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A SVM-Based Text Classification System for Knowledge Organization Method of Crop Cultivation

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文献类型：外文期刊

作者： Ji, Laiqing ¹ ; Cheng, Xinrong ¹ ; Kang, Li ¹ ; Li, Daoliang ¹ ; Li, Daiyi ¹ ; Wang, Kaiyi ² ; Chen, Yingyi ¹ ;

作者机构： 1.China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China

2.Beijing Res Ctr Informat Technol Agr, Beijing 10097, Peoples R China

关键词： Support Vector Machine (SVM);Text Classification;organization method;crop

期刊名称：COMPUTER AND COMPUTING TECHNOLOGIES IN AGRICULTURE V, PT I

ISSN： 1868-4238

年卷期： 2012 年 368 卷

页码：

收录情况： SCI

摘要： The organization of crop cultivation practices is still far from completion, and Web Resources are not used adequately. This paper proposed a method, based on SVM, to organize the knowledge of crop cultivation practices efficiently from Web Resources. The knowledge organization method of crop cultivation was proposed with Good Agricultural Practices (GAP) in the application of the crop cultivation practices. It is that how to organize the existing crop cultivation knowledge, according to the requirements of crop cultivation practices. It mainly includes a text classification method and a search strategy on the knowledge of crop cultivation. For the text classificaiion method, it used a text classification method based on SVM Decision Tree; for the search strategy, it used a strategy, organized by Ontology and custom knowledge bases. The experiment shows that performance of the proposed text classification method and the knowledge organization method with wheat, is workable and feasible.

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