一种改进的基于短技术文本的关键词提取方法

Jun Wang, Lei Li, F. Ren
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引用次数: 5

摘要

关键词是信息管理和检索、文本自动分类和聚类的关键资源。关键词提取在结构化文本的构建过程中起着重要的作用。当前的关键词提取算法在某些方面已经成熟。然而,由于未知词导致的分词错误影响了中文关键词提取的性能,特别是在科技文本领域。为了解决这一问题,本文提出了一种改进的基于词间关系的关键词提取方法。实验结果表明,该方法可以有效地纠正分割过程中产生的错误,提高关键词提取的性能,并可扩展到其他领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An improved method of keywords extraction based on short technology text
Keywords are the critical resources of information management and retrieval, automatic text classification and clustering. The keywords extraction plays an important role in the process of constructing structured text. Current algorithms of keywords extraction have matured in some ways. However the errors of word segmentation which caused by unknown words have been affected the performance of Chinese keywords extraction, particularly in the field of technological text. In order to solve the problem, this paper proposes an improved method of keywords extraction based on the relationship among words. Experiments show that the proposed method can effectively correct the errors caused by segmentation and improve the performance of keywords extraction, and it can also extend to other areas.
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