Top-k socio-spatial co-engaged location selection for social users

Article


Hasan Haldar, Nur Al, Li, Jianxin, Ali, Mohammed Eunus, Cai, Taotao, Chen, Yunliang, Sellis, Timos and Reynolds, Mark. 2023. "Top-k socio-spatial co-engaged location selection for social users." IEEE Transactions on Knowledge and Data Engineering. 35 (5), pp. 5325-5340. https://doi.org/10.1109/TKDE.2022.3151095
Article Title

Top-k socio-spatial co-engaged location selection for social users

ERA Journal ID17876
Article CategoryArticle
AuthorsHasan Haldar, Nur Al, Li, Jianxin, Ali, Mohammed Eunus, Cai, Taotao, Chen, Yunliang, Sellis, Timos and Reynolds, Mark
Journal TitleIEEE Transactions on Knowledge and Data Engineering
Journal Citation35 (5), pp. 5325-5340
Number of Pages16
Year2023
PublisherIEEE (Institute of Electrical and Electronics Engineers)
Place of PublicationUnited States
ISSN1041-4347
1558-2191
Digital Object Identifier (DOI)https://doi.org/10.1109/TKDE.2022.3151095
Web Address (URL)https://ieeexplore.ieee.org/document/9713727
Abstract

With the advent of location-based social networks, users can tag their daily activities in different locations through check-ins. These check-in locations signify user preferences for various socio-spatial activities and can be used to improve the quality of services in some applications such as recommendation systems, advertising, and group formation. To support such applications, in this paper, we formulate a new problem of identifying top-k Socio-Spatial co-engaged Location Selection (SSLS) for users in a social graph, that selects the best set of k locations from a large number of location candidates relating to the user and her friends. The selected locations should be (i) spatially and socially relevant to the user and her friends, and (ii) diversified both spatially and socially to maximize the coverage of friends in the socio-spatial space. This problem has been proved as NP-hard. To address such a challenging problem, we first develop an Exact solution by designing some pruning strategies based on derived bounds on diversity. To make the solution scalable for large datasets, we also develop an approximate solution by deriving relaxed bounds and advanced termination rules to filter out insignificant intermediate results. To further accelerate the efficiency, we present one fast exact approach and a meta-heuristic approximate approach by avoiding the repeated computation of diversity at the running time. Finally, we have performed extensive experiments to evaluate the performance of our proposed algorithms against three adapted existing methods using four large real-world datasets.

KeywordsLBSN; location selection in social networks; social graph computing; spatial database
Related Output
Is supplemented byhttps://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/LP180100750
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020460503. Data models, storage and indexing
Public NotesFiles associated with this item cannot be displayed due to copyright restrictions.
Byline AffiliationsUniversity of Western Australia
Deakin University
Bangladesh University of Engineering and Technology (BUET), Bangladesh
Macquarie University
China University of Geosciences, China
Swinburne University of Technology
Permalink -

https://research.usq.edu.au/item/z6033/top-k-socio-spatial-co-engaged-location-selection-for-social-users

  • 7
    total views
  • 0
    total downloads
  • 1
    views this month
  • 0
    downloads this month

Export as

Related outputs

FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning
Shaik, Thanveer, Tao, Xiaohui, Li, Lin, Xie, Haoran, Cai, Taotao, Zhu, Xiaofeng and Li, Qing. 2024. "FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning ." IEEE Transactions on Knowledge and Data Engineering. https://doi.org/10.1109/TKDE.2024.3382726
Reconnecting the Estranged Relationships: Optimizing the Influence Propagation in Evolving Networks
Cai, Taotao, Lei, Qi, Sheng, Quan Z., Cui, Ningning, Yang, Shuiqiao, Yang, Jian, Zhang, Wei Emma and Mahmood, Adnan. 2024. "Reconnecting the Estranged Relationships: Optimizing the Influence Propagation in Evolving Networks." IEEE Transactions on Knowledge and Data Engineering. 36 (5), pp. 2151-2165. https://doi.org/10.1109/TKDE.2023.3316268
Dynamic Correlation Adjacency Matrix Based Graph Neural Network for Traffic Flow Prediction
Gu, Junhua, Jia, Zhihao, Cai, Taotao, Song, Xiangyu and Mahmood, Adnan. 2023. "Dynamic Correlation Adjacency Matrix Based Graph Neural Network for Traffic Flow Prediction." Sensors. 23 (6). https://doi.org/10.3390/s23062897
Towards Multi-User, Secure, and Verifiable kNN Query in Cloud Database
Cui, Ningning, Qian, Kang, Cai, Taotao, Li, Jianxin, Yang, Xiaochun, Cui, Jie and Zhong, Hong. 2023. "Towards Multi-User, Secure, and Verifiable kNN Query in Cloud Database." IEEE Transactions on Knowledge and Data Engineering. 35 (9), pp. 9333-9349. https://doi.org/10.1109/TKDE.2023.3237879
Incremental graph computation: Anchored Vertex Tracking in Dynamic Social Networks
Cai, Taotao, Yang, Shuiqiao, Li, Jianxin, Sheng, Quan Z., Yang, Jian, Wang, Xin, Zhang, Wei Emma and Gao, Longxiang. 2023. "Incremental graph computation: Anchored Vertex Tracking in Dynamic Social Networks." IEEE Transactions on Knowledge and Data Engineering. 35 (7), pp. 7030-7044. https://doi.org/10.1109/TKDE.2022.3199494
Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction
Ali, Mumtaz, Deo, Ravinesh C., Xiang, Yong, Prasad, Ramendra, Li, Jianxin, Farooque, Aitazaz and Yaseen, Zaher Mundher. 2022. "Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction." Scientific Reports. 12 (1), pp. 1-23. https://doi.org/10.1038/s41598-022-09482-5
Robust cross-network node classification via constrained graph mutual information
Yang, Shuiqiao, Cai, Borui, Cai, Taotao, Song, Xiangyu, Jiang, Jiaojiao, Li, Bing and Li, Jianxin. 2022. "Robust cross-network node classification via constrained graph mutual information." Knowledge-Based Systems. 257. https://doi.org/10.1016/j.knosys.2022.109852
A survey on deep learning based knowledge tracing
Song, Xiangyu, Li, Jianxin, Cai, Taotao, Yang, Shuiqiao, Yang, Tingting and Liu, Chengfei. 2022. "A survey on deep learning based knowledge tracing." Knowledge-Based Systems. 258. https://doi.org/10.1016/j.knosys.2022.110036
Target-Aware Holistic Influence Maximization in Spatial Social Networks
Cai, Taotao, Li, Jianxin, Mian, Ajmal, Li, Rong-Hua, Sellis, Timos and Yu, Jeffrey Xu. 2022. "Target-Aware Holistic Influence Maximization in Spatial Social Networks ." IEEE Transactions on Knowledge and Data Engineering. 34 (4), pp. 1993-2007. https://doi.org/10.1109/TKDE.2020.3003047
Self-supervised cross-iterative clustering for unlabeled plant disease images
Fang, Uno, Li, J., Lu, X., Gao, Longxiang, Ali, Mumtaz and Xiang, Yong. 2021. "Self-supervised cross-iterative clustering for unlabeled plant disease images." Neurocomputing. 456, pp. 36-48. https://doi.org/10.1016/j.neucom.2021.05.066
Community-diversity Driven Influence Maximization on Social Networks
Li, Jianxin, Cai, Taotao, Ke, Deng, Wang, Xinjue, Sellis, Timos and Xia, Feng. 2020. "Community-diversity Driven Influence Maximization on Social Networks." Information Systems. 92. https://doi.org/10.1016/j.is.2020.101522
Anchor vertex selection for enhanced reliability of traffic offloading service in edge-enabled mobile P2P social networks
Zhang, Hengda, Wang, Xiaofei, Fan, Hao, Cai, Taotao, Li, Jianxin, Li, Xiuhua and Leung, Victor C. M.. 2020. "Anchor vertex selection for enhanced reliability of traffic offloading service in edge-enabled mobile P2P social networks." Journal of Communications and Information Networks. 5 (2), pp. 217-224. https://doi.org/10.23919/JCIN.2020.9130437
Anchored Vertex Exploration for Community Engagement in Social Networks
Cai, Taotao, Li, Jianxin, Hasan Haldar, Nur Al, Mian, Ajmal, Yearwood, John and Sellis, Timos. 2020. "Anchored Vertex Exploration for Community Engagement in Social Networks ." 2020 IEEE 36th International Conference on Data Engineering (ICDE). Dallas, United States 20 - 24 Apr 2020 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ICDE48307.2020.00042
Correlate Influential News Article Events to Stock Quote Movement
Mandalapu, Arun Chaitanya, Gunabalan, Saranya, Sadineni, Avinash, Cai, Taotao, Hasan, Nur Al Hasan and Li, Jianxin. 2019. "Correlate Influential News Article Events to Stock Quote Movement ." Li, Jianxin, Wang, Sen, Qin, Shaowen, Li, Xue and Wang, Shuliang (ed.) 15th International Conference on Advanced Data Mining and Applications. Dalian, China 21 - 23 Nov 2019 Switzerland. Springer. https://doi.org/10.1007/978-3-030-35231-8_24
Holistic Influence Maximization for Targeted Advertisements in Spatial Social Networks
Li, Jianxin, Cai, Taotao, Mian, Ajmal, Li, Rong-Hua, Sellis, Timos and Yu, Jeffrey Xu. 2018. "Holistic Influence Maximization for Targeted Advertisements in Spatial Social Networks ." 2018 IEEE 34th International Conference on Data Engineering (ICDE). Paris, France 16 - 19 Apr 2018 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ICDE.2018.00145
Efficient Distance-based Representative Skyline Computation in 2D Space
Mao, Rui, Cai, Taotao, Li, Rong-Hua, Yu, Jeffery Xu and Li, Jianxin. 2017. "Efficient Distance-based Representative Skyline Computation in 2D Space." World Wide Web. 20 (4), pp. 621-638. https://doi.org/10.1007/s11280-016-0406-0
Efficient Algorithms for Distance-Based Representative Skyline Computation in 2D Space
Cai, Taotao, Li, Rong-Hua, Yu, Jeffrey Xu, Mao, Rui and Cai, Yadi. 2015. "Efficient Algorithms for Distance-Based Representative Skyline Computation in 2D Space ." 17th Asia-Pacific Web Conference (APWeb2015). Guangzhou, China 18 - 20 Sep 2015 Switzerland . Springer. https://doi.org/10.1007/978-3-319-25255-1_10