摘要
在基于知识的推荐系统中,用户的个性化需求需要通过交互引导得出。为了提高用户的交互体验,建立了基于有限状态机(FSM)的用户交互模型。根据所推荐物品的特征建立用户交互行为的有限状态机模型,通过求解有限状态机模型的有效路径,生成用户的个性化需求和偏好。该模型通过会话式的交互方式,根据用户的个体特征,提供有效交互,减少了用户交互负担,提高了推荐结果的信任度、满意度。
In knowledge-based recommender system, make use of the interaction to elicit user＇s personalized requirements and preferences, in order to improve the experience of interact with users, a user interaction model based on finite state machine was established. According to the features of the recommended items, we established a user interaction model based on finite state machine. Through get the effective path of the finite state machine model, generate the user＇s person- alized requirements and preferences. According to the user＇s individual characteristics, this model can show effective interaction questions by the conversational interactive approach, and reduce their interaction burden. At the aspect of trust, satisfaction, and quality of the recommended results, this model can reached higher user perception.
出处
《软件导刊》
2015年第3期15-17,共3页
Software Guide
关键词
推荐系统
有限状态机
用户交互
Recommender System
finite state machine
user interaction
