Applying Second-Degree Neighborhood to Alleviate the Sparsity Problem in Collaborative Filtering
碩士 === 國立交通大學 === 資訊管理研究所 === 92 === Recommender systems have become dominant to reduce information overload and customize information access. The most successful recommender systems is collaborative filtering, which considers preferences of other users sharing similar interests. A major problem of...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2004
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| Online Access: | http://ndltd.ncl.edu.tw/handle/93490971127788898651 |