Classification of Semantic Documents Based on WordNet
作者： Bin Shi , Liying Fang , Jianzhuo Yan , Pu Wang , Chen Dong
DOI: 10.1109/EEEE.2009.15
关键词: Social Semantic Web 、 Artificial intelligence 、 Semantic computing 、 Computer science 、 Information retrieval 、 Semantic similarity 、 Explicit semantic analysis 、 Natural language processing 、 Semantic compression 、 Semantic integration 、 Semantic Web Stack 、 Semantic technology
摘要: There are a lot benefits to enable intelligent agent understanding the information from semantic web. It enhances efficiency of usage and at same time, suffices need users. Semantic documents contain adequate which helps understanding. However, discrepancy between ontology is an interpreter document prevents share knowledge. In this paper, we proposed uniform representation for content, include concepts relations, based on WordNet. First, disambiguation preceded within key words in purpose mapping them concepts. Then present whole form concept graph that Levenshtein Distance could be applied making classification documents. We have empirical result methodology makes promising raise accuracy.
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