New LebiD2 for Cold-Start

被引：0
|
作者：
Dali, Lebi Jean Marc [1 ]
Qin, Zhi-guang [1 ]
机构：
[1] Univ Elect Sci & Technol China, Dept Comp Sci & Engn, Chengdu, Sichuan, Peoples R China
来源：
CURRENT TRENDS IN COMPUTER SCIENCE AND MECHANICAL AUTOMATION, VOL 1 | 2017年
关键词：
Cold Start; Recommenders; model-based RS; Trust based algorithm; social network;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
As the Cold Start problem emerges as a serious bottleneck in the world of internet companies, it has become a priority to solve it efficiently. Previous techniques fail at addressing this problem. But in this paper, we present LebiD2 a hybrid Trust based technique which solves efficiently the Cold-Start. The secret of LebiD2 is that it doesn't need the active user history which is exactly the downfall of the other recommenders. In this paper, we explain our method in detail.
引用
收藏
页码：33 / 39
页数：7
相关论文
共 50 条
  • [21] Cold-start active learning for image classification
    Jin, Qiuye
    Yuan, Mingzhi
    Li, Shiman
    Wang, Haoran
    Wang, Manning
    Song, Zhijian
    INFORMATION SCIENCES, 2022, 616 : 16 - 36
  • [22] Graph Neural Patching for Cold-Start Recommendations
    Chen, Hao
    Yang, Yu
    Bei, Yuanchen
    Wang, Zefan
    Xu, Yue
    Ituang, Feiran
    DATABASES THEORY AND APPLICATIONS, ADC 2024, 2025, 15449 : 334 - 346
  • [23] Deep Pairwise Hashing for Cold-Start Recommendation
    Zhang, Yan
    Tsang, Ivor W.
    Yin, Hongzhi
    Yang, Guowu
    Lian, Defu
    Li, Jingjing
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2022, 34 (07) : 3169 - 3181
  • [24] Functional Matrix Factorizations for Cold-Start Recommendation
    Zhou, Ke
    Yang, Shuang-Hong
    Zha, Hongyuan
    PROCEEDINGS OF THE 34TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL (SIGIR'11), 2011, : 315 - 324
  • [25] Study of SCR cold-start by energy method
    Miao, Yong
    Chen, Lea-Der
    He, Yongsheng
    Kuo, Tang-wei
    CHEMICAL ENGINEERING JOURNAL, 2009, 155 (1-2) : 260 - 265
  • [26] Learning to Learn a Cold-start Sequential Recommender
    Huang, Xiaowen
    Sang, Jitao
    Yu, Jian
    Xu, Changsheng
    ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2022, 40 (02)
  • [27] Promoting Cold-Start Items in Recommender Systems
    Liu, Jin-Hu
    Zhou, Tao
    Zhang, Zi-Ke
    Yang, Zimo
    Liu, Chuang
    Li, Wei-Min
    PLOS ONE, 2014, 9 (12):
  • [28] Feature Matching Machine for Cold-Start Recommendation
    Wu, Hanrui
    Li, Nuosi
    Kwok, Ka Ho
    Cai, Xuheng
    Zhang, Jia
    Long, Jinyi
    Ng, Michael K.
    IEEE TRANSACTIONS ON SERVICES COMPUTING, 2024, 17 (01) : 98 - 112
  • [29] Cold-Start Recommendation for On-Demand Cinemas
    Li, Beibei
    Jin, Beihong
    Xue, Taofeng
    Liu, Kunchi
    Zhang, Qi
    Tian, Sihua
    MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2019, PT III, 2020, 11908 : 499 - 515
  • [30] MARec: Metadata Alignment for cold-start Recommendation
    Monteil, Julien
    Vaskovych, Volodymyr
    Lu, Wentao
    Majumder, Anirban
    van den Hengel, Anton
    PROCEEDINGS OF THE EIGHTEENTH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2024, 2024, : 401 - 410
12345