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Type of Publication: | Diploma thesis |
URI (citable link): | http://nbn-resolving.de/urn:nbn:de:bsz:352-0-259317 |
Author: | Weidele, Daniel |
Year of publication: | 2013 |
Summary: |
We review and categorize early approaches of collaborative filtering, before moving towards social-aware matrix factorization models for rating prediction, which we will theoretically compare to each other and to the state of the art model SVD++. We derive a generic social-aware factorization model and show how to improve runtime complexities of social-aware matrix factorization models in general. Moreover we discuss various trust metrics to exploit social network information and propose the application of PageRank as a new alternative in this context. Finally we provide a practical evaluation of presented approaches.
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Dissertation note: | Master thesis, Universität Konstanz |
Subject (DDC): | 004 Computer Science |
Link to License: | In Copyright |
Bibliography of Konstanz: | Yes |
WEIDELE, Daniel, 2013. Social-aware Matrix Factorization for Recommender Systems [Master thesis]. Konstanz: Universität Konstanz
@mastersthesis{Weidele2013Socia-29251, title={Social-aware Matrix Factorization for Recommender Systems}, year={2013}, address={Konstanz}, school={Universität Konstanz}, author={Weidele, Daniel} }
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Weidele_0-259317.pdf | 1820 |