A Novel Recommendation Method Based on User's Interest and Heterogeneous Information

被引:0
|
作者
Wang, Jiatong [1 ]
Fei, Zhenqian [1 ]
Qiao, Shuyu [1 ]
Sun, Wei [1 ]
Sun, Xiaoxin [1 ]
Zhang, BangZuo [1 ]
机构
[1] Northeast Normal Univ, Sch Comp Sci & Informat Technol, Changchun 130117, Peoples R China
关键词
Trust relationship; Heterogeneous information network; Recommender system;
D O I
10.1007/978-3-319-45835-9_8
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
It's a consensus that trust relationship is significant to improve the recommendation efficiently. But in most cases, trust relationship information is so sparse and difficult to use. Actually, the trust relationship is the response of interest among users, that is, it is an effective method to find the appropriate trust relationships by mining users' interests accurately. There are so many factors that can affect users' interest as well, such as age, occupation and so on. Based on these factors we can construct a heterogeneous information network, this paper deeply mine more accurate trust relationship through the interest and similarity from the heterogeneous information network among users, and merges the trust relationship to the matrix decomposition techniques. Moreover, we innovative conduct our experiment to test the recommendation algorithm based on trust, which has not been studied so far in MovieLens100k dataset. Experimental results demonstrate that our method outperforms other counterparts both in terms of accuracy.
引用
收藏
页码:90 / 101
页数:12
相关论文
共 50 条
  • [1] An Information Recommendation Method Based on User Interest Model
    Hu, Jia-Ting
    Li, Sheng
    [J]. FUZZY SYSTEM AND DATA MINING, 2016, 281 : 284 - 292
  • [2] Recommendation Method Study Based on User's Page Interest Degree
    Liu Weijiang
    Jiang Hongjie
    Wang Ying
    [J]. NINTH WUHAN INTERNATIONAL CONFERENCE ON E-BUSINESS, VOLS I-III, 2010, : 283 - 289
  • [3] A Web recommendation method based on user interest model
    Yang, Zhen-Gang
    Deng, Fei-Qi
    [J]. PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2006, : 4536 - +
  • [4] Extracting User Interest for User Recommendation Based on Folksonomy
    Saito, Junki
    Yukawa, Takashi
    [J]. IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2011, E94D (06) : 1329 - 1332
  • [5] An Unbiased User Model for Interest Diffusion in the Heterogeneous Network Recommendation
    Yin Fengjing
    Zhang Xin
    Zhang Xiaoyu
    [J]. ICEBT 2018: PROCEEDINGS OF THE 2018 2ND INTERNATIONAL CONFERENCE ON E-EDUCATION, E-BUSINESS AND E-TECHNOLOGY, 2018, : 138 - 144
  • [6] Design and Application of Multiattribute Tourist Information Recommendation Model Based on User Interest
    Lian, Jiangong
    Liang, Dan
    [J]. WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2022, 2022
  • [7] Personalized Scientific Literature Recommendation Based on User's Research Interest
    Guan, Peng
    Wang, Yuefen
    [J]. 2016 12TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD), 2016, : 1273 - 1277
  • [8] Research of Personalized Recommendation Algorithm Based on Trust and User's Interest
    Sun, PengChao
    Yin, ShiQun
    Man, Wan
    Tao, Tan
    [J]. 2018 INTERNATIONAL CONFERENCE ON ROBOTS & INTELLIGENT SYSTEM (ICRIS 2018), 2018, : 153 - 156
  • [9] A User Interest Recommendation Based on Collaborative Filtering
    Wu, Wenqi
    Wang, Jianfang
    Liu, Randong
    Gu, Zhenpeng
    Liu, Yongli
    [J]. PROCEEDINGS OF THE 2016 2ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INDUSTRIAL ENGINEERING (AIIE 2016), 2016, 133 : 524 - 528
  • [10] Mapping user interest into hyper-spherical space: A novel POI recommendation method
    Gan, Mingxin
    Ma, Yingxue
    [J]. INFORMATION PROCESSING & MANAGEMENT, 2023, 60 (02)