TwMiner:挖掘新闻文章的相关推文

2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW) Pub Date : 2023-05-01 DOI:10.1109/CCGridW59191.2023.00052

Roshni Chakraborty, Nilotpal Chakraborty

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引用次数: 0

摘要

在本文中，我们提出了一种基于伪相关反馈的自动化方法，该方法利用新闻文章的内容和上下文属性来确定与该新闻文章相关的推文。在一组1000篇新闻文章上进行的大量实证验证表明，与目前的研究工作相比，所提出的方法可以确保较高的精度(0.942)，并且可以成功地提取大多数新闻文章的相关推文，约占新闻文章总数的95%。

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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TwMiner: Mining Relevant Tweets of News Articles

In this paper, we propose a pseudo-relevance feedback-based automated approach that utilizes both the content and context attributes of a news article to determine the tweets relevant to that news article. Extensive empirical validation on a set of 1000 news articles highlights that the proposed approach can ensure high precision (0.942) in comparison to the current research works and can successfully extract relevant tweets for a majority of the news articles, around 95% of the total news articles.

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来源期刊

2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW)

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