Article

Inferring a personalized next point-of-interest recommendation model with latent behavior patterns

Authors:

William K. CheungAuthors Info & Claims

AAAI'16: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence

Pages 137 - 143

Published: 12 February 2016 Publication History

Abstract

In this paper, we address the problem of personalized next Point-of-interest (POI) recommendation which has become an important and very challenging task in location-based social networks (LBSNs), but not well studied yet. With the conjecture that, under different contextual scenario, human exhibits distinct mobility patterns, we attempt here to jointly model the next POI recommendation under the influence of user's latent behavior pattern. We propose to adopt a third-rank tensor to model the successive check-in behaviors. By incorporating softmax function to fuse the personalized Markov chain with latent pattern, we furnish a Bayesian Personalized Ranking (BPR) approach and derive the optimization criterion accordingly. Expectation Maximization (EM) is then used to estimate the model parameters. Extensive experiments on two large-scale LBSNs datasets demonstrate the significant improvements of our model over several state-of-the-art methods.

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Qin YFang YLuo HZhao FWang CAmigo ECastells PGonzalo JCarterette BCulpepper JKazai G(2022)Next Point-of-Interest Recommendation with Auto-Correlation Enhanced Multi-Modal Transformer NetworkProceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3477495.3531905(2612-2616)Online publication date: 6-Jul-2022
https://dl.acm.org/doi/10.1145/3477495.3531905
Zhang MYang YAbbas RDeng KLi JZhang BDemartini GZuccon GCulpepper JHuang ZTong H(2021)SNPRProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482394(2568-2577)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482394
Jeon JKang SJo MCho SPark NKim SSong CDemartini GZuccon GCulpepper JHuang ZTong H(2021)LightMoveProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3481935(3857-3866)Online publication date: 26-Oct-2021
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cover image Guide Proceedings

AAAI'16: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence

February 2016

4406 pages

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Association for the Advancement of Artificial Intelligence

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AAAI Press

Publication History

Published: 12 February 2016

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Cited By

Qin YFang YLuo HZhao FWang CAmigo ECastells PGonzalo JCarterette BCulpepper JKazai G(2022)Next Point-of-Interest Recommendation with Auto-Correlation Enhanced Multi-Modal Transformer NetworkProceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3477495.3531905(2612-2616)Online publication date: 6-Jul-2022
https://dl.acm.org/doi/10.1145/3477495.3531905
Zhang MYang YAbbas RDeng KLi JZhang BDemartini GZuccon GCulpepper JHuang ZTong H(2021)SNPRProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482394(2568-2577)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482394
Jeon JKang SJo MCho SPark NKim SSong CDemartini GZuccon GCulpepper JHuang ZTong H(2021)LightMoveProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3481935(3857-3866)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3481935
Zhao PZhu HLiu YXu JLi ZZhuang FSheng VZhou X(2019)Where to go nextProceedings of the Thirty-Third AAAI Conference on Artificial Intelligence and Thirty-First Innovative Applications of Artificial Intelligence Conference and Ninth AAAI Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v33i01.33015877(5877-5884)Online publication date: 27-Jan-2019
https://dl.acm.org/doi/10.1609/aaai.v33i01.33015877
Xi DZhuang FLiu YGu JXiong HHe Q(2019)Modelling of bi-directional spatio-temporal dependence and users' dynamic preferences for missing POI check-in identificationProceedings of the Thirty-Third AAAI Conference on Artificial Intelligence and Thirty-First Innovative Applications of Artificial Intelligence Conference and Ninth AAAI Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v33i01.33015458(5458-5465)Online publication date: 27-Jan-2019
https://dl.acm.org/doi/10.1609/aaai.v33i01.33015458
Liu TLiao JWu ZWang YWang JEl Saddik ADel Bimbo AZhang ZHauptmann ACandan KBertini MXie LWei X(2019)A Geographical-Temporal Awareness Hierarchical Attention Network for Next Point-of-Interest RecommendationProceedings of the 2019 on International Conference on Multimedia Retrieval10.1145/3323873.3325024(7-15)Online publication date: 5-Jun-2019
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Su CLi HXie X(2019)Personalized Ranking Point of Interest Recommendation Based on Spatial-Temporal Distance Metric in LBSNsProceedings of the 2019 8th International Conference on Software and Computer Applications10.1145/3316615.3316715(38-43)Online publication date: 19-Feb-2019
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Song CWen JLi S(2019)Personalized POI recommendation based on check-in data and geographical-regional influenceProceedings of the 3rd International Conference on Machine Learning and Soft Computing10.1145/3310986.3311034(128-133)Online publication date: 25-Jan-2019
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Zhou FYue XTrajcevski GZhong TZhang K(2019)Context-aware Variational Trajectory Encoding and Human Mobility InferenceThe World Wide Web Conference10.1145/3308558.3313608(3469-3475)Online publication date: 13-May-2019
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Lu YShih WGau HChung KHuang J(2019)On successive point-of-interest recommendationWorld Wide Web10.1007/s11280-018-0599-522:3(1151-1173)Online publication date: 1-May-2019
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