A collaborative filtering recommender system model using OWA and uninorm aggregation operators

Iván Palomares, Fiona Browne, Hui Wang, Peadar Davis

研究成果: Conference contribution

3 引文 斯高帕斯(Scopus)

摘要

Recommender systems have played a prominent role in online platforms over the last decade. These systems have been incorporated into applications ranging from e-commerce to leisure, successfully enhancing user experience. Moreover, recommender systems are now being applied to a wider diversity of emerging context applications on the Internet including social media and online platforms for communities. In this study, we present a novel collaborative filtering recommender system model. This model differentiates from other recommender system models in that it utilizes two aggregation operators, namely OWA and uninorm, to compute similarity degrees between users. We demonstrate the application of the proposed model by integrating it in the HARMONISE platform for communities in the Urban Resilience domain. The application example illustrates how the proposed model of collaborative filtering recommender system can predict content of interest to users in the platform, based not only on user preferences but also on features of their user profile.

原文English
主出版物標題Proceedings - The 2015 10th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2015
發行者Institute of Electrical and Electronics Engineers Inc.
頁面382-388
頁數7
ISBN(電子)9781467393225
DOIs
出版狀態Published - 2016 1月 13
事件10th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2015 - Taipei, Taiwan
持續時間: 2015 11月 242015 11月 27

出版系列

名字Proceedings - The 2015 10th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2015

Conference

Conference10th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2015
國家/地區Taiwan
城市Taipei
期間15-11-2415-11-27

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦視覺和模式識別
  • 控制和優化
  • 建模與模擬

指紋

深入研究「A collaborative filtering recommender system model using OWA and uninorm aggregation operators」主題。共同形成了獨特的指紋。

引用此