| 摘要: |
| 为了最大限度地获取Deep Web数据源信息,并对获取到的数据源信息进行分类,方便后续的数据源集成工作以及用户的检索使用,提出了一种基于数据库的实时的Deep Web数据源搜索框架,该模型在本地服务器上设计安装“数据源发现应用程序”模块,通过各搜索网站下载安装的“客户端数据源应用程序”模块实现数据信息的对接和实时传送.为了保证检索效率,利用知网结合同义词词林对各大被检索网站进行分类. |
| 关键词: Deep Web 数据源 实时 分类 |
| DOI： |
| 分类号: |
| 基金项目: |
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| Discovery and classification of deep web data sources |
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CHANG Tiantian, CHEN Junhua
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College of Information,Mechanical and Electrical Engineering,Shanghai Normal University
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| Abstract: |
| In order to acquire the Deep Web data source information maximally,and classify the data source information effectively,this paper proposes a method of Deep Web data search framework based on the real-time database to facilitate the subsequent data source integration work and the user′s retrieval.The framework designs and installs the S_DS Application module on the local server,the retrieved website installs the C_DS Application module by searching and downloading to achieve the data information connection and real-time transmission.In this framework of the real-time query,in order to ensure retrieval efficiency,this paper uses the classification method combined with Hownet and Tongyici cilin to classify each big retrieved web site. |
| Key words: Deep Web data source real time classification |
