为学习本体挖掘网络:技术现状和批判性评论

M. E. Asikri, S. Krit, H. Chaib, M. Kabrane, H. Ouadani, K. Karimi, Kaouthar Bendaouad, Hicham Elbousty
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引用次数: 1

摘要

本文的目的是研究和介绍使用语义Web挖掘构建本体的主题,语义Web挖掘被定义为两个快速发展的研究领域语义Web和Web挖掘的结合。Web挖掘是数据挖掘技术在Web资源的内容、结构和使用上的应用。语义网是第二代万维网,它丰富了机器可处理的信息,支持用户的任务。这可以帮助发现网页内部和网页之间的全局和局部结构“模型”或“模式”,本体提取是自动或半自动地创建本体,包括提取相应领域的术语和这些概念之间的关系,并用本体语言对它们进行编码,以便于检索。由于手工构建本体非常费力且耗时,因此有很大的动机将该过程自动化。本文概述了这两个领域今天在哪里相遇,并讨论了如何更紧密地整合才能盈利的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mining the Web for learning ontologies: State of art and critical review
The aim of the paper is to investigate and present the subject of building ontologies using the Semantic Web Mining that is defined as the combination of the two fast-developing research areas Semantic Web and Web Mining. Web mining is the application of data mining techniques to the content, structure, and usage of Web resources and The Semantic Web is the second-generation WWW, enriched by machine-processable information which supports the user in his tasks. This can help to discover global as well as local structure “models” or “patterns” within and between Web pages and ontology extraction witch is the automatic or semi-automatic creation of ontologies, including extracting the corresponding domain's terms and the relationships between those concepts, and encoding them with an ontology language for easy retrieval. As building ontologies manually is extremely labor-intensive and time-consuming, there is great motivation to automate the process. This paper gives an overview of where the two areas meet today, and discuss ways of how a closer integration could be profitable.
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