Influence of Social Communication on Content-Based Recommendation

被引：0
|
作者：
Maleszka, Bernadetta [1 ]
Maleszka, Marcin [1 ]
机构：
[1] Wrocaw Univ Sci & Technol, Fac Comp Sci & Management, St Wyspianskiego 27, PL-50370 Wroclaw, Poland
来源：
2017 IEEE INTERNATIONAL CONFERENCE ON INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS (INISTA) | 2017年
关键词：
information retrieval; knowledge diffusion; user preference evolution; user profile;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
One of basic divisions of information retrieval systems is content-based and collaborative filtering. Some hybrid methods exist combining both of them, but certain aspects still remain unexplored. In this paper we explore one: the influence of users communicating via social media on content-based recommendation systems. While in the system users do not know each other, outside they may make their own preferences known (e.g. tweeting recommendations), thus influencing the preferences of other users. Here we simulate several different types of such communication and its influence on content-based recommendation system. We intend to use this results for improving the quality of such systems.
引用
收藏
页码：143 / 148
页数：6
相关论文
共 50 条
  • [31] A content-based recommendation approach based on singular value decomposition
    Colace, Francesco
    Conte, Dajana
    De Santo, Massimo
    Lombardi, Marco
    Santaniello, Domenico
    Valentino, Carmine
    [J]. CONNECTION SCIENCE, 2022, 34 (01) : 2158 - 2176
  • [32] Content-based filtering for music recommendation based on ubiquitous computing
    Kim, Jong-Hun
    Kang, Un-Gu
    Lee, Jung-Hyun
    [J]. INTELLIGENT INFORMATION PROCESSING III, 2006, 228 : 463 - +
  • [33] Distributed Representations for Content-based and Personalized Tag Recommendation
    Kataria, Saurabh
    Agarwal, Arvind
    [J]. 2015 IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOP (ICDMW), 2015, : 1388 - 1395
  • [34] Exploring Coclustering for Serendipity Improvement in Content-Based Recommendation
    Silva, Andrei Martins
    da Silva Costa, Fernando Henrique
    Ramos Diaz, Alexandra Katiuska
    Peres, Sarajane Marques
    [J]. INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2018, PT I, 2018, 11314 : 317 - 327
  • [35] Journal Recommendation System Using Content-Based Filtering
    Jain, Sonal
    Khangarot, Harshita
    Singh, Shivank
    [J]. Advances in Intelligent Systems and Computing, 2019, 740 : 99 - 108
  • [36] TOWARDS SEMANTIC AND AFFECTIVE CONTENT-BASED VIDEO RECOMMENDATION
    Yoshida, Taiga
    Irie, Go
    Arai, Hiroyuki
    Taniguchi, Yukinobu
    [J]. ELECTRONIC PROCEEDINGS OF THE 2013 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO WORKSHOPS (ICMEW), 2013,
  • [37] MusicCNNs: A New Benchmark on Content-Based Music Recommendation
    Zhong, Guoqiang
    Wang, Haizhen
    Jiao, Wencong
    [J]. NEURAL INFORMATION PROCESSING (ICONIP 2018), PT I, 2018, 11301 : 394 - 405
  • [38] A Review of Content-Based and Context-Based Recommendation Systems
    Javed, Umair
    Shaukat, Kamran
    Hameed, Ibrahim A.
    Iqbal, Farhat
    Alam, Talha Mahboob
    Luo, Suhuai
    [J]. INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING, 2021, 16 (03): : 274 - 306
  • [39] Hybrid Recommendation System Based on Collaborative and Content-Based Filtering
    Parthasarathy, Govindarajan
    Devi, Shanmugam Sathiya
    [J]. CYBERNETICS AND SYSTEMS, 2023, 54 (04) : 432 - 453
  • [40] Content-based recommendation services for personalized Digital Libraries
    Semeraro, G.
    Basile, P.
    de Gemmis, M.
    Lops, P.
    [J]. DIGITAL LIBRARIES: RESEARCH AND DEVELOPMENT, 2007, 4877 : 77 - 86
12345