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Open Access

Node Search Contributions Based Long-Term Follow-Up Specific Individual Searching Model

School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100183, China
Institute for Hospital Management Research, Chinese PLA General Hospital, Beijing 100853, China

Yayong Shi and Fei Chang contributed equally to this work.

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Abstract

In this paper, we introduce a long-term follow-up specific individual searching (SIS) model. This model introduces the concept of node search contributions by considering the characteristics of the network structure. A node search contribution indicates the ability of a certain node to correctly guide the search path and successfully complete an SIS. The influencing factors of node search contributions have three components: the individual influence index, attribute similarity, and node search willingness. On the basis of node search contributions and the PeopleRank idea, this paper proposes an SIS model based on node search contribution values and conducts comparison experiments with several mainstream SIS algorithms in three aspects: the search failure rate, the minimum number of search hops, and the search size. The experimental results verify the advanced nature and operability of the model proposed in this paper, which presents theoretical and practical significance to the quantitative study of the SIS process.

Keywords

specific individual searchcomplex networkspropagation dynamicslong-term follow-up

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Tsinghua Science and Technology
Volume 28 Issue 4,
August 2023
Pages 729-742
DOI: 10.26599/TST.2022.9010021
Cite this article:
Shi Y, Chang F, Sun Y, et al. Node Search Contributions Based Long-Term Follow-Up Specific Individual Searching Model. Tsinghua Science and Technology, 2023, 28(4): 729-742. https://doi.org/10.26599/TST.2022.9010021

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Received: 22 January 2022
Accepted: 16 June 2022
Published: 06 January 2023
© The author(s) 2023.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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