Deep adversarial group recommendation with user feature space separation

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Sun, Jianwen;Du, Shangheng;Liang, Ruxia;Shen, Xiaoxuan;Li, Qing;...

通讯作者：

Liang, RX

作者机构：

[Shen, Xiaoxuan; Yang, Zongkai; Liu, Sannyuya; Li, Qing; Liang, Ruxia; Du, Shangheng; Sun, Jianwen] Cent China Normal Univ, Natl Engn Res Ctr Educ Big Data, Wuhan 430079, Peoples R China.

[Shen, Xiaoxuan; Yang, Zongkai; Liu, Sannyuya; Li, Qing; Liang, Ruxia; Du, Shangheng; Sun, Jianwen] Cent China Normal Univ, Fac Artificial Intelligence Educ, Wuhan 430079, Peoples R China.

[Yang, Zongkai; Liu, Sannyuya] Cent China Normal Univ, Natl Engn Res Ctr Elearning, Wuhan 430079, Peoples R China.

通讯机构：

[Liang, RX ] C

Cent China Normal Univ, Natl Engn Res Ctr Educ Big Data, Wuhan 430079, Peoples R China.

Cent China Normal Univ, Fac Artificial Intelligence Educ, Wuhan 430079, Peoples R China.

语种：

英文

关键词：

Recommender systems;Group recommender systems;Adversarial learning;Knowledge transfer

期刊：

User Modeling and User-Adapted Interaction

ISSN：

0924-1868

年：

2023

页码：

1-33

DOI：

10.1007/s11257-023-09367-w

基金类别：

National Key R &D Program of China [2020AAA0108804]; National Natural Science Foundation of China [62207017, 62107017, 62077021, 61937001]; China Postdoctoral Science Foundation [2022M711282, 2020M682454]; Hubei Provincial Natural Science Foundation of China [2022CFB414]; Knowledge Innovation Program of Wuhan-Shuguang Project [2022010801020287]; Fundamental Research Funds for the Central Universities [CCNU22XJ033, CCNU22LJ005]

机构署名：

本校为第一且通讯机构

院系归属：

国家数字化学习工程技术研究中心

摘要：

Many online services allow users to participate in various group activities such as online meeting or group buying and thus need to provide user groups with services that they are interested. The group recommender systems emerge as required and provide personalized services for various online user groups. Data sparsity is an important issue in group recommender systems, since even fewer group-item interactions are observed. Transfer learning has been one efficient tool to alleviate the data sparsity issue in recommender systems for individual u...

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Deep adversarial group recommendation with user feature space separation

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