Joint modeling of users' interests and mobility patterns for point-of-interest recommendation

Hongzhi Yin; Bin Cui; Zi Huang; Weiqing Wang; Xian Wu; Xiaofang Zhou

doi:10.1145/2733373.2806339

Joint modeling of users' interests and mobility patterns for point-of-interest recommendation

Hongzhi Yin, Bin Cui, Zi Huang, Weiqing Wang, Xian Wu, Xiaofang Zhou

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

69 Citations (Scopus)

Abstract

Point-of-Interest (POI) recommendation has become an important means to help people discover interesting places, especially when users travel out of town. However, extreme sparsity of user-POI matrix creates a severe challenge. To cope with this challenge, we propose a unified probabilistic generative model, Topic-Region Model (TRM), to simultaneously discover the semantic, temporal and spatial patterns of users' check-in activities, and to model their joint effect on users' decision-making for POIs. We conduct extensive experiments to evaluate the performance of our TRM on two real large-scale datasets, and the experimental results clearly demonstrate that TRM outperforms the state-of-Art methods.

Original language	English
Title of host publication	MM'15 - Proceedings of the 2015 ACM Multimedia Conference
Subtitle of host publication	October 26-30, 2015 Brisbane, Australia
Editors	Dick C.A. Bulterman, Heng Tao Shen, Ketan Mayer-Patel, Shuicheng Yan
Place of Publication	New York NY USA
Publisher	Association for Computing Machinery (ACM)
Pages	819-822
Number of pages	4
ISBN (Electronic)	9781450334594
DOIs	https://doi.org/10.1145/2733373.2806339
Publication status	Published - 2015
Externally published	Yes
Event	ACM International Conference on Multimedia 2015 - Brisbane, Australia Duration: 26 Oct 2015 → 30 Oct 2015 Conference number: 23rd https://dl.acm.org/doi/proceedings/10.1145/2733373

Conference

Conference	ACM International Conference on Multimedia 2015
Abbreviated title	MM 2015
Country/Territory	Australia
City	Brisbane
Period	26/10/15 → 30/10/15
Internet address	https://dl.acm.org/doi/proceedings/10.1145/2733373

Keywords

Joint Modeling
Location-based service
Probabilistic generative model
Recommender system

Access to Document

10.1145/2733373.2806339

Cite this

Yin, H., Cui, B., Huang, Z., Wang, W., Wu, X., & Zhou, X. (2015). Joint modeling of users' interests and mobility patterns for point-of-interest recommendation. In D. C.A. Bulterman, H. Tao Shen, K. Mayer-Patel, & S. Yan (Eds.), MM'15 - Proceedings of the 2015 ACM Multimedia Conference: October 26-30, 2015 Brisbane, Australia (pp. 819-822). Association for Computing Machinery (ACM). https://doi.org/10.1145/2733373.2806339

Yin, Hongzhi ; Cui, Bin ; Huang, Zi et al. / Joint modeling of users' interests and mobility patterns for point-of-interest recommendation. MM'15 - Proceedings of the 2015 ACM Multimedia Conference: October 26-30, 2015 Brisbane, Australia. editor / Dick C.A. Bulterman ; Heng Tao Shen ; Ketan Mayer-Patel ; Shuicheng Yan. New York NY USA : Association for Computing Machinery (ACM), 2015. pp. 819-822

@inproceedings{e117c9dbbfb148b896ef298638f3e49f,

title = "Joint modeling of users' interests and mobility patterns for point-of-interest recommendation",

abstract = "Point-of-Interest (POI) recommendation has become an important means to help people discover interesting places, especially when users travel out of town. However, extreme sparsity of user-POI matrix creates a severe challenge. To cope with this challenge, we propose a unified probabilistic generative model, Topic-Region Model (TRM), to simultaneously discover the semantic, temporal and spatial patterns of users' check-in activities, and to model their joint effect on users' decision-making for POIs. We conduct extensive experiments to evaluate the performance of our TRM on two real large-scale datasets, and the experimental results clearly demonstrate that TRM outperforms the state-of-Art methods.",

keywords = "Joint Modeling, Location-based service, Probabilistic generative model, Recommender system",

author = "Hongzhi Yin and Bin Cui and Zi Huang and Weiqing Wang and Xian Wu and Xiaofang Zhou",

year = "2015",

doi = "10.1145/2733373.2806339",

language = "English",

pages = "819--822",

editor = "{C.A. Bulterman}, {Dick } and {Tao Shen}, Heng and Mayer-Patel, {Ketan } and Yan, {Shuicheng }",

booktitle = "MM'15 - Proceedings of the 2015 ACM Multimedia Conference",

publisher = "Association for Computing Machinery (ACM)",

address = "United States of America",

note = "ACM International Conference on Multimedia 2015, MM 2015 ; Conference date: 26-10-2015 Through 30-10-2015",

url = "https://dl.acm.org/doi/proceedings/10.1145/2733373",

}

Yin, H, Cui, B, Huang, Z, Wang, W, Wu, X & Zhou, X 2015, Joint modeling of users' interests and mobility patterns for point-of-interest recommendation. in D C.A. Bulterman, H Tao Shen, K Mayer-Patel & S Yan (eds), MM'15 - Proceedings of the 2015 ACM Multimedia Conference: October 26-30, 2015 Brisbane, Australia. Association for Computing Machinery (ACM), New York NY USA, pp. 819-822, ACM International Conference on Multimedia 2015, Brisbane, Queensland, Australia, 26/10/15. https://doi.org/10.1145/2733373.2806339

Joint modeling of users' interests and mobility patterns for point-of-interest recommendation. / Yin, Hongzhi; Cui, Bin; Huang, Zi et al.
MM'15 - Proceedings of the 2015 ACM Multimedia Conference: October 26-30, 2015 Brisbane, Australia. ed. / Dick C.A. Bulterman; Heng Tao Shen; Ketan Mayer-Patel; Shuicheng Yan. New York NY USA: Association for Computing Machinery (ACM), 2015. p. 819-822.

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

TY - GEN

T1 - Joint modeling of users' interests and mobility patterns for point-of-interest recommendation

AU - Yin, Hongzhi

AU - Cui, Bin

AU - Huang, Zi

AU - Wang, Weiqing

AU - Wu, Xian

AU - Zhou, Xiaofang

N1 - Conference code: 23rd

PY - 2015

Y1 - 2015

N2 - Point-of-Interest (POI) recommendation has become an important means to help people discover interesting places, especially when users travel out of town. However, extreme sparsity of user-POI matrix creates a severe challenge. To cope with this challenge, we propose a unified probabilistic generative model, Topic-Region Model (TRM), to simultaneously discover the semantic, temporal and spatial patterns of users' check-in activities, and to model their joint effect on users' decision-making for POIs. We conduct extensive experiments to evaluate the performance of our TRM on two real large-scale datasets, and the experimental results clearly demonstrate that TRM outperforms the state-of-Art methods.

AB - Point-of-Interest (POI) recommendation has become an important means to help people discover interesting places, especially when users travel out of town. However, extreme sparsity of user-POI matrix creates a severe challenge. To cope with this challenge, we propose a unified probabilistic generative model, Topic-Region Model (TRM), to simultaneously discover the semantic, temporal and spatial patterns of users' check-in activities, and to model their joint effect on users' decision-making for POIs. We conduct extensive experiments to evaluate the performance of our TRM on two real large-scale datasets, and the experimental results clearly demonstrate that TRM outperforms the state-of-Art methods.

KW - Joint Modeling

KW - Location-based service

KW - Probabilistic generative model

KW - Recommender system

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U2 - 10.1145/2733373.2806339

DO - 10.1145/2733373.2806339

M3 - Conference Paper

AN - SCOPUS:84962833523

SP - 819

EP - 822

BT - MM'15 - Proceedings of the 2015 ACM Multimedia Conference

A2 - C.A. Bulterman, Dick

A2 - Tao Shen, Heng

A2 - Mayer-Patel, Ketan

A2 - Yan, Shuicheng

PB - Association for Computing Machinery (ACM)

CY - New York NY USA

T2 - ACM International Conference on Multimedia 2015

Y2 - 26 October 2015 through 30 October 2015

ER -

Yin H, Cui B, Huang Z, Wang W, Wu X, Zhou X. Joint modeling of users' interests and mobility patterns for point-of-interest recommendation. In C.A. Bulterman D, Tao Shen H, Mayer-Patel K, Yan S, editors, MM'15 - Proceedings of the 2015 ACM Multimedia Conference: October 26-30, 2015 Brisbane, Australia. New York NY USA: Association for Computing Machinery (ACM). 2015. p. 819-822 doi: 10.1145/2733373.2806339

Joint modeling of users' interests and mobility patterns for point-of-interest recommendation

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Keywords

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