语义网:信息检索中的智能

Jenice Aroma, M. Kurian
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引用次数: 8

摘要

随着网络资源的快速增长,对信息检索的搜索方案提出了更高的要求。每个用户每天都会贡献一部分新信息添加到网络中。这一庞大的数据来源是不同的,没有单纯的联系。因此,在网络上查询数据时,必须采用一种新颖的搜索方案来显示相关的结果。目前的网络搜索方案只能显示相关页面作为结果。但是,语义网通过在理解适当的信息需求时提供合适的结果来解决这个问题。它可以通过扩展对机器可读形式的数据库的支持来获得。通过添加语义注释,将当前的web重新定义为语义web。本文概述了语义映射方法。本文的主要目标是提出一种新的语义web发现算法的步骤,该算法具有高效的语义映射和一种新的概念分类方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Semantic web: Intelligence in information retrieval
The rapid growth of web resources lead to a need of enhanced Search scheme for information retrieval. Every single user contributes a part of new information to be added to the web every day. This huge data supplied are of diverse area in origin being added, without a mere relation. Hence, a novel search scheme must be applied for bringing out the relevant results on querying web for data. The current web search scheme could bring out only relevant pages to be as results. But, a Semantic web is a solution to this issue through providing a suitable result on understanding the appropriate need of information. It can be acquired through extending the support for databases in machine readable form. It leads to redefinition of current web into semantic web by adding semantic annotations. This paper gives an overview of Semantic mapping approaches. The main goal of this paper is to propose the steps for bringing out a new Semantic web discovery algorithm with an efficient Semantic mapping and a novel Classification Scheme for categorization of concepts.
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