Context-Aware Strategies For Recommender System On A Professional SNS Platform

Abstract—The importance of recommender system on Social Network Services (SNS) platform has been recognized by researchers and practitioners in many disciplines, including e-commerce, information retrieval, social computing, data mining, marketing, etc. While a substantial amount of approaches focus on recommending the most relevant items to users on mainstream SNS platforms, there is still a lack of closer investigation into the context-aware strategies on professional SNS platform whose contextual information varies significantly from generic SNS platforms. Drawing upon existing algorithmic paradigms –content-based methods and collaborative filtering, this paper proposes context-aware strategies that cope with the need to recommend both users and items on a professional SNS platform. A case study has been demonstrated based on such approach and directions for future research have been discussed. Keywords-recommender system; social network; collaborative filtering; collective intelligence; professional SNS platform I