| 查看: 1942 | 回复: 5 | |||
perry_zhang新虫 (正式写手)
|
[求助]
论文是否已被检索求助！ 已有2人参与
|
|
本人新发表了几篇SCI论文，烦请帮忙查看一下是否已被SCI检索，谢谢！ [1] Zhipeng Zhang, Yasuo Kudo, Tetsuya Murai, Yonggong Ren. Improved covering-based collaborative filtering for new users’ personalized recommendations[J]. Knowledge and Information Systems, 2020, 62: 3133–3154. [2] Zhipeng Zhang, Yao Zhang, Yonggong Ren. Employing neighborhood reduction for alleviating sparsity and cold start problems in user-based collaborative filtering[J]. Information Retrieval Journal, 2020, 23: 449–472. [3] Zhipeng Zhang, Yasuo Kudo, Tetsuya Murai, Yonggong Ren. Addressing completed new item cold-start recommendation: A niche item-based collaborative filtering via interrelationship mining[J]. Applied Sciences-Basel, 2019, 9, 1894. [4] Zhipeng Zhang, Yasuo Kudo, Tetsuya Murai, Yonggong Ren. Enhancing recommendation accuracy of item-based collaborative filtering via item-variance weighting[J]. Applied Sciences-Basel, 2019, 9, 1928. |
回复此楼» 猜你喜欢
085600 英一数二272求调剂
已经有47人回复
-
材料328求调剂
已经有6人回复
-
085600材料与化工（高分子）290分求调剂
已经有3人回复
-
325求调剂
已经有4人回复
-
320材料与化工，求调剂
已经有4人回复
-
一志愿314求调剂
已经有5人回复
-
求调剂
已经有4人回复
-
347求调剂
已经有4人回复
-
一志愿西交大材料学硕 346 求调剂
已经有3人回复
-
304分材料专硕求调剂
已经有8人回复
knight7120
铁杆木虫 (正式写手)
- 应助: 1 (幼儿园)
- 金币: 5984.1
- 散金: 44
- 红花: 2
- 帖子: 452
- 在线: 190.9小时
- 虫号: 616065
- 注册: 2008-10-03
- 性别: GG
- 专业: 民族药学
2楼2020-09-13 21:49:45
3楼2020-09-13 21:53:43
4楼2020-09-13 23:00:20
bobvan
至尊木虫 (文坛精英)
- SEPI: 1
- 应助: 4791 (副教授)
- 金币: 32436.7
- 散金: 20775
- 红花: 351
- 帖子: 11187
- 在线: 1516.7小时
- 虫号: 2171443
- 注册: 2012-12-07
- 专业: 催化化学
【答案】应助回帖
★ ★ ★ ★ ★ ★ ★ ★ ★ ★
感谢参与，应助指数 +1
perry_zhang: 金币+10, ★★★★★最佳答案 2020-09-14 06:57:28
感谢参与，应助指数 +1
perry_zhang: 金币+10, ★★★★★最佳答案 2020-09-14 06:57:28
|
1) Improved covering-based collaborative filtering for new users’ personalized recommendations 入藏号: WOS:000544063400008 2) Employing neighborhood reduction for alleviating sparsity and cold start problems in user-based collaborative filtering 入藏号: WOS:000541331600001 3) Addressing complete new item cold-start recommendation: A niche item-based collaborative filtering via interrelationship mining 入藏号: WOS:000469756000173 4) Enhancing recommendation accuracy of item-based collaborative filtering via item-variance weighting 入藏号: WOS:000469756000207 |
5楼2020-09-14 00:43:13
|
恭喜！恭喜！ 发自小木虫Android客户端 |
6楼2020-09-14 00:46:08
5