A User's Guide to CARSKit

TL;DR

CARSKit is an open-source Java library that implements state-of-the-art context-aware recommendation algorithms, providing users with tools to prepare data, configure experiments, and evaluate recommendations effectively.

Contribution

This paper introduces CARSKit, a comprehensive toolkit for context-aware recommendation, including implementation details and user guidance for effective use.

Findings

Provides a detailed user guide for CARSKit v0.3.5+

Includes implementation of state-of-the-art algorithms

Facilitates data preparation and evaluation processes

Abstract

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.