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Content Provider | IEEE Xplore Digital Library |
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Author | Qing Yang Kai-min Cai Jun-li Sun Yan Li |
Copyright Year | 2010 |
Description | Author affiliation: Department of Computer Science, Huazhong Normal University, Wuhan, China (Qing Yang; Kai-min Cai; Jun-li Sun; Yan Li) |
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. |
File Size | 147308 |
File Format | |
ISBN | 9781424463473 |
e-ISBN | 9781424463497 |
DOI | 10.1109/ICCET.2010.5485818 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2010-04-16 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Filtering Statistical analysis Ontologies learning Paper technology Data mining Sun Computer science Learning systems concept extraction Collaboration Machine learning personalization ecommendation ontology |
Content Type | Text |
Resource Type | Article |
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