你读过什么书?基于多文档摘要

Sabina Irum, Jamal Abdul Nasir, Zakia Jalil
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引用次数: 0

摘要

由于目前可用的数据量巨大,从如此大量的数据中提取重要信息是相当困难的。特别是在文本文档的情况下,这需要用户花费大量的时间来阅读材料并提取有用的信息。主要的问题是识别用户的相关文档,删除最重要的信息,确定文档相关性,排除无关信息,减少细节,并生成紧凑、一致的报告。针对这些问题,我们提出了一种新的技术,该技术解决了从大量文本数据中提取重要信息并使用以前读取的文档生成新文档摘要的问题。我们的技术更侧重于从先前阅读的文档中提取主题(也称为主题签名),然后根据更新摘要生成选择与这些主题更相关的句子。在此基础上,利用重叠值的概念,挖掘出有意义的词和词的相似度。另一个让我们的工作变得更好的东西是Dice Coefficient,它测量文档集之间单词的交集,并帮助消除冗余。生成的摘要是基于更多样化和具有高度代表性的平均长度的句子。根据经验,我们已经观察到我们提出的新技术在真实世界的TAC2008数据集上对基线竞争对手表现更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
What have you read? based Multi-Document Summarization
Due to the tremendous amount of data available today, extracting essential information from such a large volume of data is quite tough. Particularly in the case of text documents, which need a significant amount of time from the user to read the material and extract useful information. The major problem is identifying the user's relevant documents, removing the most significant pieces of information, determining document relevancy, excluding extraneous information, reducing details, and generating a compact, consistent report. For all these issues, we proposed a novel technique that solves the problem of extracting important information from a huge amount of text data and using previously read documents to generate summaries of new documents. Our technique is more focused on extracting topics (also known as topic signatures) from the previously read documents and then selecting the sentences that are more relevant to these topics based on update summary generation. Besides this, the concept of overlapping value is used that digs out the meaningful words and word similarities. Another thing that makes our work better is the Dice Coefficient which measures the intersection of words between document sets and helps to eliminate redundancy. The summary generated is based on more diverse and highly representative sentences with an average length. Empirically, we have observed that our proposed novel technique performed better with baseline competitors on the real-world TAC2008 dataset.
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