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A Novel Architecture for Information Retrieval System based on Semantic Web

机译:基于语义网的新型信息检索系统架构

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Nowadays, the web has enabled an explosive growth of information sharing (there are currently over 4 billion pages covering most areas of human endeavor) so that the web has faced a new challenge of information overhead. The challenge that is now before us is not only to help people locating relevant information precisely but also to access and aggregate a variety of information from different resources automatically. Current web document are in human-oriented formats and they are suitable for the presentation, but machines cannot understand the meaning of document To address this issue, BernersLee proposed a concept of semantic web. With semantic web technology, web information can be understood and processed by machine. It provides new possibilities for automatic web information processing. A main problem of semantic web information retrieval is that when these is not enough knowledge to such information retrieval system, the system will return to a large of no sense result to uses due to a huge amount of information results. In this paper, we present the architecture of information based on semantic web. In addiction, our systems employ the inference Engine to check whether the query should pose to Keyword-based Search Engine or should pose to the Semantic Search Engine.
机译:如今,Web已实现了信息共享的爆炸性增长(目前,人类活动的大部分领域超过40亿页),因此Web面临着信息开销方面的新挑战。现在摆在我们面前的挑战不仅是帮助人们精确地找到相关信息,而且还要自动访问和汇总来自不同资源的各种信息。当前的Web文档采用以人为本的格式,适合于演示,但是机器无法理解文档的含义。为解决此问题,BernersLee提出了语义Web的概念。使用语义网络技术,机器可以理解和处理网络信息。它为自动Web信息处理提供了新的可能性。语义Web信息检索的一个主要问题是,当这些信息检索系统的知识不足时,由于大量的信息结果,系统将返回到大量没有意义的结果以供使用。在本文中,我们提出了基于语义网的信息体系结构。令人上瘾的是,我们的系统使用推理引擎来检查查询是针对基于关键字的搜索引擎还是针对语义搜索引擎。

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