基于Web挖掘的人脸数据库科技展望

Chunxia Yang, Yunyang Yan, Quanyin Zhu
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引用次数: 1

摘要

对于人脸数据库系统通过Web对科技专家进行挖掘,Web挖掘的数据包括科技专家的人脸、姓名、性别、职称、学校等属性。本系统采用了Python编程语言,并建立了Django框架。在Web提取的基础上,通过URL过滤提取科技专家的基本信息。科技专家人脸数据提取采用OpenCV库实现。因此,它可以检测人脸并将其剪切出来。提取还采用了语义分析的方法,利用在网页文本中分割的预定义关键字来计算最短距离。将下载的科技专家人脸数据存储在本地文件夹中,然后通过文件夹遍历得到的绝对路径存储在MySQL数据库系统中,实现对科技专家基本信息的查询和统计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Face Database Development of Science and Technology Expects Based on Web Mining
For the Face database system by Web mining of science and technology experts, the Web mining data include the faces of science and technology experts, name, gender, title, schools and other properties. The Python programming language and the establishment of the Django framework are used in the proposed system. According to the Web extracting, the basic information of science and technology experts is extracted by the URL filtering. The face data of science and technology experts extracting is obtained by OpenCV libraries. As a result, it can detect face and cut them out. The extraction also adopts the semantic analysis method which uses predefined keywords segmented in the web page text to calculate the shortest distance. The face date of science and technical experts downloaded are deposited in local folder, and then the absolute path got by means of folder traversal is stored in the MySQL database system which can achieve the query and statistics of basic information of science and technical experts.
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