Deep Web站点分类研究进展  

Advances in Deep Web classification

作　　者：陆余良[1] 房珊瑶[1] 刘金红[1] 施凡[1] 

机构地区：[1]电子工程学院网络系,安徽合肥230037

出　　处：《安徽大学学报（自然科学版）》2010年第1期103-108,共6页Journal of Anhui University(Natural Science Edition)

摘　　要：如何高效、准确地组织和检索Deep Web蕴含的高质量信息已经成为未来Web挖掘和数据库领域面临的一项崭新课题和挑战,而Deep Web分类则是Deep Web信息检索的基础.该论文综合论述了Deep Web信息集成的研究概况,重点分析了结构化Deep Web分类的主要方法和存在的主要问题,并且讨论了解决这些问题的可能方法;最后对未来工作进行展望.In the future of Web mining and database field, it is a new task and challenge that how to organize and search the Deep Web information efficiently and accurately, while Deep Web classification is the base problem of Deep Web information retrieval. The paper presented a survey on the up-to-date development of Deep Web information integration and Deep Web classification, particularly analyzed the main methods of Deep Web classification and key problems. Then possible solutions to those problems were also discussed respectively. Finally, some future directions of research were given.

关 键 词：DEEP WEB分类 WEB挖掘 信息集成 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]