Affiliation:
1. Department of Foreign Languages and General Studies, Shenyang Urban Construction University, Shenyang, Liaoning, China
Abstract
Traditional methods only consider topic information in English vocabulary information extraction, lose the statistical feature information of the keywords themselves, and easily ignore the semantic information of the words. In order to improve the extraction efficiency of English keyword information, based on the CAD mesh model, this paper adds constraint factors such as vertex neighborhood flatness, vertex degree, side length, and flatness on both sides of the side on the basis of the original QEM quadratic error simplification algorithm, and it incorporates a smoothing effect into the edge folding cost function. Moreover, based on the proposed normal vector-based QEM mesh simplification algorithm, the point selection after the edge folding operation is fixed as the vertices of the original edge, and it is applied to the mesh parameterization. In addition, the algorithm solves the local parameterization problem of partially deleted vertices after the simplification operation of each layer is completed. After the model is constructed, the performance of the model is verified through experiments. The research shows that the English keyword information extraction model constructed in this paper is effective.
Funder
Shenyang Urban Construction University
Subject
General Mathematics,General Medicine,General Neuroscience,General Computer Science
Reference15 articles.
1. Effective approaches for extraction of keywords;J. Kaur;International Journal of Computer Science Issues (IJCSI),2010
2. Keyword and Keyphrase Extraction Techniques: A Literature Review
3. Efficient feature extraction for text mining;M. Pandi;Advances in Natural & Applied Sciences,2016
4. Automatic keyword extraction from documents using conditional random fields;C. Zhang;Journal of Computational Information Systems,2008
5. Keyword extraction from emails
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