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Shen, Y., He, X., Gao, J. et al. (2014). Learning Semantic Representations Using Convolutional Neural Networks for Web Search (pp. 373-374). Proceedings of the 23rd International Conference on World Wide Web, Seoul, 7-11 April 2014.
https://doi.org/10.1145/2567948.2577348

has been cited by the following article:

• 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.