizing available information of a specific user who intends to contact an unknown user. Next, fuzzy logic is incorporated to rank the membership of trust to a specific class, according to two-, three- and five-classes classification. Finally, to classify the trust values of users, three machine learning techniques, namely Linear Regression, Decision Tree (DT), and Random forest, are used instead of traditional weighted sum methods, to express the trust between any two users in the presence of a special pattern.
Keywords: Data mining, Pre processing, Transformation, Data Mining.
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DOI:
10.17148/IJARCCE.2021.10733
