Title
CN-Probase: A Data-driven Approach for Large-scale Chinese Taxonomy Construction.
Abstract
Taxonomies play an important role in machine intelligence. However, most well-known taxonomies are in English, and non-English taxonomies, especially Chinese ones, are still very rare. In this paper, we focus on automatic Chinese taxonomy construction and propose an effective generation and verification framework to build a large-scale and high-quality Chinese taxonomy. In the generation module, we extract isA relations from multiple sources of Chinese encyclopedia, which ensures the coverage. To further improve the precision of taxonomy, we apply three heuristic approaches in verification module. As a result, we construct the largest Chinese taxonomy with high precision about 95% called CN-Probase. Our taxonomy has been deployed on Aliyun, with over 82 million API calls in six months.
Year
DOI
Venue
2019
10.1109/ICDE.2019.00178
2019 IEEE 35th International Conference on Data Engineering (ICDE)
Keywords
DocType
Volume
Taxonomy,Encyclopedias,Compounds,Binary trees,Noise measurement,Conferences,Data engineering
Conference
abs/1902.10326
ISSN
ISBN
Citations 
1084-4627
978-1-5386-7474-1
1
PageRank 
References 
Authors
0.36
0
8
Name
Order
Citations
PageRank
Jindong Chen118726.83
Ao Wang210.36
Jiangjie Chen311.37
Yanghua Xiao448254.90
Zhendong Chu510.36
Jingping Liu633.43
Jiaqing Liang7379.59
Wei Wang87122746.33