Context-aware point-of-interest recommendation using Tensor Factorization with social regularization

Lina Yao; Quan Z. Sheng; Yongrui Qin; Xianzhi Wang; Ali Shemshadi; Qi He

doi:10.1145/2766462.2767794

Context-aware point-of-interest recommendation using Tensor Factorization with social regularization

Lina Yao, Quan Z. Sheng, Yongrui Qin, Xianzhi Wang, Ali Shemshadi, Qi He

University of Adelaide

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

105 Citations (Scopus)

Abstract

Point-of-Interest (POI) recommendation is a new type of recommendation task that comes along with the prevalence of locationbased social networks in recent years. Compared with traditional tasks, it focuses more on personalized, context-aware recommendation results to provide better user experience. To address this new challenge, we propose a Collaborative Filtering method based on Nonnegative Tensor Factorization, a generalization of the Matrix Factorization approach that exploits a high-order tensor instead of traditional User-Location matrix to model multi-dimensional contextual information. The factorization of this tensor leads to a compact model of the data which is specially suitable for context-aware POI recommendations. In addition, we fuse users' social relations as regularization terms of the factorization to improve the recommendation accuracy. Experimental results on real-world datasets demonstrate the effectiveness of our approach.

Original language	English
Title of host publication	SIGIR 2015 - Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval
Publisher	Association for Computing Machinery, Inc
Pages	1007-1010
Number of pages	4
ISBN (Electronic)	9781450336215
DOIs	https://doi.org/10.1145/2766462.2767794
Publication status	Published - 9 Aug 2015
Externally published	Yes
Event	38th International ACM SIGIR Conference on Research and Development in Information Retrieval - Santiago, Chile Duration: 9 Aug 2015 → 13 Aug 2015 Conference number: 38

Conference

Conference	38th International ACM SIGIR Conference on Research and Development in Information Retrieval
Abbreviated title	SIGIR 2015
Country/Territory	Chile
City	Santiago
Period	9/08/15 → 13/08/15

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10.1145/2766462.2767794Licence: Unspecified

Cite this

Yao, L., Sheng, Q. Z., Qin, Y., Wang, X., Shemshadi, A., & He, Q. (2015). Context-aware point-of-interest recommendation using Tensor Factorization with social regularization. In SIGIR 2015 - Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 1007-1010). Association for Computing Machinery, Inc. https://doi.org/10.1145/2766462.2767794

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title = "Context-aware point-of-interest recommendation using Tensor Factorization with social regularization",

abstract = "Point-of-Interest (POI) recommendation is a new type of recommendation task that comes along with the prevalence of locationbased social networks in recent years. Compared with traditional tasks, it focuses more on personalized, context-aware recommendation results to provide better user experience. To address this new challenge, we propose a Collaborative Filtering method based on Nonnegative Tensor Factorization, a generalization of the Matrix Factorization approach that exploits a high-order tensor instead of traditional User-Location matrix to model multi-dimensional contextual information. The factorization of this tensor leads to a compact model of the data which is specially suitable for context-aware POI recommendations. In addition, we fuse users' social relations as regularization terms of the factorization to improve the recommendation accuracy. Experimental results on real-world datasets demonstrate the effectiveness of our approach.",

keywords = "Location based social networks, Recommendation, Social regularization, Tensor Factorization",

author = "Lina Yao and Sheng, \{Quan Z.\} and Yongrui Qin and Xianzhi Wang and Ali Shemshadi and Qi He",

year = "2015",

month = aug,

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doi = "10.1145/2766462.2767794",

language = "English",

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booktitle = "SIGIR 2015 - Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval",

publisher = "Association for Computing Machinery, Inc",

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note = "38th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2015 ; Conference date: 09-08-2015 Through 13-08-2015",

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Yao, L, Sheng, QZ, Qin, Y, Wang, X, Shemshadi, A & He, Q 2015, Context-aware point-of-interest recommendation using Tensor Factorization with social regularization. in SIGIR 2015 - Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, Inc, pp. 1007-1010, 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, Santiago, Chile, 9/08/15. https://doi.org/10.1145/2766462.2767794

Context-aware point-of-interest recommendation using Tensor Factorization with social regularization. / Yao, Lina; Sheng, Quan Z.; Qin, Yongrui et al.
SIGIR 2015 - Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, Inc, 2015. p. 1007-1010.

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

TY - GEN

T1 - Context-aware point-of-interest recommendation using Tensor Factorization with social regularization

AU - Yao, Lina

AU - Sheng, Quan Z.

AU - Qin, Yongrui

AU - Wang, Xianzhi

AU - Shemshadi, Ali

AU - He, Qi

N1 - Conference code: 38

PY - 2015/8/9

Y1 - 2015/8/9

N2 - Point-of-Interest (POI) recommendation is a new type of recommendation task that comes along with the prevalence of locationbased social networks in recent years. Compared with traditional tasks, it focuses more on personalized, context-aware recommendation results to provide better user experience. To address this new challenge, we propose a Collaborative Filtering method based on Nonnegative Tensor Factorization, a generalization of the Matrix Factorization approach that exploits a high-order tensor instead of traditional User-Location matrix to model multi-dimensional contextual information. The factorization of this tensor leads to a compact model of the data which is specially suitable for context-aware POI recommendations. In addition, we fuse users' social relations as regularization terms of the factorization to improve the recommendation accuracy. Experimental results on real-world datasets demonstrate the effectiveness of our approach.

AB - Point-of-Interest (POI) recommendation is a new type of recommendation task that comes along with the prevalence of locationbased social networks in recent years. Compared with traditional tasks, it focuses more on personalized, context-aware recommendation results to provide better user experience. To address this new challenge, we propose a Collaborative Filtering method based on Nonnegative Tensor Factorization, a generalization of the Matrix Factorization approach that exploits a high-order tensor instead of traditional User-Location matrix to model multi-dimensional contextual information. The factorization of this tensor leads to a compact model of the data which is specially suitable for context-aware POI recommendations. In addition, we fuse users' social relations as regularization terms of the factorization to improve the recommendation accuracy. Experimental results on real-world datasets demonstrate the effectiveness of our approach.

KW - Location based social networks

KW - Recommendation

KW - Social regularization

KW - Tensor Factorization

UR - https://www.scopus.com/pages/publications/84953774751

U2 - 10.1145/2766462.2767794

DO - 10.1145/2766462.2767794

M3 - Conference contribution

AN - SCOPUS:84953774751

SP - 1007

EP - 1010

BT - SIGIR 2015 - Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval

PB - Association for Computing Machinery, Inc

T2 - 38th International ACM SIGIR Conference on Research and Development in Information Retrieval

Y2 - 9 August 2015 through 13 August 2015

ER -

Yao L, Sheng QZ, Qin Y, Wang X, Shemshadi A, He Q. Context-aware point-of-interest recommendation using Tensor Factorization with social regularization. In SIGIR 2015 - Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, Inc. 2015. p. 1007-1010 doi: 10.1145/2766462.2767794

Context-aware point-of-interest recommendation using Tensor Factorization with social regularization

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