Hybrid User Recommendation in Online Social Network

Social web and recommendation system has become an indispensable part of today’s e-world. In such environment, most of the communications and transactions happen with unfamiliar persons. Any communication with unfamiliar persons is problematic as it lacks trust. Thus trust is an important factor to integrate recommendation system with the social web. In current scenario recommendation of trustable individuals with the similarity in behavior or trusted products is what is essential. The work reported in his paper aims towards recommending a trustable similar individual. The current work proposes user-user recommendation methods. Since the proposed approach is a hybrid approach it uses content-based technique and collaborative technique for the recommendation. Similar users are identified using content-based technique with Formal Concept Analysis (FCA) and Jaccard index and trustable users are identified using collaborative based technique. The trusted similar users are recommended using decision tree algorithm. The recommendation provided by this hybrid system is evaluated for its accuracy.

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