Bag-of-features for clustering online handwritten mathematical expressions

被引：0
|
作者：
Ung, Huy Quang [1 ]
Khuong, Vu Tran Minh [1 ]
Le, Anh Duc [1 ]
Nguyen, Cuong Tuan [1 ]
Nakagawa, Masaki [1 ]
机构：
[1] Tokyo Univ Agr & Technol, Dept Comp & Informat Sci, Tokyo, Japan
来源：
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE (ICPRAI 2018) | 2018年
关键词：
clustering; handwritten mathematical expressions; computer-assisted marking; bag-of-features; online patterns; SYSTEM;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents clustering of online handwritten mathematical expressions (HMEs) to help human markers to mark them efficiently and reliably. We propose bag-of-features from online handwritten mathematical expressions. It consists of 6 levels of features from low-level pattern features to high-level symbolic and structural features which are obtained from recognizing online HMEs. Experiments are conducted on our dataset. The best clustering result is 0.9185 for purity, which is obtained by applying the combination of both low-level and high-level features with the k-means++ algorithm.
引用
收藏
页码：127 / 132
页数：6
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