Intent classification for a management conversational assistant
Hefny, Abdelrahman, Dafoulas, George ORCID: https://orcid.org/0000-0003-2638-8771 and Ismail, Manal
(2020)
Intent classification for a management conversational assistant.
15th International Conference on Computer Engineering and Systems Proceedings.
In: ICCES 2020, 15-16 Dec 2020, Cairo, Egypt.
e-ISBN 9780738105598, pbk-ISBN 9780738105604.
[Conference or Workshop Item]
(doi:10.1109/ICCES51560.2020.9334685)
Abstract
Intent classification is an essential step in processing user input to a conversational assistant. This work investigates techniques of intent classification of chat messages used for communication among software development teams with the aim of building an intent classifier for a management conversational assistant integrated into modern communication platforms used by developers. Experiments conducted using rule-based and common ML techniques have shown that careful choice of classification features has a significant impact on performance, and the best performing model was able to obtain a classification accuracy of 72%. A set of techniques for extracting useful features for text classification in the software engineering domain was also implemented and tested.
Item Type: | Conference or Workshop Item (Paper) |
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Research Areas: | A. > School of Science and Technology > Computer Science > Intelligent Environments group |
Item ID: | 32282 |
Useful Links: | |
Depositing User: | George Dafoulas |
Date Deposited: | 09 Apr 2021 09:36 |
Last Modified: | 13 Apr 2021 11:44 |
URI: | https://eprints.mdx.ac.uk/id/eprint/32282 |
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