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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 1: AAAI-21 Technical Tracks 1

Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce

February 1, 2023

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Authors

Houye Ji

Beijing University of Posts and Telecommunications


Junxiong Zhu

Alibaba Group


Xiao Wang

Beijing University of Posts and Telecommunications


Chuan Shi

Beijing University of Posts and Telecommunications


Bai Wang

Beijing University of Posts and Telecommunications


Xiaoye Tan

Alibaba Group


Yanghua Li

Alibaba Group


Shaojian He

Alibaba Group


DOI:

10.1609/aaai.v35i1.16097


Abstract:

The prosperous development of social e-commerce has spawned diverse recommendation demands, and accompanied a new recommendation paradigm, share recommendation. Significantly different from traditional binary recommendations (e.g., item recommendation and friend recommendation), share recommendation models ternary interactions among 〈 User, Item, Friend 〉 , which aims to recommend a most likely friend to a user who would like to share a specific item, progressively becoming an indispensable service in social e-commerce. Seamlessly integrating the social relations and purchase behaviours, share recommendation improves user stickiness and monetizes the user influence, meanwhile encountering three unique challenges: rich heterogeneous information, complex ternary interaction, and asymmetric share action. In this paper, we first study the share recommendation problem and propose a heterogeneous graph neural network based share recommendation model, called HGSRec. Specifically, HGSRec delicately designs a tripartite heterogeneous GNNs to describe the multifold characteristics of users and items, and then dynamically fuses them via capturing potential ternary dependency with a dual co-attention mechanism, followed by a transitive triplet representation to depict the asymmetry of share action and predict whether share action happens. Offline experiments demonstrate the superiority of the proposed HGSRec with significant improvements (11.7%-14.5%) over the state-of-the-arts, and online A/B testing on Taobao platform further demonstrates the high industrial practicability and stability of HGSRec.

Topics: AAAI

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HOW TO CITE:

Houye Ji||Junxiong Zhu||Xiao Wang||Chuan Shi||Bai Wang||Xiaoye Tan||Yanghua Li||Shaojian He Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce Proceedings of the AAAI Conference on Artificial Intelligence (2021) 232-239.

Houye Ji||Junxiong Zhu||Xiao Wang||Chuan Shi||Bai Wang||Xiaoye Tan||Yanghua Li||Shaojian He Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce AAAI 2021, 232-239.

Houye Ji||Junxiong Zhu||Xiao Wang||Chuan Shi||Bai Wang||Xiaoye Tan||Yanghua Li||Shaojian He (2021). Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce. Proceedings of the AAAI Conference on Artificial Intelligence, 232-239.

Houye Ji||Junxiong Zhu||Xiao Wang||Chuan Shi||Bai Wang||Xiaoye Tan||Yanghua Li||Shaojian He. Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.232-239.

Houye Ji||Junxiong Zhu||Xiao Wang||Chuan Shi||Bai Wang||Xiaoye Tan||Yanghua Li||Shaojian He. 2021. Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce. "Proceedings of the AAAI Conference on Artificial Intelligence". 232-239.

Houye Ji||Junxiong Zhu||Xiao Wang||Chuan Shi||Bai Wang||Xiaoye Tan||Yanghua Li||Shaojian He. (2021) "Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce", Proceedings of the AAAI Conference on Artificial Intelligence, p.232-239

Houye Ji||Junxiong Zhu||Xiao Wang||Chuan Shi||Bai Wang||Xiaoye Tan||Yanghua Li||Shaojian He, "Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce", AAAI, p.232-239, 2021.

Houye Ji||Junxiong Zhu||Xiao Wang||Chuan Shi||Bai Wang||Xiaoye Tan||Yanghua Li||Shaojian He. "Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.232-239.

Houye Ji||Junxiong Zhu||Xiao Wang||Chuan Shi||Bai Wang||Xiaoye Tan||Yanghua Li||Shaojian He. "Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 232-239.

Houye Ji||Junxiong Zhu||Xiao Wang||Chuan Shi||Bai Wang||Xiaoye Tan||Yanghua Li||Shaojian He. Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce. AAAI[Internet]. 2021[cited 2023]; 232-239.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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