Results 31 to 40 of about 6,507,474 (284)
Geodemographic Influence Maximization
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020 Given a set of locations in a city, on which ones should we place ads on so as to reach as many people as possible within a limited budget? Past research has addressed this question under the assumption that dense trajectory data are available to determine the reach of each ad.
Zhang, Kaichen +5 more
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cognitivefactory/features-maximization-metric
, 2023 Release 0.1.0 of cognitivefactory/features-maximization-metric package. GitHub repository : https://github.com/cognitivefactory/features-maximization-metric/tree/0.1.0 Main documentation : https://cognitivefactory.github.io/features-maximization-metric/
Schild, Erwan
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Context-based influence maximization with privacy protection in social networks
EURASIP Journal on Wireless Communications and Networking, 2019 As the increase of requirements of accessing and sharing information of people, large social networks have appeared. The influence maximization over social network has been a popular research topic, whose goal is to maximize the expected range of ...
Dong Jing, Ting Liu
doaj +1 more source
Knapsack-Based Reverse Influence Maximization for Target Marketing in Social Networks
IEEE Access, 2019 With the dramatic proliferation in recent years, the social networks have become a ubiquitous medium of marketing and the influence maximization (IM) technique, being such a viral marketing tool, has gained significant research interest in recent years ...
Ashis Talukder +4 more
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CIM: Community-Based Influence Maximization in Social Networks [PDF]
, 2014 Given a social graph, the problem of influence maximization is to determine a set of nodes that maximizes the spread of influences. While some recent research has studied the problem of influence maximization, these works are generally too time consuming
Chen, Yi-Cheng; Peng, Wen-Chih; Lee, Wan-Chien; Lee, Suh-Yin
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Near-Optimal Convergent Approach for Composed Influence Maximization Problem in Social Networks
IEEE Access, 2019 Crowd psychology is a critical factor when considering information diffusion, which has been modeled as composed influence. The composed influence is represented as a hyperedge in a graph model.
Jianming Zhu +3 more
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Holistic Influence Maximization for Targeted Advertisements in Spatial Social Networks
, 2018 The problem of influence maximization has recently received significant attention. However, most studies focused on user influence via cyber interactions while ignoring their physical interactions which are important to gauge influence propagation ...
Ajmal Mian +11 more
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Modeling and maximizing influence diffusion in social networks for viral marketing
Applied Network Science, 2018 Modeling influence diffusion in social networks is an important challenge. We investigate influence-diffusion modeling and maximization in the setting of viral marketing, in which a node’s influence is measured by the number of nodes it can activate to ...
Wenjun Wang, W. Nick Street
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Big Data Mining and Analytics, 2022 Online social networks are increasingly connecting people around the world. Influence maximization is a key area of research in online social networks, which identifies influential users during information dissemination.
Jie Tong +4 more
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Multi-task Learning for Influence Estimation and Maximization [PDF]
, 2020 International audienceWe address the problem of influence maximization when the social network is accompanied by diffusion cascades. In the literature, such information is used to compute influence probabilities, which is utilized by stochastic diffusion
Vazirgiannis, Michalis +4 more
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