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ADAPT at IJCNLP-2017 Task 4: a multinomial naive Bayes classification approach for customer feedback analysis task

Lohar, Pintu orcid logoORCID: 0000-0002-5328-1585, Dutta Chowdhury, Koel, Afli, Haithem orcid logoORCID: 0000-0002-7449-4707, Hasanuzzaman, Mohammed and Way, Andy orcid logoORCID: 0000-0001-5736-5930 (2017) ADAPT at IJCNLP-2017 Task 4: a multinomial naive Bayes classification approach for customer feedback analysis task. In: 8th International Joint Conference on Natural Language Processing, Shared Tasks, 27 Nov- 1 Dec 2017, Taipei, Taiwan.

Abstract
In this age of the digital economy, promoting organisations attempt their best to engage the customers in the feedback provisioning process. With the assistance of customer insights, an organisation can develop a better product and provide a better service to its customer. In this paper, we analyse the real world samples of customer feedback from Microsoft Office customers in four languages, i.e., English, French, Spanish and Japanese and conclude a five-plus-one-classes categorisation (comment, request, bug, complaint, meaningless and undetermined) for meaning classification. The task is to determine what class(es) the customer feedback sentences should be annotated as in four languages. We propose following approaches to accomplish this task: (i) a multinomial naive bayes (MNB) approach for multilabel classification, (ii) MNB with one-vsrest classifier approach, and (iii) the combination of the multilabel classification based and the sentiment classification based approach. Our best system produces F-scores of 0.67, 0.83, 0.72 and 0.7 for English, Spanish, French and Japanese, respectively. The results are competitive to the best ones for all languages and secure 3 rd and 5 the position for Japanese and French, respectively, among all submitted systems.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > ADAPT
Published in: Proceedings of the 8th International Joint Conference on Natural Language Processing, Shared Task. . Asian Federation of Natural Language Processing.
Publisher:Asian Federation of Natural Language Processing
Official URL:https://www.aclweb.org/anthology/I17-4027
Copyright Information:© 2017 Asian Federation of Natural Language Processing
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland in the ADAPT Centre (Grant 13/RC/2106) (www.adaptcentre.ie) at Dublin City University
ID Code:23305
Deposited On:20 May 2019 13:25 by Thomas Murtagh . Last Modified 05 May 2023 16:29
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