基于BERT+CNN的捐赠型众筹标题分类

Gang Zhou
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引用次数: 3

摘要

随着互联网的快速发展,越来越多的捐赠型众筹信息在微博、朋友圈等互联网平台上被发布和转发。出资人如何从捐赠众筹的文字信息中快速获取自己需要的内容?赞助商如何获得资金支持已成为非常迫切的需求。本文采用深度学习的方法对捐赠类众筹的标题进行处理,实现了对不同语言风格的捐赠类众筹文本的分类。研究发现,基于BERT+ cnn的捐赠众筹标题分类模型可以更准确地对标题进行分类,并且在各项评价指标上都优于其他模型。研究结果对文本分类领域的研究具有现实意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Donation-Based Crowdfunding Title Classification Based on BERT+CNN
With the rapid development of the Internet, more and more donation-based crowdfunding information is published and forwarded on Internet platforms such as Weibo and Moments. How can funders quickly obtain the content they need from the text information of donation-based crowdfunding. How sponsors can obtain financial support has become a very urgent need. This article uses deep learning methods to process the titles of donation-based crowdfunding, and realizes the classification of donation-based crowdfunding texts in different language styles. Research has found that the BERT+CNN-based donation-based crowdfunding title classification model can more accurately classify titles, and is superior to other models in various evaluation indicators. The research results have practical significance for the research in the field of text classification.
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