Intent classification for a management conversational assistant
Conference paper
Hefny, A., Dafoulas, G. and Ismail, M. 2020. Intent classification for a management conversational assistant. ICCES 2020. Cairo, Egypt 15 - 16 Dec 2020 Institute of Electrical and Electronics Engineers (IEEE). pp. 1-6 https://doi.org/10.1109/ICCES51560.2020.9334685
Type | Conference paper |
---|---|
Title | Intent classification for a management conversational assistant |
Authors | Hefny, A., Dafoulas, G. and Ismail, M. |
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. |
Research Group | Research Group on Development of Intelligent Environments |
Conference | ICCES 2020 |
Page range | 1-6 |
ISBN | |
Electronic | 9780738105598 |
Paperback | 9780738105604 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Publication dates | |
15 Dec 2020 | |
Online | 01 Feb 2021 |
Publication process dates | |
Deposited | 09 Apr 2021 |
Accepted | 12 Nov 2020 |
Output status | Published |
Accepted author manuscript | |
Copyright Statement | Copyright © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Digital Object Identifier (DOI) | https://doi.org/10.1109/ICCES51560.2020.9334685 |
Language | English |
Book title | 15th International Conference on Computer Engineering and Systems Proceedings |
https://repository.mdx.ac.uk/item/894v6
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