Paper-Conference

The Magic Barrier of Recommender Systems – No Magic, Just Ratings
Recommender Systems need to deal with different types of users who represent their preferences in various ways. This difference in user …
Alejandro Bellogín, Alan Said, Arjen P. De Vries
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User-Item Reciprocity in Recommender Systems: Incentivizing the Crowd
Alan Said, Martha Larson, Domonkos Tikk, Paolo Cremonesi, Alexandros Karatzoglou, Frank Hopfgartner, Roberto Turrin, Joost Geurts
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WrapRec: An easy extension of recommender system libraries
WrapRec is an easy-to-use Recommender Systems toolkit which allows users to easily implement or wrap recommen- dation algorithms from …
B. Loni, Alan Said
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You are What You Eat! Tracking Health Through Recipe Interactions.
On today’s World Wide Web, social recommender systems have become a commodity regardless of application domain. Even tangible items …
Alan Said, Alejandro Bellogín
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A month in the life of a production news recommender system
During the last decade, recommender systems have become a ubiquitous feature in the online world. Research on systems and algorithms in …
Alan Said, Jimmy Lin, Alejandro Bellogín, Arjen De Vries
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A Top-N Recommender System Evaluation Protocol Inspired by Deployed Systems
The evaluation of recommender systems is crucial for their development. In today’s recommendation landscape there are many …
Alan Said, Alejandro Bellogín Kouki, Arjen De Vries
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Activating the Crowd: Exploiting User-Item Reciprocity for Recommendation
Recommender systems have always faced the problem of sparse data. In the current era, however, with its demand for highly personalized, …
Martha Larson, Alan Said, Yue Shi, Paolo Cremonesi, Domonkos Tikk, Alexandros Karatzoglou, Linas Baltrunas, Jozef Geurts, Xavi Anguera, Frank Hopfgartner
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Workshop on reproducibility and replication in recommender systems evaluation
Experiment replication and reproduction are key requirements for empirical research methodology, and an important open issue in the …
Alejandro Bellogin, Pablo Castells, Alan Said, Domonkos Tikk
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Workshop on benchmarking adaptive retrieval and recommender systems
Evaluating adaptive and personalized information retrieval tech-niques is known to be a difficult endeavor. The rapid evolution of …
Pablo Castells, Frank Hopfgartner, Alan Said, Mounia Lalmas
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User-centric evaluation of a K-furthest neighbor collaborative filtering recommender
Collaborative filtering recommender systems often use nearest neighbor methods to identify candidate items. In this paper we present an …
Alan Said, Ben Fields, Brijnesh J. Jain, Sahin Albayrak
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