Collaborative restricted Boltzmann machine for social event recommendation

Xiaowei Jia; Xiaoyi Li; Kang Li; Vishrawas Gopalakrishnan; Guangxu Xun; Aidong Zhang

doi:10.1109/ASONAM.2016.7752265

Collaborative restricted Boltzmann machine for social event recommendation

Xiaowei Jia
, Xiaoyi Li
, Kang Li
, Vishrawas Gopalakrishnan
, Guangxu Xun
, Aidong Zhang

Department of Computer Science and Engineering

University of Minnesota Twin Cities
SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

21 Scopus citations

Abstract

The development of social networks has not only improved the online experience, but also stimulated the advances in knowledge mining so as to assist people in planning their offline social events. Users can explore their favorite events, such as celebrations and symposiums, through the pictures and the posts from their friends on social networks. An effective event recommendation can offer great convenience for both event organizers and participants, which yet remains extremely challenging due to a wide range of practical concerns. In this paper we propose a novel recommendation framework, which combines the information from multiple sources and establishes a connection between the online knowledge and the event participation.

Original language	English
Title of host publication	Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
Editors	Ravi Kumar, James Caverlee, Hanghang Tong
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	402-405
Number of pages	4
ISBN (Electronic)	9781509028467
DOIs	https://doi.org/10.1109/ASONAM.2016.7752265
State	Published - Nov 21 2016
Event	8th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 - San Francisco, United States Duration: Aug 18 2016 → Aug 21 2016

Publication series

Name	Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016

Conference

Conference	8th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
Country/Territory	United States
City	San Francisco
Period	08/18/16 → 08/21/16

Access to Document

10.1109/ASONAM.2016.7752265

Cite this

Jia, X., Li, X., Li, K., Gopalakrishnan, V., Xun, G., & Zhang, A. (2016). Collaborative restricted Boltzmann machine for social event recommendation. In R. Kumar, J. Caverlee, & H. Tong (Eds.), Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 (pp. 402-405). Article 7752265 (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASONAM.2016.7752265

Jia, Xiaowei ; Li, Xiaoyi ; Li, Kang et al. / Collaborative restricted Boltzmann machine for social event recommendation. Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016. editor / Ravi Kumar ; James Caverlee ; Hanghang Tong. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 402-405 (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016).

@inproceedings{1d41b0d24a4b46da9e77f17313b3446b,

title = "Collaborative restricted Boltzmann machine for social event recommendation",

abstract = "The development of social networks has not only improved the online experience, but also stimulated the advances in knowledge mining so as to assist people in planning their offline social events. Users can explore their favorite events, such as celebrations and symposiums, through the pictures and the posts from their friends on social networks. An effective event recommendation can offer great convenience for both event organizers and participants, which yet remains extremely challenging due to a wide range of practical concerns. In this paper we propose a novel recommendation framework, which combines the information from multiple sources and establishes a connection between the online knowledge and the event participation.",

author = "Xiaowei Jia and Xiaoyi Li and Kang Li and Vishrawas Gopalakrishnan and Guangxu Xun and Aidong Zhang",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 8th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 ; Conference date: 18-08-2016 Through 21-08-2016",

year = "2016",

month = nov,

day = "21",

doi = "10.1109/ASONAM.2016.7752265",

language = "English",

series = "Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "402--405",

editor = "Ravi Kumar and James Caverlee and Hanghang Tong",

booktitle = "Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016",

address = "United States",

}

Jia, X, Li, X, Li, K, Gopalakrishnan, V, Xun, G & Zhang, A 2016, Collaborative restricted Boltzmann machine for social event recommendation. in R Kumar, J Caverlee & H Tong (eds), Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016., 7752265, Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016, Institute of Electrical and Electronics Engineers Inc., pp. 402-405, 8th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016, San Francisco, United States, 08/18/16. https://doi.org/10.1109/ASONAM.2016.7752265

Collaborative restricted Boltzmann machine for social event recommendation. / Jia, Xiaowei; Li, Xiaoyi; Li, Kang et al.
Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016. ed. / Ravi Kumar; James Caverlee; Hanghang Tong. Institute of Electrical and Electronics Engineers Inc., 2016. p. 402-405 7752265 (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Gopalakrishnan, Vishrawas

AU - Xun, Guangxu

AU - Zhang, Aidong

PY - 2016/11/21

Y1 - 2016/11/21

N2 - The development of social networks has not only improved the online experience, but also stimulated the advances in knowledge mining so as to assist people in planning their offline social events. Users can explore their favorite events, such as celebrations and symposiums, through the pictures and the posts from their friends on social networks. An effective event recommendation can offer great convenience for both event organizers and participants, which yet remains extremely challenging due to a wide range of practical concerns. In this paper we propose a novel recommendation framework, which combines the information from multiple sources and establishes a connection between the online knowledge and the event participation.

AB - The development of social networks has not only improved the online experience, but also stimulated the advances in knowledge mining so as to assist people in planning their offline social events. Users can explore their favorite events, such as celebrations and symposiums, through the pictures and the posts from their friends on social networks. An effective event recommendation can offer great convenience for both event organizers and participants, which yet remains extremely challenging due to a wide range of practical concerns. In this paper we propose a novel recommendation framework, which combines the information from multiple sources and establishes a connection between the online knowledge and the event participation.

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U2 - 10.1109/ASONAM.2016.7752265

DO - 10.1109/ASONAM.2016.7752265

M3 - Conference contribution

AN - SCOPUS:85006733680

T3 - Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016

SP - 402

EP - 405

BT - Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016

A2 - Kumar, Ravi

A2 - Caverlee, James

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PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 8th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016

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Jia X, Li X, Li K, Gopalakrishnan V, Xun G, Zhang A. Collaborative restricted Boltzmann machine for social event recommendation. In Kumar R, Caverlee J, Tong H, editors, Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 402-405. 7752265. (Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016). doi: 10.1109/ASONAM.2016.7752265

Collaborative restricted Boltzmann machine for social event recommendation

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