Target-Aware Holistic Influence Maximization in Spatial Social Networks
Article
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
| Article Title | Target-Aware Holistic Influence Maximization in Spatial Social Networks |
|---|---|
| ERA Journal ID | 17876 |
| Article Category | Article |
| Authors | Cai, Taotao, Li, Jianxin, Mian, Ajmal, Li, Rong-Hua, Sellis, Timos and Yu, Jeffrey Xu |
| Journal Title | IEEE Transactions on Knowledge and Data Engineering |
| Journal Citation | 34 (4), pp. 1993-2007 |
| Number of Pages | 15 |
| Year | 2022 |
| Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
| Place of Publication | United States |
| ISSN | 1041-4347 |
| 1558-2191 | |
| Digital Object Identifier (DOI) | https://doi.org/10.1109/TKDE.2020.3003047 |
| Web Address (URL) | https://ieeexplore.ieee.org/document/9119847 |
| Abstract | Influence maximization has recently received significant attention for scheduling online campaigns or advertisements on social network platforms. However, most studies only focus on user influence via cyber interactions while ignoring their physical interactions which are also essential to gauge influence propagation. Additionally, targeted campaigns or advertisements have not received sufficient attention. To address these issues, we first devise a novel holistic influence diffusion model that takes into account both cyber and physical user interactions in an effective and practical way. Based on the new diffusion model, we formulate a new problem of holistic influence maximization , denoted as HIM query, for targeted advertisements in a spatial social network. The HIM query problem aims to find a minimum set of users whose holistic influence can cover all target users in the network, which belongs to a set covering problem. Since the HIM query problem is NP-hard, we develop a greedy baseline algorithm and then improve on this algorithm to reduce the computational cost. To deal with large networks, we also design a spatial-social index to maintain the social, spatial and textual information of users, as well as developing an index-based efficient solution. Finally, we conduct extensive experiments using one synthetic and three real-world datasets to validate the efficiency and effectiveness of the proposed holistic influence diffusion model and our developed algorithms. |
| Keywords | Holistic influence maximization |
| Related Output | |
| Is supplemented by | https://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/LP180100750 |
| Is supplemented by | https://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/DP190102443 |
| Contains Sensitive Content | Does not contain sensitive content |
| ANZSRC Field of Research 2020 | 460503. Data models, storage and indexing |
| Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
| Byline Affiliations | Deakin University |
| University of Western Australia | |
| Beijing Institute of Technology, China | |
| Swinburne University of Technology | |
| Chinese University of Hong Kong, China |
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