short-paper

Tag-Aware Personalized Recommendation Using a Deep-Semantic Similarity Model with Negative Sampling

Authors:

Xiangwu MengAuthors Info & Claims

CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

Pages 1921 - 1924

https://doi.org/10.1145/2983323.2983874

Published: 24 October 2016 Publication History

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Abstract

With the rapid growth of social tagging systems, many efforts have been put on tag-aware personalized recommendation. However, due to uncontrolled vocabularies, social tags are usually redundant, sparse, and ambiguous. In this paper, we propose a deep neural network approach to solve this problem by mapping both the tag-based user and item profiles to an abstract deep feature space, where the deep-semantic similarities between users and their target items (resp., irrelevant items) are maximized (resp., minimized). Due to huge numbers of online items, the training of this model is usually computationally expensive in the real-world context. Therefore, we introduce negative sampling, which significantly increases the model's training efficiency (109.6 times quicker) and ensures the scalability in practice. Experimental results show that our model can significantly outperform the state-of-the-art baselines in tag-aware personalized recommendation: e.g., its mean reciprocal rank is between 5.7 and 16.5 times better than the baselines.

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Cited By

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Zuo YLiu SZhou Y(2023)DTGCF: Diversified Tag-Aware Recommendation with Graph Collaborative FilteringApplied Sciences10.3390/app1305294513:5(2945)Online publication date: 24-Feb-2023
https://doi.org/10.3390/app13052945
Zuo YLiu SZhou YLiu H(2023)TRAL: A Tag-Aware Recommendation Algorithm Based on Attention LearningApplied Sciences10.3390/app1302081413:2(814)Online publication date: 6-Jan-2023
https://doi.org/10.3390/app13020814
Shokrzadeh ZFeizi-Derakhshi MBalafar MBagherzadeh Mohasefi J(2023)Graph-Based Recommendation System Enhanced by Community DetectionScientific Programming10.1155/2023/50737692023Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1155/2023/5073769
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Tag-Aware Personalized Recommendation Using a Deep-Semantic Similarity Model with Negative Sampling

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Published In

CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

October 2016

2566 pages

ISBN:9781450340731

DOI:10.1145/2983323

General Chairs:
Snehasis Mukhopadhyay
Indiana University Purdue University Indianapolis, USA
,
ChengXiang Zhai
University of Illinois at Urbana-Champaign, USA
,
Program Chairs:
Elisa Bertino
Purdue University
,
Fabio Crestani
University of Lugano
,
Javed Mostafa
University of North Carolina
,
Jie Tang
Tsinghua University
,
Luo Si
Alibaba Group Inc & Purdue University
,
Xiaofang Zhou
University of Queensland
,
Yi Chang
Yahoo Research
,
Yunyao Li
IBM Research - Almaden
,
Parikshit Sondhi
WalmartLabs

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 October 2016

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Short-paper

Funding Sources

UK EPSRC

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CIKM'16

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CIKM'16: ACM Conference on Information and Knowledge Management

October 24 - 28, 2016

Indiana, Indianapolis, USA

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CIKM '16 Paper Acceptance Rate 160 of 701 submissions, 23%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

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Zuo YLiu SZhou Y(2023)DTGCF: Diversified Tag-Aware Recommendation with Graph Collaborative FilteringApplied Sciences10.3390/app1305294513:5(2945)Online publication date: 24-Feb-2023
https://doi.org/10.3390/app13052945
Zuo YLiu SZhou YLiu H(2023)TRAL: A Tag-Aware Recommendation Algorithm Based on Attention LearningApplied Sciences10.3390/app1302081413:2(814)Online publication date: 6-Jan-2023
https://doi.org/10.3390/app13020814
Shokrzadeh ZFeizi-Derakhshi MBalafar MBagherzadeh Mohasefi J(2023)Graph-Based Recommendation System Enhanced by Community DetectionScientific Programming10.1155/2023/50737692023Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1155/2023/5073769
Zhu XDu PShao SZhu CZhang WWang YCao YSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)A Feature-Based Coalition Game Framework with Privileged Knowledge Transfer for User-tag Profile ModelingProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599761(5739-5749)Online publication date: 6-Aug-2023
https://dl.acm.org/doi/10.1145/3580305.3599761
Wang QZhao WYang JWu JXue SXing QYu P(2023)C-DeepTrust: A Context-Aware Deep Trust Prediction Model in Online Social NetworksIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2021.310794834:6(2767-2780)Online publication date: Jun-2023
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Zuo YZhou YLiu SLiu Y(2023)A Tag-aware Recommendation Algorithm Based on Deep Learning and Multi-objective Optimization2023 International Conference on Pattern Recognition, Machine Vision and Intelligent Algorithms (PRMVIA)10.1109/PRMVIA58252.2023.00013(42-46)Online publication date: Mar-2023
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Wu HZhang YMa CGuo WTang RLiu XCoates M(2023)Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00090(1112-1125)Online publication date: Apr-2023
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Xu CZhang YChen HDong LWang W(2023)A fairness-aware graph contrastive learning recommender framework for social tagging systemsInformation Sciences: an International Journal10.1016/j.ins.2023.119064640:COnline publication date: 11-Jul-2023
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Wen XWang JYang X(2023)Dynamic negative sampling for recommendation with feature matchingMultimedia Tools and Applications10.1007/s11042-023-17521-083:16(49749-49766)Online publication date: 4-Nov-2023
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Seo HKim SRyu SJo SCho SSohn JLim C(2023)Development of an offline OOH advertising recommendation system using negative sampling and deep interest networkMultimedia Tools and Applications10.1007/s11042-023-16083-583:4(11943-11955)Online publication date: 27-Jun-2023
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