Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/150977
Title: Learning personalized itemset mapping for cross-domain recommendation
Authors: Zhang, Yinan
Liu, Yong
Han, Peng
Miao, Chunyan
Cui, Lizhen
Li, Baoli
Tang, Haihong
Keywords: Engineering::Computer science and engineering
Issue Date: 2020
Source: Zhang, Y., Liu, Y., Han, P., Miao, C., Cui, L., Li, B. & Tang, H. (2020). Learning personalized itemset mapping for cross-domain recommendation. 2020 International Joint Conference on Artificial Intelligence (IJCAI’20), 2561-2567. https://dx.doi.org/10.24963/ijcai.2020/355
Abstract: Cross-domain recommendation methods usually transfer knowledge across different domains implicitly, by sharing model parameters or learning parameter mappings in the latent space. Differing from previous studies, this paper focuses on learning explicit mapping between a user's behaviors (i.e. interaction itemsets) in different domains during the same temporal period. In this paper, we propose a novel deep cross-domain recommendation model, called Cycle Generation Networks (CGN). Specifically, CGN employs two generators to construct the dual-direction personalized itemset mapping between a user's behaviors in two different domains over time. The generators are learned by optimizing the distance between the generated itemset and the real interacted itemset, as well as the cycle-consistent loss defined based on the dual-direction generation procedure. We have performed extensive experiments on real datasets to demonstrate the effectiveness of the proposed model, comparing with existing single-domain and cross-domain recommendation methods.
URI: https://hdl.handle.net/10356/150977
ISBN: 978-0-9992411-6-5
DOI: 10.24963/ijcai.2020/355
Rights: © 2020 Twenty-Fifth International Joint Conference on Artificial Intelligence Organization (IJCAI-16 Organization)]. All rights reserved. This paper was published in 2020 International Joint Conference on Artificial Intelligence (IJCAI’20) and is made available with permission of Twenty-Fifth International Joint Conference on Artificial Intelligence Organization (IJCAI-16 Organization).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Conference Papers

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