Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science

Improving support vector machine level-based for person domain categorization

Authors
Lijuan Diao, Lei Cui, Xijie Wang
Corresponding Author
Lijuan Diao
Available Online May 2014.
DOI
https://doi.org/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.
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Proceedings
International Conference on Logistics Engineering, Management and Computer Science (LEMCS 2014)
Part of series
Advances in Intelligent Systems Research
Publication Date
May 2014
ISBN
978-94-6252-010-3
ISSN
1951-6851
DOI
https://doi.org/10.2991/lemcs-14.2014.233How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - International Conference on Logistics Engineering, Management and Computer Science (LEMCS 2014)
PB  - Atlantis Press
SP  - 1043
EP  - 1047
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-14.2014.233
DO  - https://doi.org/10.2991/lemcs-14.2014.233
ID  - Diao2014/05
ER  -