Co-AI: A Colab-Based Tool for Abstraction Identification

Zedong Peng, Nan Niu
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引用次数: 2

Abstract

Abstraction identification is aimed at discovering significant domain terms. Prior work, notably AbstFinder and RAI (relevance-driven abstraction identification), has introduced the core ideas, but offered only limited tool support. This paper presents our abstraction identification tool, Co-AI, built on the Google Colab environment allowing the users to run the tool within their web browsers, promoting tool adoption and extension. Co-AI integrates the Wikipedia pages as the domain corpus, and identifies the candidate abstractions with a set of natural language processing (NLP) patterns. Co-AI is available at: https://colab.research.google.com/drive/1ur5KILoi_n-3KY0_vJcMBQDtiSYgcYeP?usp=sharing and we welcome the community’s feedback of our tool.
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协同人工智能:基于协作的抽象识别工具
抽象识别的目的是发现重要的领域术语。先前的工作,特别是AbstFinder和RAI(关联驱动的抽象识别),已经介绍了核心思想,但只提供了有限的工具支持。本文介绍了我们的抽象识别工具,Co-AI,它建立在Google Colab环境上,允许用户在他们的web浏览器中运行该工具,促进了工具的采用和扩展。Co-AI将维基百科页面集成为领域语料库,并使用一组自然语言处理(NLP)模式识别候选抽象。Co-AI可在:https://colab.research.google.com/drive/1ur5KILoi_n-3KY0_vJcMBQDtiSYgcYeP?usp=sharing获得,我们欢迎社区对我们的工具的反馈。
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