Research ArticleOpen AccessGoogle Scholar indexed
Education Web Information Retrieval and Classification with Big Data Analysis
Office of Educational Administration, Yangtze University, Jingzhou, China
- 1 Office of Educational Administration, Yangtze University, Jingzhou, China
Creative Education·Volume 07 (2016)·Pages 2868–2875·Published 30 November 2016·DOI10.4236/ce.2016.718265
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Abstract
This paper discusses the text mining method to obtain the education web information rules. The method can be applied to words and parts of speech in texts to record the two-tier structure of automatic mining. On the basis of the initial discovery of the labeling rules, we put forward the linguistic features based on words to expand the application of the approaches. The web information retrieval mechanism is proposed based on web content segmentation. In addition, we build a rule matching method to improve performance of rule utilization, in terms of information of interest to the user and the extent to the interesting part. In conclusion, the use of automatic labeling rules can make part of the tagging accuracy rate reach a new height.
KeywordsEducation InformatizationBig DataText MiningInformation RetrievalText CategorizationWeb CategorizationWeb Page SegmentationConcept Semantic Space
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