DocumentCode :
2656994
Title :
Design analysis and implementation for ontology learning model
Author :
Yang, Qing ; Cai, Kai-min ; Sun, Jun-Li ; Li, Yan
Author_Institution :
Dept. of Comput. Sci., Huazhong Normal Univ., Wuhan, China
Volume :
3
fYear :
2010
fDate :
16-18 April 2010
Abstract :
Ontology learning is a technology. Ontology learning can be used to establish ontology automatically or semi-automatically by introducing the ontology engineering and machine learning technology and many other sciences and technologies. The ontology learning technology which is proposed in our paper is to reduce the time of building an entire ontology. Our paper presents an Ontology Learning model which will enhance the efficiency of extraction concept, and enhance the efficiency of ontology building. It includes several aspects, and area concept extraction is the main aspect of all. The model combines personalized recommendation with concept extraction and realizes a more accurate and stable domain concept extraction method. We describe these techniques and report the results of the experiment examining its effectiveness and efficiency.
Keywords :
learning (artificial intelligence); ontologies (artificial intelligence); area concept extraction; design analysis; extraction concept; machine learning; ontology building; ontology engineering; ontology learning model; personalized recommendation; stable domain concept extraction; Collaboration; Computer science; Data mining; Filtering; Learning systems; Machine learning; Ontologies; Paper technology; Statistical analysis; Sun; concept extraction; learning; ontology; personalization ecommendation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6347-3
Type :
conf
DOI :
10.1109/ICCET.2010.5485818
Filename :
5485818
Link To Document :
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