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Analysis of OWA operators for automatic keyphrase extraction in a semantic context

机译:语义上下影中自动关键关键术后owa运营商的分析

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摘要

Automatic keyphrase extraction from texts is useful for many computational systems in the fields of natural language processing and text mining. Although a number of solutions to this problem have been described, semantic analysis is one of the least exploited linguistic features in the most widely-known proposals, causing the results obtained to have low accuracy and performance rates. This paper presents an unsupervised method for keyphrase extraction, based on the use of lexico-syntactic patterns for extracting information from texts, and a fuzzy topic modeling. An OWA operator combining several semantic measures was applied to the topic modeling process. This new approach was evaluated with Inspec and 500N-KPCrowd datasets. Several approaches within our proposal were evaluated against each other. A statistical analysis was performed to substantiate the best approach of the proposal. This best approach was also compared with other reported systems, giving promising results.
机译:来自文本的自动关键短语提取对于自然语言处理和文本挖掘领域的许多计算系统非常有用。虽然已经描述了许多对该问题的解决方案,但是语义分析是最广泛熟的提案中最不利用的语言特征之一,导致获得的结果具有低精度和性能率。本文介绍了关键肾上腺酶提取的无监督方法,基于使用词典语法模式来从文本中提取信息以及模糊主题建模。组合多种语义措施的OWA操作员对主题建模过程。使用Inspec和500n-kpcrowd数据集进行了这种新方法。我们提案中的若干方法互相评估。进行统计分析以证实提案的最佳方法。与其他报告的系统相比,这种最佳方法也具有有前途的结果。

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