Text Classification Method Based on Machine Learning and Domain Knowledge Ontology

DOI

10.2991/msota-16.2016.74How to use a DOI?

Keywords

machine learning; ontology; text classification

Abstract

The use of machine learning method is discussed herein to produce a corpus by domain knowledge ontology and conduct text classification according to the ontology of professional knowledge domain. Nowadays, a large number of literature materials have been accumulated in each professional field, and it is still in rapid growth. This constitutes a great challenge for researchers in various fields. To be specific, not only the workload in literature retrieval and reading is constantly increased, but also the work efficiency of the study is affected. In this paper, ontology is taken as the text feature extractor for storage, processing, classification and retrieval through ontology development tools Prot,g,, Jena and natural language processing tool NLTK, so as to facilitate the researcher for literature retrieval and reading. The advantage of this text classification method lies in that category structure is no longer a single tree structure, but instead, different categories may intersect and new category may be grouped by themselves.

Copyright

© 2017, 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  - Zhiyong Gao
AU  - Shuhan Qiao
AU  - Yongquan Liang
PY  - 2016/12
DA  - 2016/12
TI  - Text Classification Method Based on Machine Learning and Domain Knowledge Ontology
BT  - Proceedings of 2016 International Conference on Modeling, Simulation and Optimization Technologies and Applications (MSOTA2016)
PB  - Atlantis Press
SP  - 344
EP  - 347
SN  - 2352-538X
UR  - https://doi.org/10.2991/msota-16.2016.74
DO  - 10.2991/msota-16.2016.74
ID  - Gao2016/12
ER  -