Titlebook: Social Information Access; Systems and Technolo Peter Brusilovsky,Daqing He Book 2018 Springer International Publishing AG, part of Springe

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Rating-Based Collaborative Filtering: Algorithms and Evaluation,orative filtering recommender systems do this by finding patterns that are consistent across the ratings of other users. These patterns can be used on their own, or in conjunction with other forms of social information access to identify and recommend content that a user might like. This chapter rev

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Recommendations Based on Social Links,elated issues, as well as future directions for research. Among several kinds of social recommendations, this chapter focuses on recommendations, which are based on users’ .-. (i.e., explicit) social links and suggest items, rather than people of interest. The chapter starts by reviewing the needs f

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From Opinions to Recommendations,es of recommendation knowledge. More recently, new sources of recommendation knowledge in the form of social media information and other kinds of user-generated content have emerged as viable alternatives. For example, services such as Twitter, Facebook, Amazon and TripAdvisor provide a rich source

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Location Recommendation with Social Media Data,focus on recommender systems that use location data to help users navigate the physical world. We examine various recommendation problems: recommending new places, recommending the next place to visit, events to attend, and recommending neighbourhoods or large areas to explore further. Lastly, we di

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Introduction to Social Information Access, to support information access. These two factors are the angles we use in this chapter to create a map of the field, as well as to introduce the book structure and the role of the remaining book chapters in covering social information access topics and technologies.

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