一种上下文感知的旅游信息服务推荐方法

在旅游时游客很难预先知道自己的旅游需求,并且旅游偏好在旅游过程中也会发生变化.为了给游客提供即时高效的个性化信息服务,本文将上下文信息引入推荐系统,结合案例推理和神经网络,根据游客的喜好为用户提供个性化信息服务推荐.实验表明,该方法可较好克服推荐系统新用户冷启动的问题,提高旅游信息服务的准确率和提升游客服务的满意度.

A Context Aware Tourism Information Service Recommendation Method

It is difficult for tourists to know their tourism needs in advance,and their tourism preferences may change in the process of tourism.In order to provide tourists with instant and efficient personalized information services,this paper studies the introduction of context information into the recommendation system.By combining case-based reasoning and neural network,personalized information service recommendation can be provided for users according to tourists'preferences.Experiments show that this method can better overcome the cold start problem of new users of the recommendation system,improve the accuracy of tourism information service and improve the satisfaction of tourist service.