Topological Analysis of Contradictions in Text

Topological Analysis of Contradictions in Text
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文本矛盾的拓扑分析

DOI:
10.1145/3477495.3531881
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发表时间:
2022
期刊:
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’22
影响因子:
--
通讯作者:
Rahman, Ruhani
Rahman, Ruhani
中科院分区:
--
文献类型:
--
作者:
Wu, Xiangcheng;Niu, Xi;Rahman, Ruhani

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从文本中自动发现矛盾是自然语言理解和信息检索中的一个基本而又未被研究的问题。拓扑学是一门研究几何形状性质的数学分支,近年来被证明对理解文本的语义很有用。本研究提出了一种拓扑学方法来增强深度学习模型在发现文本中的矛盾方面的作用。此外,为了更好地理解矛盾,我们提出了六类矛盾的分类。在此基础上,以不同的矛盾类型和不同的文本体裁对拓扑增强型模式进行了评价。总体而言,我们已经证明了拓扑特征在发现矛盾方面的有效性,特别是文本中更潜在、更复杂的矛盾。
Automatically finding contradictions from text is a fundamental yet under-studied problem in natural language understanding and information retrieval. Recently, topology, a branch of mathematics concerned with the properties of geometric shapes, has been shown useful to understand semantics of text. This study presents a topological approach to enhancing deep learning models in detecting contradictions in text. In addition, in order to better understand contradictions, we propose a classification with six types of contradictions. Following that, the topologically enhanced models are evaluated with different contradictions types, as well as different text genres. Overall we have demonstrated the usefulness of topological features in finding contradictions, especially the more latent and more complex contradictions in text.
DOI: 10.21105/joss.00925
发表时间: 2018-09
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影响因子: --
作者:
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影响因子: --
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