Algorithm Research of Individualized Travelling Route Recommendation Based on Similarity
1 Qingdao Vocational and Technical College of Hotel Management, Qingdao, Shandong, China
2 Qingdao Technological University, Qingdao, Shandong, China
Although commercial recommendation system has made certain achievement in travelling route development, the recommendation system is facing a series of challenges because of people’s increasing interest in travelling. It is obvious that the core content of the recommendation system is recommendation algorithm. The advantages of recommendation algorithm can bring great effect to the recommendation system. Based on this, this paper applies traditional collaborative filtering algorithm for analysis. Besides, illustrating the deficiencies of the algorithm, such as the rating unicity and rating matrix sparsity, this paper proposes an improved algorithm combing the multi-similarity algorithm based on user and the element similarity algorithm based on user, so as to compensate for the deficiencies that traditional algorithm has within a controllable range. Experimental results have shown that the improved algorithm has obvious advantages in comparison with the traditional one. The improved algorithm has obvious effect on remedying the rating matrix sparsity and rating unicity.
Key words: collaborative filtering / multi-similarity / element similarity / trust degree / fraction of coverage / accumulated gain in normalization depreciation
© Owned by the authors, published by EDP Sciences, 2015
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