Author : Ajin Brabasher A 1
Date of Publication :7th April 2016
Abstract: Social recommendation forms a specific type of information filtering technique that attempts to suggest information (blog, news, music, travel plans, web pages, images, tags, etc.) that are likely to interest the users.Social recommendation involves the investigation of collective intelligence by using computational techniques such as machine learning, data mining, natural language processing, etc. Social behavior data collected from the blogs, wikis, recommender systems, question & answer communities, query logs, tags, etc. from areas such as social networks, social search, social media, social bookmarks, social news, social knowledge sharing, and social games. In this tutorial, it will introduce collaborative filtering (CF) techniques, social recommendation and hybrid random walk (HRW) method.The social recommendation system is conducted according to the messages and social structure of target users. The similarity of the discovered features of users and products will then be calculated as the essence of the recommendation engine. A case study will be included to present how the recommendation system works based on real data.
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