Context-Aware recommender systems, aiming to further improve performance accuracy and user satisfaction by fully utilizing contextual information, have recently become one of the hottest topics in the domain of recommender systems. This paper presents an overview of the field of context-aware recommender systems from a process-oriented perspective, including system frameworks, key techniques, main models, evaluation, and typical applications. The prospects for future development and suggestions for possible extensions are also discussed.