期刊論文
| 學年 | 108 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2020-04-01 |
| 作品名稱 | A collaborative filtering recommendation system with dynamic time decay |
| 作品名稱（其他語言） | |
| 著者 | Yi-Cheng Chen; Lin Hui; Tipajin Thaipisutikul |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | The Journal of Supercomputing 77(1), p.244–262 |
| 摘要 | The collaborative filtering (CF) technique has been widely utilized in recommendation systems due to the precise prediction of users' interests. Most prior CF methods adapted overall ratings to make predictions by collecting preference information from other users. However, in real applications, people’s preferences usually vary with time; the traditional CF could not properly reveal the change in users’ interests. In this paper, we propose a novel CF-based recommendation, dynamic decay collaborative filtering (DDCF), which captures the preference variations of users and includes the concept of dynamic time decay. We extend the idea of human brain memory to specify the level of a user’s interests (i.e., instantaneous, short-term, or long-term). According to different interest levels, DDCF dynamically tunes the decay function based on users’ behaviors. The experimental results show that DDCF with the integration of the dynamic decay concept performs better than traditional CF. In addition, we conduct experiments on real-world datasets to demonstrate the practicability of the proposed DDCF. |
| 關鍵字 | Collaborative filtering;Decay function;Human brain memory;Recommendation system |
| 語言 | en |
| ISSN | 1573-0484 |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 是 |
| 國別 | NLD |
| 公開徵稿 | |
| 出版型式 | ,電子版,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/120159 ) |