Domain-to-Domain Translation Model for Recommender System

12/15/2018
by   Linh Nguyen, et al.
0

Recently multi-domain recommender systems have received much attention from researchers because they can solve cold-start problem as well as support for cross-selling. However, when applying into multi-domain items, although algorithms specifically addressing a single domain have many difficulties in capturing the specific characteristics of each domain, multi-domain algorithms have less opportunity to obtain similar features among domains. Because both similarities and differences exist among domains, multi-domain models must capture both to achieve good performance. Other studies of multi-domain systems merely transfer knowledge from the source domain to the target domain, so the source domain usually comes from external factors such as the search query or social network, which is sometimes impossible to obtain. To handle the two problems, we propose a model that can extract both homogeneous and divergent features among domains and extract data in a domain can support for other domain equally: a so-called Domain-to-Domain Translation Model (D2D-TM). It is based on generative adversarial networks (GANs), Variational Autoencoders (VAEs), and Cycle-Consistency (CC) for weight-sharing. We use the user interaction history of each domain as input and extract latent features through a VAE-GAN-CC network. Experiments underscore the effectiveness of the proposed system over state-of-the-art methods by a large margin.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/22/2022

One for All, All for One: Learning and Transferring User Embeddings for Cross-Domain Recommendation

Cross-domain recommendation is an important method to improve recommende...
research
11/07/2022

Debiasing Graph Transfer Learning via Item Semantic Clustering for Cross-Domain Recommendations

Deep learning-based recommender systems may lead to over-fitting when la...
research
09/17/2019

Cycle-consistent Conditional Adversarial Transfer Networks

Domain adaptation investigates the problem of cross-domain knowledge tra...
research
04/26/2021

Recommending Burgers based on Pizza Preferences: Addressing Data Sparsity with a Product of Experts

In this paper we describe a method to tackle data sparsity and create re...
research
03/10/2023

Knowledge Transfer via Multi-Head Feature Adaptation for Whole Slide Image Classification

Transferring prior knowledge from a source domain to the same or similar...
research
10/06/2021

Dynamically Decoding Source Domain Knowledge For Unseen Domain Generalization

Domain generalization is an important problem which has gain much attent...
research
02/18/2021

DINO: A Conditional Energy-Based GAN for Domain Translation

Domain translation is the process of transforming data from one domain t...

Please sign up or login with your details

Forgot password? Click here to reset