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IIR
2010
13 years 9 months ago
Context-Dependent Recommendations with Items Splitting
Recommender systems are intelligent applications that help on-line users to tackle information overload by providing recommendations of relevant items. Collaborative Filtering (CF...
Linas Baltrunas, Francesco Ricci
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 8 months ago
Modeling relationships at multiple scales to improve accuracy of large recommender systems
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Robert M. Bell, Yehuda Koren, Chris Volinsky
ATAL
2007
Springer
13 years 11 months ago
Strategy recommender agents (ALEX) - the methodology
Agents for Alignment into strategy Experience (ALEX agents), a type of recommender agent (RA), are proposed here as a means of helping employees to perform tasks in line with the ...
Ronald Uriel Ruiz Ordóñez, Josep Llu...
WWW
2003
ACM
14 years 8 months ago
An Effective Complete-Web Recommender System
There are a number of recommendation systems that can suggest the webpages, within a single website, that other (purportedly similar) users have visited. By contrast, our goal is ...
Gerald Häubl, Russell Greiner, Tingshao Zhu
EDM
2009
114views Data Mining» more  EDM 2009»
13 years 5 months ago
Edu-mining for Book Recommendation for Pupils
This paper proposes a novel method for recommending books to pupils based on a framework called Edu-mining. One of the properties of the proposed method is that it uses only loan h...
Ryo Nagata, Keigo Takeda, Koji Suda, Jun'ichi Kake...