Text Fragment Recovery Method Based on Imperial Competition Algorithm

DOI

10.2991/ncce-18.2018.111How to use a DOI?

Keywords

Imperial Competition Algorithm; K-MEANS clustering; text fragment splicing.

Abstract

In this paper, a text fragment splicing method based on K-means and Empire competition algorithm is proposed. First, use K-means clustering to find out a piece of paper that belongs to one line; Then, define the edge distance of the paper, and establish a combined optimization model; using the imperial competition algorithm to optimize the solution. The experimental results show that the speed and accuracy of this algorithm are improved compared with the literature algorithm and have certain application value.

Copyright

© 2018, 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/).

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TY  - CONF
AU  - Dongyu Guo
AU  - Zeyuan Tao
PY  - 2018/05
DA  - 2018/05
TI  - Text Fragment Recovery Method Based on Imperial Competition Algorithm
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 675
EP  - 680
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.111
DO  - 10.2991/ncce-18.2018.111
ID  - Guo2018/05
ER  -