Development of Valuable Users Identification model in Online Education Communities Based on Optimal Removal Strategy

DOI

10.2991/iccse-16.2016.18How to use a DOI?

Keywords

Valuable users, Online education communities, Removal strategy, Tabu search

Abstract

The valuable users in online education communities identification model has broad applications and recently has received growing attention. This paper first presents an optimized removal strategy model for online education communities, and the network performance is quantitatively measured by the size of the largest connected component and " ". Here, we introduce the tabu search into the optimal removal strategy problem to identify the valuable users. The efficiency of the proposed solution was verified by comparing it with other removal strategies used in real-world networks. Numerical experiments suggest that our solution can find the most valuable users for node failure removals, and it can be identified through global searches. Our understanding of the optimal removal strategy may also shed light on an incentive mechanism for active users and deserves additional study.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Yu Bai
AU  - Gang Yin
AU  - Huaimin Wang
AU  - Ye Deng
PY  - 2016/10
DA  - 2016/10
TI  - Development of Valuable Users Identification model in Online Education Communities Based on Optimal Removal Strategy
BT  - Proceedings of the 2016 International Conference on Computational Science and Engineering (ICCSE 2016)
PB  - Atlantis Press
SP  - 105
EP  - 112
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccse-16.2016.18
DO  - 10.2991/iccse-16.2016.18
ID  - Bai2016/10
ER  -