基于bert的Siamese网络短文本语义相似度模型

Haoyu Jiang
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引用次数: 0

摘要

人们通过语言——人类思想的媒介——来表达自己的情感和思想。随着流媒体的蓬勃发展,文本相似度的计算在自然语言处理领域中势在必行。任何与文本相关的字段都离不开文本语义相似度。文本语义相似度的计算在文档管理、文档分类和文档关联中起着关键作用。此外,在人工智能、人机翻译、问题系统、智能聊天系统、命名法识别等一些新兴领域,流行的自然语言处理任务都与文本语义相似度计算交织在一起。近年来,许多优秀的研究者从不同的维度研究了文本语义相似度的算法和模型。本文提出了一种新的基于bert的Siamese网络的短文本余弦相似度计算模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Short-Text Semantic Similarity Model of BERT-Based Siamese Network
People convey their emotions and thoughts through words, the medium of human thoughts. Up against the vigorous development of streaming media, the calculation of text similarity is imperative in the field of natural language processing. Any text-related field is inseparable from text semantic similarity. The calculation of text semantic similarity plays a key role in document management, document classification, and document relevance. Besides, popular natural language processing tasks in some trendy fields, such as artificial intelligence, human-machine translation, problem system, intelligent chat system, and nomenclature recognition, are intertwined with text semantic similarity calculation. In recent years, many excellent researchers have studied the algorithms and models of text semantic similarity from different dimensions. In this paper, a new short-text cosine similarity calculation model of the BERT-based Siamese network is proposed.
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