A collaborative filtering recommendation framework based on Wasserstein GAN. (November 2020)
- Record Type:
- Journal Article
- Title:
- A collaborative filtering recommendation framework based on Wasserstein GAN. (November 2020)
- Main Title:
- A collaborative filtering recommendation framework based on Wasserstein GAN
- Authors:
- Li, Rui
Qian, Fulan
Du, Xiuquan
Zhao, Shu
Zhang, Yanping - Abstract:
- Abstract: Compared with the original GAN, Wasserstein GAN minimizes the Wasserstein Distance between the generative distribution and the real distribution, can well capture the potential distribution of data and has achieved excellent results in image generation. However, the exploration of Wasserstein GAN on recommendation systems has received relatively less scrutiny. In this paper, we propose a collaborative filtering recommendation framework based on Wasserstein GAN called CFWGAN to improve recommendation accuracy. By learning the real user distribution, we can mine the potential nonlinear interactions between users and items, and capture users' preferences for all items. Besides, we combine two positive and negative item sampling methods and add the reconstruction loss to the generator's loss. This can well handle the problem of discrete data in recommendation (relative to the continuity of image data). By continuously approximating the generative distribution to the real user distribution, we can finally obtain better users' preference information and provide higher accuracy in recommendation. We evaluate the CFWGAN model on three real-world datasets, and the empirical results show that our method is competitive with or superior to state-of-the-art approaches on the benchmark top-N recommendation task.
- Is Part Of:
- Journal of physics. Volume 1684(2020)
- Journal:
- Journal of physics
- Issue:
- Volume 1684(2020)
- Issue Display:
- Volume 1684, Issue 1 (2020)
- Year:
- 2020
- Volume:
- 1684
- Issue:
- 1
- Issue Sort Value:
- 2020-1684-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-11
- Subjects:
- Physics -- Congresses
530.5 - Journal URLs:
- http://www.iop.org/EJ/journal/1742-6596 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1742-6596/1684/1/012057 ↗
- Languages:
- English
- ISSNs:
- 1742-6588
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5036.223000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25478.xml