计算机工程与应用2019，Vol.55Issue(8)：201-207,7.DOI:10.3778/j.issn.1002-8331.1712-0392
基于卷积神经网络的构件分类策略的研究
Research on Component Classification Strategy Based on Convolution Neural Network
摘要
Abstract
To improve the efficiency of component retrieval in software reuse process, advantages and disadvantages of software component classification technology and component features are analyzed. From the aspect of component facet-ing information, convolution neural network technology is used to propose a component based on convolution neural net-work. The convolutional neural network is used to extract the facet features, reduce the human factors, improve the accuracy of faceted information extraction, and train the component classification model based on convolution neural network. Through the specific experiments, the model is demonstrated to improve the efficiency of component retrieval.关键词
软件复用/软件构件/卷积神经网络/构件分类/构件检索Key words
software reuse/ software component/ convolution neural network/ component classification/ component retrieval分类
信息技术与安全科学引用本文复制引用
张富为,杨秋翔,宋超峰..基于卷积神经网络的构件分类策略的研究[J].计算机工程与应用,2019,55(8):201-207,7.基金项目
浙江省公益技术研究社会发展项目(No.2016C33016) （No.2016C33016）
浙江理工大学科研启动基金(No.14022086-Y) （No.14022086-Y）
国家自然科学基金(No.61503341). （No.61503341）
