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The Development of Movie Recommendation System with Graph Data Structure |
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| รหัสดีโอไอ | |
| Creator | Suchinthorn Songsittidet |
| Title | The Development of Movie Recommendation System with Graph Data Structure |
| Contributor | Nakorn Indra-Payoong |
| Publisher | Department of Information Science, Faculty of Humanities and Social Sciences, Khon Kaen University |
| Publication Year | 2566 |
| Journal Title | Journal of Information Science Research and Practice |
| Journal Vol. | 41 |
| Journal No. | 4 |
| Page no. | 93–107 |
| Keyword | Recommendation system, Graph data structure, Maximum spanning tree |
| URL Website | https://www.tci-thaijo.org/index.php/jiskku/index |
| Website title | Journal of Information Science Research and Practice |
| ISSN | 3027-6586 |
| Abstract | Purpose: The objective of this research is to design and evaluate the efficiency a movie recommendation process with graph data structure.Methodology: The MovieLens dataset contains 100,000 records on 1,682 movies from 943 users. There are two parts of the study 1) the recommendation based on movie preference ratings by K - mean clustering method and 2) the recommendation based on a spanning tree of maximum weights in graph data structure by user’s attributions.Findings: The recommendations for top – 10 movies based on movie preference ratings from 5 user groups by K – mean Clustering. The result has shown that the average recommendation accuracy is 28.16%. In addition to the recommendation for top-10 movies based on graph data structure from 111 user groups by user’s attributions, such as sex, age rage, and occupation found that the average recommendation accuracy is 87.45%.Applications of this study: The results indicated that the proposed maximum weight spanning tree in graph data structure can recommend movies to watching more efficiently. |
