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  • canary-2017

    Rights statement: ©2017 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

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Canary: Extracting Requirements-Related Information from Online Discussions

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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Canary : Extracting Requirements-Related Information from Online Discussions. / Kanchev, Georgi M.; Murukannaiah, Pradeep K.; Chopra, Amit K.; Sawyer, Pete.

Proceedings of the 25th IEEE International Requirements Engineering Conference. Lisbon : IEEE, 2017. p. 31-40.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Kanchev, GM, Murukannaiah, PK, Chopra, AK & Sawyer, P 2017, Canary: Extracting Requirements-Related Information from Online Discussions. in Proceedings of the 25th IEEE International Requirements Engineering Conference. IEEE, Lisbon, pp. 31-40. https://doi.org/10.1109/RE.2017.83

APA

Kanchev, G. M., Murukannaiah, P. K., Chopra, A. K., & Sawyer, P. (2017). Canary: Extracting Requirements-Related Information from Online Discussions. In Proceedings of the 25th IEEE International Requirements Engineering Conference (pp. 31-40). IEEE. https://doi.org/10.1109/RE.2017.83

Vancouver

Kanchev GM, Murukannaiah PK, Chopra AK, Sawyer P. Canary: Extracting Requirements-Related Information from Online Discussions. In Proceedings of the 25th IEEE International Requirements Engineering Conference. Lisbon: IEEE. 2017. p. 31-40 https://doi.org/10.1109/RE.2017.83

Author

Kanchev, Georgi M. ; Murukannaiah, Pradeep K. ; Chopra, Amit K. ; Sawyer, Pete. / Canary : Extracting Requirements-Related Information from Online Discussions. Proceedings of the 25th IEEE International Requirements Engineering Conference. Lisbon : IEEE, 2017. pp. 31-40

Bibtex

@inproceedings{87f725465b544b3c8d9dadf4a7fb8cd4,
title = "Canary: Extracting Requirements-Related Information from Online Discussions",
abstract = "Online discussions about software applications generate a large amount of requirements-related information. This information can potentially be usefully applied in requirements engineering; however currently, there are few systematic approaches for extracting such information. To address this gap, we propose Canary, an approach for extracting and querying requirements-related information in online discussions. The highlight of our approach is a high-level query language that combines aspects of both requirements and discussion in online forums. We give the semantics of the query language in terms of relational databases and SQL. We demonstrate the usefulness of the language using examples on real data extracted from online discussions. Our approach relies on human annotations of online discussions. We highlight the subtleties involved in interpreting the content in online discussions and the assumptions and choices we made to effectively address them. We demonstrate the feasibility of generating high-quality annotations by obtaining them from lay Amazon Mechanical Turk users.",
author = "Kanchev, {Georgi M.} and Murukannaiah, {Pradeep K.} and Chopra, {Amit K.} and Pete Sawyer",
note = "{\textcopyright}2017 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.",
year = "2017",
month = sep,
day = "26",
doi = "10.1109/RE.2017.83",
language = "English",
isbn = "9781538631928",
pages = "31--40",
booktitle = "Proceedings of the 25th IEEE International Requirements Engineering Conference",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - Canary

T2 - Extracting Requirements-Related Information from Online Discussions

AU - Kanchev, Georgi M.

AU - Murukannaiah, Pradeep K.

AU - Chopra, Amit K.

AU - Sawyer, Pete

N1 - ©2017 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2017/9/26

Y1 - 2017/9/26

N2 - Online discussions about software applications generate a large amount of requirements-related information. This information can potentially be usefully applied in requirements engineering; however currently, there are few systematic approaches for extracting such information. To address this gap, we propose Canary, an approach for extracting and querying requirements-related information in online discussions. The highlight of our approach is a high-level query language that combines aspects of both requirements and discussion in online forums. We give the semantics of the query language in terms of relational databases and SQL. We demonstrate the usefulness of the language using examples on real data extracted from online discussions. Our approach relies on human annotations of online discussions. We highlight the subtleties involved in interpreting the content in online discussions and the assumptions and choices we made to effectively address them. We demonstrate the feasibility of generating high-quality annotations by obtaining them from lay Amazon Mechanical Turk users.

AB - Online discussions about software applications generate a large amount of requirements-related information. This information can potentially be usefully applied in requirements engineering; however currently, there are few systematic approaches for extracting such information. To address this gap, we propose Canary, an approach for extracting and querying requirements-related information in online discussions. The highlight of our approach is a high-level query language that combines aspects of both requirements and discussion in online forums. We give the semantics of the query language in terms of relational databases and SQL. We demonstrate the usefulness of the language using examples on real data extracted from online discussions. Our approach relies on human annotations of online discussions. We highlight the subtleties involved in interpreting the content in online discussions and the assumptions and choices we made to effectively address them. We demonstrate the feasibility of generating high-quality annotations by obtaining them from lay Amazon Mechanical Turk users.

U2 - 10.1109/RE.2017.83

DO - 10.1109/RE.2017.83

M3 - Conference contribution/Paper

SN - 9781538631928

SP - 31

EP - 40

BT - Proceedings of the 25th IEEE International Requirements Engineering Conference

PB - IEEE

CY - Lisbon

ER -