肤浅的语义分析真的那么肤浅吗?提高文本分类性能的研究

Proceedings of the International Multiconference on Computer Science and Information Technology Pub Date : 2010-10-01 DOI:10.1109/IMCSIT.2010.5680029

Przemyslaw Maciolek, G. Dobrowolski

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引用次数: 4

摘要

本文提出了一种基于图的、浅层语义分析驱动的文档内容建模方法。这允许在改进的文档分类中提取关于文本含义和效果的附加信息。将其性能与“遗留”词袋和Schenker等基于波兰语和英语新闻文章的k - NN分类方法进行比较。

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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Is shallow semantic analysis really that shallow? A study on improving text classification performance

The paper presents a graph-based, shallow semantic analysis-driven approach for modeling document contents. This allows to extract additional information about meaning of text and effects in improved document classification. Its performance is compared against the “legacy” bag-of-words and Schenker et al. approaches with k - NN classification based on Polish and English news articles.

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Proceedings of the International Multiconference on Computer Science and Information Technology

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