A fast algorithm for finding most influential people based on the linear threshold model

被引：87

作者：

Rahimkhani, Khadije ^{[1
]}

Aleahmad, Abolfazl ^{[1
]}

Rahgozar, Maseud ^{[1
]}

Moeini, Ali ^{[2
]}

机构：

[1] Univ Tehran, Control & Intelligent Proc Ctr Excellence, Sch Elect & Comp Engn, Database Res Grp, Tehran 14174, Iran

[2] Univ Tehran, Fac Engn Sci, Sch Engn, Tehran 14174, Iran

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2015年 / 42卷 / 03期

关键词：

Social networks; Influential people retrieval; Influence maximization; Linear threshold model; INFLUENCE MAXIMIZATION; COMPLEXITY;

D O I：

10.1016/j.eswa.2014.09.037

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Finding the most influential people is an NP-hard problem that has attracted many researchers in the field of social networks. The problem is also known as influence maximization and aims to find a number of people that are able to maximize the spread of influence through a target social network. In this paper, a new algorithm based on the linear threshold model of influence maximization is proposed. The main benefit of the algorithm is that it reduces the number of investigated nodes without loss of quality to decrease its execution time. Our experimental results based on two well-known datasets show that the proposed algorithm is much faster and at the same time more efficient than the state of the art algorithms. (C) 2014 Elsevier Ltd. All rights reserved.

引用

页码：1353 / 1361

页数：9

共 50 条

[1] Finding the Most Influential Parameters of Coalitions in a PSO-CO Algorithm
Ruiz, Patricia
Dorronsoro, Bernabe
Carlos de la Torre, Juan
Carlos Burguillo, Juan
INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS: APPLICATIONS, IPMU 2018, PT III, 2018, 855 : 284 - 296
[2] FAST ALGORITHM FOR FINDING A FOREST OF A LINEAR GRAPH
JOVANOVICH, AD
CHOBELJICH, SN
ELECTRONICS LETTERS, 1973, 9 (21) : 504 - 505
[3] Development of a Linear Regression Model Based on the Most Influential Predictors for a Research Office Cooling Load
Mutombo, Ntumba Marc-Alain
Numbi, Bubele Papy
ENERGIES, 2022, 15 (14)
[4] Tuned Linear Threshold Model for Tracking Influential Node in Social Network
Kumar, P. Vimal
Balasubramanian, C.
IETE JOURNAL OF RESEARCH, 2024,
[5] Threshold Estimation Models for Linear Threshold-Based Influential User Mining in Social Networks
Talukder, Ashis
Alam, Md Golam Rabiul
Tran, Nguyen H.
Niyato, Dusit
Park, Gwan Hoon
Hong, Choong Seon
IEEE ACCESS, 2019, 7 : 105441 - 105461
[6] Selecting Influential Features by a Learnable Content-Aware Linear Threshold Model
Khurana, Ansh
Logins, Alvis
Karras, Panagiotis
CIKM '20: PROCEEDINGS OF THE 29TH ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT, 2020, : 635 - 644
[7] Influence Maximization Algorithm for Dynamic Social Networks Based on Linear Threshold Model
Zhu J.
Li Y.
Wang Y.
Yang Y.
Gongcheng Kexue Yu Jishu/Advanced Engineering Sciences, 2019, 51 (01): : 181 - 188
[8] SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging
Sagadeeva, Svetlana
Boehm, Matthias
SIGMOD '21: PROCEEDINGS OF THE 2021 INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, 2021, : 2290 - 2299
[9] An algorithm for finding most likely explanations in valuation based systems
Wierzchon, ST
Klopotek, MA
CONTROL AND CYBERNETICS, 2000, 29 (04): : 921 - 936
[10] Algorithm for Finding Influential User: Based on User's Information Diffusion Region
Namtirtha, Amrita
Gupta, Shaswat
Dutta, Animesh
Dutta, Biswanath
Coenen, Frans
PROCEEDINGS OF THE 2016 IEEE REGION 10 CONFERENCE (TENCON), 2016, : 2734 - 2738

← 1 2 3 4 5 →