DocumentCode
525414
Title
An area concept extraction algorithm based on association rule
Author
Yang, Qing ; Cai, Kai-min ; Li, Yan ; Liu, Rui-qing
Author_Institution
Dept. of Comput. Sci., Hua Zhong Normal Univ., Wuhan, China
Volume
3
fYear
2010
fDate
25-27 June 2010
Abstract
Ontology learning is from a given area document sets automatic or semi-automatic extraction terms to construct a domain ontology. Area concept extraction is one of the most important aspects in building ontology. In this paper, we proposed an improved area concept extraction algorithm. In the algorithm, we firstly employed association rule algorithm to obtain the similarity between the sememes, and then used the similarity between the sememes to find the similarity between area concepts. Finally our paper achieves the whole area concepts extraction process. By analyzing the experimental results shows the effectiveness and correctness of the algorithm.
Keywords
data mining; learning (artificial intelligence); ontologies (artificial intelligence); area concept extraction algorithm; association rule; domain ontology; ontology learning; sememe similarity; Accuracy; Algorithm design and analysis; Association rules; Buildings; Computer science; Data mining; Dictionaries; Educational institutions; Libraries; Ontologies; area concept extraction; association rule; sememe;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Design and Applications (ICCDA), 2010 International Conference on
Conference_Location
Qinhuangdao
Print_ISBN
978-1-4244-7164-5
Electronic_ISBN
978-1-4244-7164-5
Type
conf
DOI
10.1109/ICCDA.2010.5541367
Filename
5541367
Link To Document