TITLE:
Education Web Information Retrieval and Classification with Big Data Analysis
AUTHORS:
Rurui Zhou
KEYWORDS:
Education Informatization, Big Data, Text Mining, Information Retrieval, Text Categorization, Web Categorization, Web Page Segmentation, Concept Semantic Space
JOURNAL NAME:
Creative Education,
Vol.7 No.18,
December
29,
2016
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.