☆ 4.6 Article

Influence maximization algorithm based on group trust and local topology structure

NEUROCOMPUTING (2024)

Related references

Note: Only part of the references are listed.

Article Computer Science, Information Systems

An influence maximization method based on crowd emotion under an emotion-based attribute social network

Weimin Li et al.

Summary: This paper introduces a novel approach for attributed influence maximization based on crowd emotion, aiming to analyze the impact of multi-dimensional characteristics on information propagation. The algorithm's effectiveness is demonstrated through experiments on real-world datasets, showing superior performance compared to heuristic methods with improved time efficiency.

INFORMATION PROCESSING & MANAGEMENT (2022)

Add to Collection

Article Computer Science, Artificial Intelligence

Collaborative representation learning for nodes and relations via heterogeneous graph neural network

Weimin Li et al.

Summary: This paper proposes a new heterogeneous graph neural network model called CoNR for link prediction task. The model learns node representations and relation representations collaboratively to improve the performance of downstream tasks.

KNOWLEDGE-BASED SYSTEMS (2022)

Add to Collection

Article Computer Science, Artificial Intelligence

Neighborhood Matters: Influence Maximization in Social Networks With Limited Access

Chen Feng et al.

Summary: This paper proposes an adaptive approach to solve the limited influence maximization problem in real-world scenarios, taking into account seeding and diffusion uncertainty. By studying the set-wise friendship paradox phenomenon, a two-stage seeding model with the paradox embedded is presented. The adaptive submodularity and submodularity of the influence spread function in two stages are proven, and a series of adaptive greedy algorithms are proposed with constant approximation ratio. Extensive experiments show that the adaptive algorithms achieve larger influence spread compared to non-adaptive and other adaptive algorithms (up to a maximum of 116 percent).

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2022)

Add to Collection

Article Computer Science, Artificial Intelligence

Information diffusion across cyber-physical-social systems in smart city: A survey

Xiaokang Zhou et al.

Summary: Smart cities utilize information technology to integrate city systems and functions for better management and services. The paper treats smart cities as Cyber-Physical-Social Systems (CPSS) and focuses on information diffusion within CPSS, covering its features, applications in smart city field, and critical technologies. The research also identifies open issues, challenges, and potential future directions for information diffusion in smart city CPSS.

NEUROCOMPUTING (2021)

Add to Collection

Article Computer Science, Artificial Intelligence

An improved gravity model to identify influential nodes in complex networks based on k-shell method

Xuan Yang et al.

Summary: This study introduces an improved gravity centrality measure KSGC based on the k-shell algorithm, which can effectively evaluate the importance of nodes in complex networks.

KNOWLEDGE-BASED SYSTEMS (2021)

Add to Collection

Article Computer Science, Information Systems

Three-hop velocity attenuation propagation model for influence maximization in social networks

Weimin Li et al.

WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS (2020)

Add to Collection

Article Physics, Fluids & Plasmas

Influence maximization on temporal networks

Sirag Erkol et al.

PHYSICAL REVIEW E (2020)

Add to Collection

Article Computer Science, Information Systems

Influence Maximization in Independent Cascade Networks Based on Activation Probability Computation

Wenjing Yang et al.

IEEE ACCESS (2019)

Add to Collection

Article Computer Science, Artificial Intelligence

Influence maximization in social networks based on TOPSIS

Ahmad Zareie et al.

EXPERT SYSTEMS WITH APPLICATIONS (2018)

Add to Collection

Article Computer Science, Information Systems

An efficient and effective hop-based approach for influence maximization in social networks

Jing Tang et al.

SOCIAL NETWORK ANALYSIS AND MINING (2018)

Add to Collection

Article Computer Science, Artificial Intelligence

Continuous states latency aware influence maximization in social networks

Rezvan MohamadiBaghmolaei et al.

AI COMMUNICATIONS (2017)

Add to Collection

Article Computer Science, Information Systems

Information diffusion in online social networks

Adrien Guille et al.

SIGMOD RECORD (2013)

Add to Collection

Article Physics, Multidisciplinary

Identification of influential spreaders in complex networks

Maksim Kitsak et al.

NATURE PHYSICS (2010)

Add to Collection

Article Physics, Condensed Matter

Betweenness centrality in large complex networks

M Barthélemy

EUROPEAN PHYSICAL JOURNAL B (2004)

Add to Collection

Article Anthropology

Eigenvector-centrality - a node-centrality?

B Ruhnau

SOCIAL NETWORKS (2000)

Add to Collection

© Peeref 2019-2024. All rights reserved.