Personalized Recommendation for Traveling Planning Based on Online Word-of-mouth

Abstract

Abstract:

With the rapid development of internet, it provides more information and services for users. Traditional methods for scenic spot and traveling routes are not fit for mobile network because of plenteous content. This paper proposes a personalized recommendation method for traveling planning based on online word-of-mouth. In the proposed method, a users' matching model is suggested for finding the similarities between users' demand and traveling planning. Second, a dynamic user's opinion-based web mining model is offered to mine online word-of-mouth. Finally, an integrated model is proposed for combining users' demand matching and opinions. To verify the efficiency of the proposed method, a demo for traveling recommendation is developed and a survey is carried out for method evaluation. The empirical results show that the performance of the proposed method outperforms ones of traditional methods, and the proposed method has better users' experiences. Our paper provides an alternative and efficient method for traveling recommendation.

Key words: traveling planning, intelligent recommendation, users'demand, users'opinion, mobile network

Li Qian, Xu Wei, Jiang Hongxun. Personalized Recommendation for Traveling Planning Based on Online Word-of-mouth[J]. , 2016, 28(6): 113-118.

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