基于本体的领域关键词提取和近重复文章检测

The 2015 IEEE RIVF International Conference on Computing & Communication Technologies - Research, Innovation, and Vision for Future (RIVF) Pub Date : 2015-02-26 DOI:10.1109/RIVF.2015.7049886

N. Do, LongVan Ho

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引用次数: 5

摘要

网络报纸数量的显著增加为网络用户提供了一个巨大的信息来源。用户很难管理内容，也很难检查文章的正确性。本文介绍了用于近重复文章检测的关键字提取和签名匹配算法。在本体的基础上，自动提取文章的关键词，并利用提取的关键词计算两篇文章的相似度。算法应用于越南在线劳动与就业报纸。实验结果表明，该方法是有效的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Domain-specific keyphrase extraction and near-duplicate article detection based on ontology

The significant increase in number of the online newspapers has given web users a giant information source. The users are really difficult to manage content as well as check the correctness of articles. In this paper, we introduce algorithms of extracting keyphrase and matching signatures for near-duplicate articles detection. Based on ontology, keyphrases of articles are extracted automatically and similarity of two articles is calculated by using extracted keyphrases. Algorithms are applied on Vietnamese online newspapers for Labor & Employment. Experimental results show that our proposed methods are effective.

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来源期刊

The 2015 IEEE RIVF International Conference on Computing & Communication Technologies - Research, Innovation, and Vision for Future (RIVF)

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