Algorithm Research of Individualized Travelling Route Recommendation Based on Similarity
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...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2015-01-01
|
| Series: | MATEC Web of Conferences |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1051/matecconf/20152201013 |
| _version_ | 1818615683955556352 |
|---|---|
| author | Xue Shan Liu Song |
| author_facet | Xue Shan Liu Song |
| author_sort | Xue Shan |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-16T16:37:49Z |
| format | Article |
| id | doaj.art-daef9164a8c045c6a5ae9f8580caa627 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-16T16:37:49Z |
| publishDate | 2015-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-daef9164a8c045c6a5ae9f8580caa6272022-12-21T22:24:25ZengEDP SciencesMATEC Web of Conferences2261-236X2015-01-01220101310.1051/matecconf/20152201013matecconf_iceta2015_01013Algorithm Research of Individualized Travelling Route Recommendation Based on SimilarityXue Shan0Liu Song1Qingdao Vocational and Technical College of Hotel ManagementQingdao Technological UniversityAlthough 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.http://dx.doi.org/10.1051/matecconf/20152201013collaborative filteringmulti-similarityelement similaritytrust degreefraction of coverageaccumulated gain in normalization depreciation |
| spellingShingle | Xue Shan Liu Song Algorithm Research of Individualized Travelling Route Recommendation Based on Similarity MATEC Web of Conferences collaborative filtering multi-similarity element similarity trust degree fraction of coverage accumulated gain in normalization depreciation |
| title | Algorithm Research of Individualized Travelling Route Recommendation Based on Similarity |
| title_full | Algorithm Research of Individualized Travelling Route Recommendation Based on Similarity |
| title_fullStr | Algorithm Research of Individualized Travelling Route Recommendation Based on Similarity |
| title_full_unstemmed | Algorithm Research of Individualized Travelling Route Recommendation Based on Similarity |
| title_short | Algorithm Research of Individualized Travelling Route Recommendation Based on Similarity |
| title_sort | algorithm research of individualized travelling route recommendation based on similarity |
| topic | collaborative filtering multi-similarity element similarity trust degree fraction of coverage accumulated gain in normalization depreciation |
| url | http://dx.doi.org/10.1051/matecconf/20152201013 |
| work_keys_str_mv | AT xueshan algorithmresearchofindividualizedtravellingrouterecommendationbasedonsimilarity AT liusong algorithmresearchofindividualizedtravellingrouterecommendationbasedonsimilarity |