Clustering item for better recommendation quality
碩士 === 國立臺灣大學 === 資訊網路與多媒體研究所 === 107 === Recommendation system begin very popular in recent years and are adopted in many fields, such as movies, musics, and E-commerce items. We choose food items for our recommendation items. The biggest challenge of food recommendation is the sparsity of any food...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2019
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| Online Access: | http://ndltd.ncl.edu.tw/handle/u5xufn |