Abstract
This chapter describes a set of recommender systems for both people and content within the enterprise that were all built based on a rich aggregation model. The underlying infrastructure is based on a complex relationship model among three core entities: people, items, and tags. We describe the general model and the different recommender systems that were built on top, including the main results and the implications from one system to another. We conclude by highlighting the main findings and suggesting next steps and future directions.
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Guy, I. (2012). Social Recommendation Based on a Rich Aggregation Model. In: Recommender Systems for the Social Web. Intelligent Systems Reference Library, vol 32. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25694-3_6
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DOI: https://doi.org/10.1007/978-3-642-25694-3_6
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