Title :
Mining data records based on ontology evolution for deep web
Author :
Zhang, Wen ; Chen, Kerui ; Zhang, Fan
Author_Institution :
Coll. of Inf. Eng., Zhongzhou Univ., Zhengzhou, China
Abstract :
Currently, the research for the extraction of information in deep web is pretty active. Although many researchers already adopted ontology in the data extraction, many problems still exist. This paper proposed an ontology evolution based method for mining in the data area. Not only will this method solve the problem when the website only consists of one record, but it also can identify he meaning of data that has no labels. With the evolution of ontology, the extraction of data records is being more accurate. Experiments indicate that this method could improve the accuracy and efficiency of data extraction.
Keywords :
Internet; data mining; ontologies (artificial intelligence); data extraction; data record mining; deep Web; ontology evolution; Computer science; Data engineering; Data mining; Educational institutions; Educational technology; Entropy; Knowledge engineering; Ontologies; Random processes; Web pages; component; data records; deep web; maximum entropy model; ontology evolution;
Conference_Titel :
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6347-3
DOI :
10.1109/ICCET.2010.5485649
