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

Zedong Peng; Nan Niu

doi:10.1109/RE51729.2021.00050

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

Zedong Peng
, Nan Niu

Computer Science

University of Cincinnati

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

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.

Original language	English
Title of host publication	Proceedings - 29th IEEE International Requirements Engineering Conference, RE 2021
Editors	Ana Moreira, Kurt Schneider, Michael Vierhauser, Jane Cleland-Huang
Publisher	IEEE Computer Society
Pages	420-421
Number of pages	2
ISBN (Electronic)	9781665428569
DOIs	https://doi.org/10.1109/RE51729.2021.00050
State	Published - 2021
Event	29th IEEE International Requirements Engineering Conference, RE 2021 - Virtual, Notre Dame, United States Duration: Sep 20 2021 → Sep 24 2021

Publication series

Name	Proceedings of the IEEE International Conference on Requirements Engineering
ISSN (Print)	1090-705X
ISSN (Electronic)	2332-6441

Conference

Conference	29th IEEE International Requirements Engineering Conference, RE 2021
Country/Territory	United States
City	Virtual, Notre Dame
Period	09/20/21 → 09/24/21

Keywords

Abstraction identification
Google Colab
Natural language processing

Access to Document

10.1109/RE51729.2021.00050

Cite this

Peng, Z., & Niu, N. (2021). Co-AI: A Colab-Based Tool for Abstraction Identification. In A. Moreira, K. Schneider, M. Vierhauser, & J. Cleland-Huang (Eds.), Proceedings - 29th IEEE International Requirements Engineering Conference, RE 2021 (pp. 420-421). (Proceedings of the IEEE International Conference on Requirements Engineering). IEEE Computer Society. https://doi.org/10.1109/RE51729.2021.00050

Peng, Zedong ; Niu, Nan. / Co-AI : A Colab-Based Tool for Abstraction Identification. Proceedings - 29th IEEE International Requirements Engineering Conference, RE 2021. editor / Ana Moreira ; Kurt Schneider ; Michael Vierhauser ; Jane Cleland-Huang. IEEE Computer Society, 2021. pp. 420-421 (Proceedings of the IEEE International Conference on Requirements Engineering).

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title = "Co-AI: A Colab-Based Tool for Abstraction Identification",

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.",

keywords = "Abstraction identification, Google Colab, Natural language processing",

author = "Zedong Peng and Nan Niu",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 29th IEEE International Requirements Engineering Conference, RE 2021 ; Conference date: 20-09-2021 Through 24-09-2021",

year = "2021",

doi = "10.1109/RE51729.2021.00050",

language = "English",

series = "Proceedings of the IEEE International Conference on Requirements Engineering",

publisher = "IEEE Computer Society",

pages = "420--421",

editor = "Ana Moreira and Kurt Schneider and Michael Vierhauser and Jane Cleland-Huang",

booktitle = "Proceedings - 29th IEEE International Requirements Engineering Conference, RE 2021",

}

Peng, Z & Niu, N 2021, Co-AI: A Colab-Based Tool for Abstraction Identification. in A Moreira, K Schneider, M Vierhauser & J Cleland-Huang (eds), Proceedings - 29th IEEE International Requirements Engineering Conference, RE 2021. Proceedings of the IEEE International Conference on Requirements Engineering, IEEE Computer Society, pp. 420-421, 29th IEEE International Requirements Engineering Conference, RE 2021, Virtual, Notre Dame, United States, 09/20/21. https://doi.org/10.1109/RE51729.2021.00050

Co-AI: A Colab-Based Tool for Abstraction Identification. / Peng, Zedong; Niu, Nan.
Proceedings - 29th IEEE International Requirements Engineering Conference, RE 2021. ed. / Ana Moreira; Kurt Schneider; Michael Vierhauser; Jane Cleland-Huang. IEEE Computer Society, 2021. p. 420-421 (Proceedings of the IEEE International Conference on Requirements Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Co-AI

T2 - 29th IEEE International Requirements Engineering Conference, RE 2021

AU - Peng, Zedong

AU - Niu, Nan

PY - 2021

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N2 - 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.

AB - 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.

KW - Abstraction identification

KW - Google Colab

KW - Natural language processing

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M3 - Conference contribution

AN - SCOPUS:85123212256

T3 - Proceedings of the IEEE International Conference on Requirements Engineering

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ER -

Peng Z, Niu N. Co-AI: A Colab-Based Tool for Abstraction Identification. In Moreira A, Schneider K, Vierhauser M, Cleland-Huang J, editors, Proceedings - 29th IEEE International Requirements Engineering Conference, RE 2021. IEEE Computer Society. 2021. p. 420-421. (Proceedings of the IEEE International Conference on Requirements Engineering). doi: 10.1109/RE51729.2021.00050

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

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