DocumentCode
1660471
Title
The Field of Automatic Entity Relation Extraction Based on Binary Classifier and Reasoning
Author
Lei, Chun-ya ; Guo, Jian-yi ; Yu, Zheng-tao ; Zhang, Shao-min ; Mao, Cun-li ; Zhang, Chao-shen
Author_Institution
Sch. of Inf. Eng. & Autom., Kunming Univ. of Sci. & Technol., Kunming, China
fYear
2010
Firstpage
327
Lastpage
331
Abstract
To solve the difficulty of the field of Automatic Entity Relation Extraction, in this paper, a method that used binary classification thinking, meanwhile combined with reasoning rules to extract the field of entity relation is proposed. considering comprehensively the context information of entity, entity type and their combination of characteristics to construct the feature set, which in order to build the Binary Classifier of entity relation extraction, then taking full advantage of the field characteristics of entity relation, further combine reasoning rules to obtain the type of the field of entity relation. Doing our experiment on the artificial collection of 600 corpuses for tourism field, experimental result shows the method of Binary Classifier combining Reasoning is better than Multiple Classifiers, the F-score is improved 3%.
Keywords
feature extraction; inference mechanisms; information retrieval; pattern classification; automatic entity relation extraction; binary classifier; feature set; reasoning rules; Classification algorithms; Cognition; Data mining; Entropy; Feature extraction; Snow; Training; binary classifier; features; filed of entity relation; multiple classifier; reasoning;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Processing (ISIP), 2010 Third International Symposium on
Conference_Location
Qingdao
Print_ISBN
978-1-4244-8627-4
Type
conf
DOI
10.1109/ISIP.2010.40
Filename
5669065
Link To Document