基于本体的学术文章推荐

Gohar Rehman Chughtai, Jia Lee, Asif Kabir, Rashid Abbasi, Muhammad Arshad Shehzad Hassan
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引用次数: 3

摘要

科学文献大部头中科学成果的定性分析是基于各机构(期刊、会议)向同行审稿人推荐的文章,这通常是由任何机构的编辑完成的。文章更好的分类取决于文章中呈现的本体或概念。我们观察到,场馆提供了一个非常抽象的主题分类,而不是特定主题的分类。在这篇文章中,我们提出了基于本体论的文章类别分类,不仅可以通过特定的文章提取,还可以从被引文章中提取,这可以让我们更深入地了解特定主题的分类,也可以让我们了解被引文章的本体论在参考任何特定文章时的同质性。对来自科学网络的数据集进行了模拟。为了更好地理解其含义,我们将数据集缩小到仅计算机科学主题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ontology-Based Academic Article Recommendation
The qualitative analysis of scientific production in the tome of scientific literature is based on the article recommendation to peer reviewers by the venues (journal, conferences), which is usually done by editor of any venue. The better classification of an article depends upon the ontologies or concepts presented in it. It has been observed that venues provide a very abstract classification of the topic which can't be topic-specific classification. In this write-up, we have proposed ontology-based category classification of an article which is not only extracted through the particular article but also from the cited articles which can give us more insight into the topic-specific categorization and also give us the homogeneity of ontologies of the cited article with reference to any particular article. Simulation has been done over the data set from the web of science. For the better understanding and its implication, we narrow our data set to just computer science subject.
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