摘要
不同于Surface W eb的信息获取方式,Deep W eb中大量的数据隐藏在数据库中,无法直接通过静态的URL链接来获得,只能在查询接口中输入关键词来获得站点中的网页.主要对Deep W eb中查询数据库时提交的查询操作进行了研究,发展了一种机器学习方法去自动获取Deep W eb的查询语言,并根据迭代算法寻找到合适的网页.
Different from the route of getting the information on the Surface Web, a number of data are hidden in the database on the Deep Web and can be attained through not static URL but inputting the key words in query interface. This paper mainly investigates the query operator referred when querying the Deep Web database and de- belop a kind of method of machine learning, that is how to recognize the query language automatically and find the appropriate webpage based on the iterative algorithm.
出处
《云南民族大学学报（自然科学版）》
CAS
2007年第1期66-68,共3页
Journal of Yunnan Minzu University:Natural Sciences Edition
