Research on the Removing Overlapping Ambiguity of Chinese Segmentation based on the Granular Computing model of Ontology

DOI

10.2991/iccmcee-15.2015.207How to use a DOI?

Keywords

Concept, Ontology, Granular Computing, Difference of t- test, overlapping ambiguity.

Abstract

The word as the smallest language unit has its own independent concept. Human beings learn language through understanding semantics. This paper proposed a Granular Computing model based on Ontology, to restrict the concept of word and word, the use of Granular Computing similar ideas as well as human stratification and difference of t-test statistics method, the paper mainly studies the Chinese segmentation in overlapping ambiguity. The feasibility and effectiveness of the proposed model and the computational method are demonstrated by simulation experiments.

Copyright

© 2015, 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  - FanJin Mai
AU  - Gen Zhang
PY  - 2015/11
DA  - 2015/11
TI  - Research on the Removing Overlapping Ambiguity of Chinese Segmentation based on the Granular Computing model of Ontology
BT  - Proceedings of the 2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering
PB  - Atlantis Press
SP  - 1096
EP  - 1100
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccmcee-15.2015.207
DO  - 10.2991/iccmcee-15.2015.207
ID  - Mai2015/11
ER  -