A User's Guide to CARSKit
It offers a practical tool for researchers and practitioners working on context-aware recommendation, but it is incremental as it focuses on documentation and implementation rather than new methods.
The paper introduces CARSKit, a Java-based open-source library for context-aware recommender systems, providing a user guide for data preparation, configuration, and evaluation of implemented state-of-the-art algorithms.
Context-aware recommender systems extend traditional recommenders by adapting their suggestions to users' contextual situations. CARSKit is a Java-based open-source library specifically designed for the context-aware recommendation, where the state-of-the-art context-aware recommendation algorithms have been implemented. This report provides the basic user's guide to CARSKit, including how to prepare the data set, how to configure the experimental settings, and how to evaluate the algorithms, as well as interpreting the outputs. The instructions in this guide are applicable for CARSKit v0.3.5 and above.