FSBPR: a novel approach to improving BPR for recommendation with the fusion of similarity

被引:0
|
作者
Zheng, Jianchang [1 ]
Wang, Hongjuan [2 ]
机构
[1] Beijing Inst Graph Commun, Sch Informat Engn, Beijing, Peoples R China
[2] Beijing Inst Graph Commun, Sch New Media, Beijing, Peoples R China
来源
JOURNAL OF SUPERCOMPUTING | 2024年 / 80卷 / 09期
基金
北京市自然科学基金;
关键词
Recommender systems; One-class collaborative filtering; Bayesian personalized ranking; Potential feedback; BAYESIAN PERSONALIZED RANKING; IMPLICIT FEEDBACK;
D O I
10.1007/s11227-024-05911-6
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
As an essential part of big data, the recommendation system is widely used because of its practicability. Most of the traditional rating prediction algorithms mainly focus on explicit feedback, but this type of data is usually sparse in the real world. By contrast, the Bayesian Personalized Ranking (BPR) algorithm could directly optimize for ranking and provide personalized recommendation from implicit feedback. The BPR is a well-known pairwise method for one-class collaborative filtering, it proposed two assumptions: (1) it assumes all the unrated items are negative items for each user; and (2) it assumes user prefer rated items to unrated items. However, the assumptions in BPR may not always hold in reality. That is because for the unrated items, a user may have different view, such as potentially like or dislike. To mitigate the above-mentioned problems, we propose a novel approach to improving BPR for recommendation with the fusion of similarity, termed as FSBPR for brevity. We first fuse the predefined similarity and the learned similarity method to calculate the similarity between items, and then find the items that users may be interested in through the number of item occurrence. To this end, we divide the items into three sets for each user and provide the pairwise preference assumption. We also extend the idea of the CoFiSet model to our model and provide a series pairwise assumption. The model parameters are learned by the stochastic gradient descent. We conduct experiments on three real-world datasets to verify the accuracy of FSBPR, and compare FSBPR with the state-of-the-art methods. The experimental results indicate that our model significantly improves the accuracy of the recommendation.
引用
收藏
页码:12003 / 12020
页数:18
相关论文
共 50 条
  • [31] A novel similarity based quality metric for image fusion
    Li, Shanshan
    Hong, Richang
    Wu, Xiuqing
    2008 INTERNATIONAL CONFERENCE ON AUDIO, LANGUAGE AND IMAGE PROCESSING, VOLS 1 AND 2, PROCEEDINGS, 2008, : 167 - 172
  • [32] A novel approach for measuring hyperspectral similarity
    Galal, Abdulrahman
    Hassan, Hesham
    Imam, Ibrahim F.
    APPLIED SOFT COMPUTING, 2012, 12 (10) : 3115 - 3123
  • [33] A NOVEL-APPROACH TO MOLECULAR SIMILARITY
    COOPER, DL
    ALLAN, NL
    JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN, 1989, 3 (03) : 253 - 259
  • [34] Improving Academic Event Recommendation Using Research Similarity and Interaction Strength Between Authors
    Dinh Tuyen Hoang
    Van Cuong Tran
    Van Du Nguyen
    Ngoc Thanh Nguyen
    Hwang, Dosam
    CYBERNETICS AND SYSTEMS, 2017, 48 (03) : 210 - 230
  • [35] A Novel Personalized Dynamic Route Recommendation Approach Based on Pearson Similarity Coefficient in Cooperative Vehicle-Infrastructure Systems
    Shan, Danlei
    Zhou, Wenjuan
    Wang, Jianqiang
    2018 IEEE 8TH ANNUAL INTERNATIONAL CONFERENCE ON CYBER TECHNOLOGY IN AUTOMATION, CONTROL, AND INTELLIGENT SYSTEMS (IEEE-CYBER), 2018, : 1270 - 1275
  • [36] Improving chemical similarity ensemble approach in target prediction
    Zhonghua Wang
    Lu Liang
    Zheng Yin
    Jianping Lin
    Journal of Cheminformatics, 8
  • [37] Improving chemical similarity ensemble approach in target prediction
    Wang, Zhonghua
    Liang, Lu
    Yin, Zheng
    Lin, Jianping
    JOURNAL OF CHEMINFORMATICS, 2016, 8
  • [38] Improving graphs of cycles approach to structural similarity of molecules
    Ilemo, Stefi Nouleho
    Barth, Dominique
    David, Olivier
    Quessette, Franck
    Weisser, Marc-Antoine
    Watel, Dimitri
    PLOS ONE, 2019, 14 (12):
  • [39] State Similarity Based Approach for Improving Performance in RL
    Girgin, Sertan
    Polat, Faruk
    Alhajj, Reda
    20TH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2007, : 817 - 822
  • [40] OntoInfoG++: A Knowledge Fusion Semantic Approach for Infographics Recommendation
    Deepak, Gerard
    Vibakar, Adithya
    Santhanavijayan, A.
    INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE, 2023, 8 (02): : 213 - 223