Improving support vector machine level-based for person domain categorization

DOI

10.2991/lemcs-14.2014.233How to use a DOI?

Keywords

KNN DAG-SVM KNN-DAG-SVM TFIDF

Abstract

Classification technology refers to assigning of one or more suitable categories from multiple categories data sets. While previous work in classification focused on single classifier, we propose classification method of improving support vector machine level-based that can classify multiple categories. Actually, we use the weight calculation method of TFIDF and combine DAG-SVM and KNN algorithm to improve precise of classification. An experiment has been carried out to measure the performance of our proposed classification method. The results show that our method performs better for person domain data set comparing with single DAG-SVM method.

Copyright

© 2014, 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  - Lijuan Diao
AU  - Lei Cui
AU  - Xijie Wang
PY  - 2014/05
DA  - 2014/05
TI  - Improving support vector machine level-based for person domain categorization
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 1043
EP  - 1047
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-14.2014.233
DO  - 10.2991/lemcs-14.2014.233
ID  - Diao2014/05
ER  -