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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Crowd-Informed Goal Models
AU - Kanchev, G.M.
AU - Murukannaiah, P.K.
AU - Chopra, A.K.
N1 - ©2018 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 - 2018/8/21
Y1 - 2018/8/21
N2 - A topic of recent interest is how to apply crowdsourced information toward producing better software requirements. A research question that has received little attention so far is how to leverage crowdsourced information toward creating better-informed models of requirements. In this paper, we contribute a method following which information in online discussions may be leveraged toward constructing goal models. A salient feature of our method is that it applies high-level queries to draw out potentially relevant information from discussions. We also give a subjective logic-based method for deriving an ordering of the goals based on the amount of supporting and rebutting evidence in the discussions. Such an ordering can potentially be applied toward prioritizing goals for implementation. © 2018 IEEE.
AB - A topic of recent interest is how to apply crowdsourced information toward producing better software requirements. A research question that has received little attention so far is how to leverage crowdsourced information toward creating better-informed models of requirements. In this paper, we contribute a method following which information in online discussions may be leveraged toward constructing goal models. A salient feature of our method is that it applies high-level queries to draw out potentially relevant information from discussions. We also give a subjective logic-based method for deriving an ordering of the goals based on the amount of supporting and rebutting evidence in the discussions. Such an ordering can potentially be applied toward prioritizing goals for implementation. © 2018 IEEE.
KW - crowdsourcing
KW - discussions
KW - evidence
KW - goals
KW - methodology
KW - modeling
KW - Artificial intelligence
KW - Models
KW - Requirements engineering
KW - High-level queries
KW - Online discussions
KW - Research questions
KW - Software requirements
KW - Crowdsourcing
U2 - 10.1109/AIRE.2018.00013
DO - 10.1109/AIRE.2018.00013
M3 - Conference contribution/Paper
SP - 47
EP - 53
BT - 2018 5th International Workshop on Artificial Intelligence for Requirements Engineering (AIRE)
PB - IEEE
ER -