Provenance based Trust computation for Recommendation in Social Network

User Recommendation in OSN

“…The proposed research work uses frequency pattern among various type of user behavior patterns described by Park DHet al [16]. Trust value (user rating) could be predicted using stochastic model once the latent features are identified [15] [18].The process of trust prediction as proposed by Christiyana et al [2] and user recommendation for the proposed work is explained below: 1) Compute the prime user's reputation on another user x based on prime user's interaction using stochastic differential equation. 2) Compute trust from the reputation value, which defines the closeness of prime user with user x.…”

“…Hence, the proposed strategy employs reputation-based user believe framework to identify and recommend the prospective user to the requested. Sample trust value obtained using stochastic model and Bayesian classification process by Christiyana et al [2] isgiven in Table 1.…”

“…These parameters are extracted from individual user's timeline and chat sessions in FaceBook. Values of these parameters are computed using stochastic model proposed by Christiyana et al [2]. The field named 'Class' in Table 1 defined the accepted (A) and refused (R) labels as trusted and untrusted users respectively.…”

“…The corresponding output were classified using Bayesian classier with 96.7% accuracy. The precision test of the classifier showed that 96.7 percent of trusted users classified are reliable [2].The recommendation system thus built using stochastic and Bayesian classification is evaluated for its effectiveness as in section 5.…”

“…The recommendation in OSN could beuser -itemsrecommendation and user-user recommendation. In user based community users are prone to have the thread enforced by the imposters in order to abuse the users Anticipating and eradicating such imposters is the requisite for the virtual environments like OSN [2]. In addition to the eradication of the imposters, suggesting trustworthy user will protect and enhance the wellbeing of the communityIn user based community users are prone to have the threat enforced by the imposters in order to abuse the users.Anticipating and eradicating such imposters is the requisite for the virtual environments like OSN [2].…”