Knowledge transfer in homogeneous networks with consideration of self-learning mechanism

Haiying Wang; Jun Wang

doi:10.1109/INFOMAN.2017.7950365

Knowledge transfer in homogeneous networks with consideration of self-learning mechanism

Haiying Wang
, Jun Wang

School of Economics and Management

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Depending on the fact that knowledge can be learned by oneself, which is different from epidemic spreading, we take into account self-learning mechanism in the knowledge transfer process. In this paper, we propose a knowledge transfer model, and derive the mean-field equations that describe the dynamics of the knowledge transfer in homogeneous networks. Using differential theory, we obtain the knowledge transfer threshold and solution of the mean-field equations. Both the solution and threshold are closely related with self-learning rate. In addition, numerical simulations are performed to verify the reasonability of the theoretical analysis. The results indicate that the self-learning mechanism have obvious promoting effect on the knowledge transfer in homogeneous networks.

Original language	English
Title of host publication	2017 3rd International Conference on Information Management, ICIM 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	149-153
Number of pages	5
ISBN (Electronic)	9781509063048
DOIs	https://doi.org/10.1109/INFOMAN.2017.7950365
State	Published - 15 Jun 2017
Event	3rd International Conference on Information Management, ICIM 2017 - Chengdu, China Duration: 21 Apr 2017 → 23 Apr 2017

Publication series

Name	2017 3rd International Conference on Information Management, ICIM 2017

Conference

Conference	3rd International Conference on Information Management, ICIM 2017
Country/Territory	China
City	Chengdu
Period	21/04/17 → 23/04/17

Keywords

Homogeneous networks
Knowledge transfer
Self-learning
Threshold

Access to Document

10.1109/INFOMAN.2017.7950365

Cite this

Wang, H., & Wang, J. (2017). Knowledge transfer in homogeneous networks with consideration of self-learning mechanism. In 2017 3rd International Conference on Information Management, ICIM 2017 (pp. 149-153). Article 7950365 (2017 3rd International Conference on Information Management, ICIM 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INFOMAN.2017.7950365

@inproceedings{adad4381ff0547778f25269185e657a7,

title = "Knowledge transfer in homogeneous networks with consideration of self-learning mechanism",

abstract = "Depending on the fact that knowledge can be learned by oneself, which is different from epidemic spreading, we take into account self-learning mechanism in the knowledge transfer process. In this paper, we propose a knowledge transfer model, and derive the mean-field equations that describe the dynamics of the knowledge transfer in homogeneous networks. Using differential theory, we obtain the knowledge transfer threshold and solution of the mean-field equations. Both the solution and threshold are closely related with self-learning rate. In addition, numerical simulations are performed to verify the reasonability of the theoretical analysis. The results indicate that the self-learning mechanism have obvious promoting effect on the knowledge transfer in homogeneous networks.",

keywords = "Homogeneous networks, Knowledge transfer, Self-learning, Threshold",

author = "Haiying Wang and Jun Wang",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 3rd International Conference on Information Management, ICIM 2017 ; Conference date: 21-04-2017 Through 23-04-2017",

year = "2017",

month = jun,

day = "15",

doi = "10.1109/INFOMAN.2017.7950365",

language = "英语",

series = "2017 3rd International Conference on Information Management, ICIM 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "2017 3rd International Conference on Information Management, ICIM 2017",

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}

Wang, H & Wang, J 2017, Knowledge transfer in homogeneous networks with consideration of self-learning mechanism. in 2017 3rd International Conference on Information Management, ICIM 2017., 7950365, 2017 3rd International Conference on Information Management, ICIM 2017, Institute of Electrical and Electronics Engineers Inc., pp. 149-153, 3rd International Conference on Information Management, ICIM 2017, Chengdu, China, 21/04/17. https://doi.org/10.1109/INFOMAN.2017.7950365

Knowledge transfer in homogeneous networks with consideration of self-learning mechanism. / Wang, Haiying; Wang, Jun.
2017 3rd International Conference on Information Management, ICIM 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 149-153 7950365 (2017 3rd International Conference on Information Management, ICIM 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Knowledge transfer in homogeneous networks with consideration of self-learning mechanism

AU - Wang, Haiying

AU - Wang, Jun

PY - 2017/6/15

Y1 - 2017/6/15

N2 - Depending on the fact that knowledge can be learned by oneself, which is different from epidemic spreading, we take into account self-learning mechanism in the knowledge transfer process. In this paper, we propose a knowledge transfer model, and derive the mean-field equations that describe the dynamics of the knowledge transfer in homogeneous networks. Using differential theory, we obtain the knowledge transfer threshold and solution of the mean-field equations. Both the solution and threshold are closely related with self-learning rate. In addition, numerical simulations are performed to verify the reasonability of the theoretical analysis. The results indicate that the self-learning mechanism have obvious promoting effect on the knowledge transfer in homogeneous networks.

AB - Depending on the fact that knowledge can be learned by oneself, which is different from epidemic spreading, we take into account self-learning mechanism in the knowledge transfer process. In this paper, we propose a knowledge transfer model, and derive the mean-field equations that describe the dynamics of the knowledge transfer in homogeneous networks. Using differential theory, we obtain the knowledge transfer threshold and solution of the mean-field equations. Both the solution and threshold are closely related with self-learning rate. In addition, numerical simulations are performed to verify the reasonability of the theoretical analysis. The results indicate that the self-learning mechanism have obvious promoting effect on the knowledge transfer in homogeneous networks.

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KW - Knowledge transfer

KW - Self-learning

KW - Threshold

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DO - 10.1109/INFOMAN.2017.7950365

M3 - 会议稿件

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BT - 2017 3rd International Conference on Information Management, ICIM 2017

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Wang H, Wang J. Knowledge transfer in homogeneous networks with consideration of self-learning mechanism. In 2017 3rd International Conference on Information Management, ICIM 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 149-153. 7950365. (2017 3rd International Conference on Information Management, ICIM 2017). doi: 10.1109/INFOMAN.2017.7950365

Knowledge transfer in homogeneous networks with consideration of self-learning mechanism

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Keywords

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