A Survey on Multi-objective Recommender Systems
Dietmar Jannach and Himan Abdollahpouri
Driven by applications in clinical medicine and business, we address the problem of modeling trajectories over multiple states. We build on well-known methods from survival analysis and introduce a family of sequence models based on localized Bayesian Markov chains. We develop inference and prediction algorithms, and we apply the model to real-world data, demonstrating favorable empirical results. Our approach provides a practical and effective alternative to plain Markov chains and to existing (finite) mixture models; It retains the simplicity and computational benefits of the former while matching or exceeding the predictive performance of the latter.
Dietmar Jannach and Himan Abdollahpouri
Athanasios Vlontzos, Bernhard Kainz, Ciarán M. Gilligan-Lee
Yu Liang, Aditya Ponnada, Paul Lamere, Nediyana Daskalova