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相关论文: Budgeted Influence and Earned Benefit Maximization…

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Given a social network with nonuniform selection cost of the users, the problem of \textit{Budgeted Influence Maximization} (BIM in short) asks for selecting a subset of the nodes within an allocated budget for initial activation, such that…

社会与信息网络 · 计算机科学 2020-04-09 Suman Banerjee , Mamata Jenamani , Dilip Kumar Pratihar

Given a budget and arbitrary cost for selecting each node, the budgeted influence maximization (BIM) problem concerns selecting a set of seed nodes to disseminate some information that maximizes the total number of nodes influenced (termed…

社会与信息网络 · 计算机科学 2013-01-23 Huy Nguyen , Rong Zheng

Due to much closer to real application scenarios,the budgeted influence maximization (BIM) problem has attracted great attention among researchers. As a variant of the influence maximization (IM) problem, the BIM problem aims at mining…

社会与信息网络 · 计算机科学 2022-03-23 Jianshe Wu , Junjun Gao , Hongde Zhu , Zulei Zhang

Given a social network of users with selection cost, the \textsc{Budgeted Influence Maximization Problem} (\emph{BIM Problem} in short) asks for selecting a subset of the nodes (known as \emph{seed nodes}) within an allocated budget for…

社会与信息网络 · 计算机科学 2021-04-15 Suman Banerjee

Influence maximization (IM) seeks to identify a seed set that maximizes influence within a network, with applications in areas such as viral marketing, disease control, and political campaigns. The budgeted influence maximization (BIM)…

社会与信息网络 · 计算机科学 2024-10-08 Su-Su Zhang , Chuang Liu , Huijuan Wang , Yang Chen , Xiu-Xiu Zhan

Given a social network with diffusion probabilities as edge weights and an integer k, which k nodes should be chosen for initial injection of information to maximize influence in the network? This problem is known as Target Set Selection in…

社会与信息网络 · 计算机科学 2018-08-17 Suman Banerjee , Mamata Jenamani , Dilip Kumar Pratihar

Influence maximization (IM) is the problem of identifying a limited number of initial influential users within a social network to maximize the number of influenced users. However, previous research has mostly focused on individual…

社会与信息网络 · 计算机科学 2024-03-29 Zirui Yuan , Minglai Shao , Zhiqian Chen

The well-known influence maximization problem aims at maximizing the influence of one information cascade in a social network by selecting appropriate seed users prior to the diffusion process. In its adaptive version, additional seed users…

社会与信息网络 · 计算机科学 2020-03-30 Guangmo Tong , Ruiqi Wang , Zheng Dong , Xiang Li

Influence maximization is the problem of finding a set of influential users in a social network such that the expected spread of influence under a certain propagation model is maximized. Much of the previous work has neglected the important…

社会与信息网络 · 计算机科学 2016-11-18 Wei Lu , Laks V. S. Lakshmanan

We consider the problem of selecting a seed set to maximize the expected number of influenced nodes in the social network, referred to as the \textit{influence maximization} (IM) problem. We assume that the topology of the social network is…

机器学习 · 计算机科学 2019-11-26 Xiaojin Zhang

In the context of influence propagation in a social graph, we can identify three orthogonal dimensions - the number of seed nodes activated at the beginning (known as budget), the expected number of activated nodes at the end of the…

离散数学 · 计算机科学 2011-11-08 Amit Goyal , Francesco Bonchi , Laks V. S. Lakshmanan , Suresh Venkatasubramanian

Social networks are commonly used for marketing purposes. For example, free samples of a product can be given to a few influential social network users (or "seed nodes"), with the hope that they will convince their friends to buy it. One…

社会与信息网络 · 计算机科学 2019-01-17 Siyu Lei , Silviu Maniu , Luyi Mo , Reynold Cheng , Pierre Senellart

Influence Maximization (IM) aims to maximize the number of people that become aware of a product by finding the `best' set of `seed' users to initiate the product advertisement. Unlike prior arts on static social networks containing fixed…

社会与信息网络 · 计算机科学 2019-11-14 Xudong Wu , Luoyi Fu , Zixin Zhang , Jingfan Meng , Xinbing Wang , Guihai Chen

The typical algorithmic problem in viral marketing aims to identify a set of influential users in a social network, who, when convinced to adopt a product, shall influence other users in the network and trigger a large cascade of adoptions.…

机器学习 · 计算机科学 2014-04-17 Nan Du , Yingyu Liang , Maria Florina Balcan , Le Song

Research on influence maximization has often to cope with marketing needs relating to the propagation of information towards specific users. However, little attention has been paid to the fact that the success of an information diffusion…

社会与信息网络 · 计算机科学 2018-04-23 Antonio Caliò , Roberto Interdonato , Chiara Pulice , Andrea Tagarelli

The majority of influence maximization (IM) studies focus on targeting influential seeders to trigger substantial information spread in social networks. In this paper, we consider a new and complementary problem of how to further increase…

社会与信息网络 · 计算机科学 2017-06-27 Yishi Lin , Wei Chen , John C. S. Lui

Influence maximization (IM) aims to identify a small number of influential individuals to maximize the information spread and finds applications in various fields. It was first introduced in the context of viral marketing, where a company…

社会与信息网络 · 计算机科学 2023-06-06 Shiqi Zhang , Yiqian Huang , Jiachen Sun , Wenqing Lin , Xiaokui Xiao , Bo Tang

How to utilize an allocated budget effectively for branding and promotion of a commercial house is an important problem, particularly when multiple advertising media are available. There exist multiple such media, and among them, two…

数据结构与算法 · 计算机科学 2026-04-02 Dildar Ali , Ansh Jasrotia , Abishek Salaria , Suman Banerjee

Influence maximization is the problem of finding influential users, or nodes, in a graph so as to maximize the spread of information. It has many applications in advertising and marketing on social networks. In this paper, we study a highly…

社会与信息网络 · 计算机科学 2017-10-25 Paul Lagrée , Olivier Cappé , Bogdan Cautis , Silviu Maniu

Influence maximization is the problem of finding a set of users in a social network, such that by targeting this set, one maximizes the expected spread of influence in the network. Most of the literature on this topic has focused…

数据库 · 计算机科学 2011-10-03 Amit Goyal , Francesco Bonchi , Laks V. S. Lakshmanan
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