采用在线评论的景点个性化推荐

Attractions Personalized Recommendations Using Online Reviews

通过对旅游网站的景点评论进行情感分析,综合利用自然语言处理技术和领域本体构建技术,准确把握游客对旅游目的地的满意度和需求;将群体智慧和个人偏好有效地结合,为游客出行制定合理的个性化推荐策略.实验结果表明:所提出的推荐策略能够有效地将碎片化的游客评论数据转化为对其他游客出行地选择的辅助信息,提高了游客获取旅游知识的效率,真实地反映游客的旅游感受,为游客景点选择提供参考.

Through analyzing attractions online reviews of travel sites based on sentiment analysis,this paper comprehensively utilizes natural language processing technology and domain ontology construction technology,accurately grasps the tourist satisfaction and the demand for tourism destination,effectively combines the wisdom of crowds and personal preference,and sets reasonable personalized recommendation for tourists travel strategy.The experimental results show that the proposed strategy can effectively translate fragmented visitors review data into ancillary information of tourists traveling,improve the efficiency of the tourists to obtain knowledge,truly reflect the tourists feel,and provide the reference for tourist choosing attractions.