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Random Indexing and Modified Random Indexing based approach for extractive text summarization

机译：基于随机索引和改进的基于随机索引的提取性文本摘要方法

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摘要

Random Indexing based extractive text summarization has already been proposed in literature. This paper looks at the above technique in detail, and proposes several improvements. The improvements are both in terms of formation of index (word) vectors of the document, and construction of context vectors by using convolution instead of addition operation on the index vectors. Experiments have been conducted using both angular and linear distances as metrics for proximity. As a consequence, three improved versions of the algorithm, viz. RISUM, RISUM+ and MRISUM were obtained. These algorithms have been applied on DUC 2002 documents, and their comparative performance has been studied. Different ROUGE metrics have been used for performance evaluation. While RISUM and RISUM+ perform almost at par, MRISUM is found to outperform both RISUM and RISUM+ significantly. MRISUM also outperforms LSA+TRM based summarization approach. The study reveals that all the three Random Indexing based techniques proposed in this study produce consistent results when linear distance is used for measuring proximity.
机译：在文献中已经提出了基于随机索引的提取文本摘要。本文详细研究了上述技术，并提出了一些改进措施。改进既包括文档的索引（单词）向量的形成，又包括通过使用卷积而不是对索引向量进行加法运算来构造上下文向量。已经使用角距离和线性距离作为接近度的量度进行了实验。结果，算法的三个改进版本，即。获得了RISUM，RISUM +和MRISUM。这些算法已应用于DUC 2002文档，并研究了它们的比较性能。不同的ROUGE指标已用于性能评估。尽管RISUM和RISUM +的性能几乎相等，但发现MRISUM的性能明显优于RISUM和RISUM +。 MRISUM还优于基于LSA + TRM的汇总方法。该研究表明，当使用线性距离测量接近度时，本研究中提出的所有三种基于随机索引的技术均会产生一致的结果。

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  • 来源
    《Computer speech and language》 |2015年第1期|32-44|共13页
  • 作者

    Niladri Chatterjee; Pramod Kumar Sahoo;

  • 作者单位

    Department of Mathematics, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India;

    Department of Mathematics, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India,Institute for Systems Studies & Analyses, Defence Research & Development Organisation, Metcalfe House Complex, Delhi 110054, India;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Word Space Model; Random Indexing; PageRank; Convolution; Modified Random Indexing;

    机译：词空间模型随机索引网页排名;卷积;修改后的随机索引;

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