Recommender systems have been well recognized as a typical application of Big Data and Machine Learning. LibRec is a GPL-licensed Java library (Java version 1.7+ required), aiming to solve two classic tasks in recommender systems, i.e., rating prediction and item ranking by implementing a suite of state-of-the-art recommendation algorithms. It has been listed by the RecSys Wiki (see the LibRec page).
|Guibing Guo, Jie Zhang, Zhu Sun and Neil Yorke-Smith, LibRec: A Java Library for Recommender Systems, in Posters, Demos, Late-breaking Results and Workshop Proceedings of the 23rd Conference on User Modelling, Adaptation and Personalization (UMAP), 2015.|
|G. Guo, J. Zhang and N. Yorke-Smith, TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings, in Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2015, 123-129.|
|G. Guo, J. Zhang and N. Yorke-Smith, A Novel Recommendation Model Regularized with User Trust and Item Ratings, IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(7), 1607-1620, 2016.|