{"id":215231,"date":"2010-05-01T00:00:00","date_gmt":"2010-05-01T00:00:00","guid":{"rendered":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/msr-research-item\/introduction-to-social-recommendation\/"},"modified":"2018-10-16T20:06:14","modified_gmt":"2018-10-17T03:06:14","slug":"introduction-to-social-recommendation","status":"publish","type":"msr-research-item","link":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/publication\/introduction-to-social-recommendation\/","title":{"rendered":"Introduction to Social Recommendation"},"content":{"rendered":"<div class=\"asset-content\">\n<p>As the exponential growth of information generated on the World Wide Web, Social Recommendation has emerged as one of the hot research topics recently. Social Recommendation forms a specific type of information filtering technique that attempts to suggest information (blogs, 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. on social behavior data collected from 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, we will introduce Social Recommendation and elaborate on how the various characteristics and aspects are involved in the social platforms for collective intelligence. Moreover, we will discuss the challenging issues involved in Social Recommendation in the context of theory and models of social networks, methods to improve recommender systems using social contextual information, ways to deal with partial and incomplete information in the social context, scalability and algorithmic issues with social computational techniques.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>As the exponential growth of information generated on the World Wide Web, Social Recommendation has emerged as one of the hot research topics recently. Social Recommendation forms a specific type of information filtering technique that attempts to suggest information (blogs, news, music, travel plans, web pages, images, tags, etc.) that are likely to interest the [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"ACM - Association for Computing Machinery","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"\u00a9 ACM. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. 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