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https://www.um.edu.mt/library/oar/handle/123456789/108246
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DC Field | Value | Language |
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dc.date.accessioned | 2023-04-10T09:27:34Z | - |
dc.date.available | 2023-04-10T09:27:34Z | - |
dc.date.issued | 2022 | - |
dc.identifier.citation | Agius, J.G. (2022). Automated email customer service: a local, low-resource IT scenario (Master's dissertation). | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar/handle/123456789/108246 | - |
dc.description | M.Sc.(Melit.) | en_GB |
dc.description.abstract | Email is one of most prevalent communication channels used by customers to request a service. Automated email classification can allow companies to provide more efficient and effective service. For this research, we collect and carry out classification experiments on realworld data from MITA’s service call centre. We analyze the performance of three text representation techniques, namely a TF-IDF based approach, Word2vec and GloVe, in conjunction with traditional machine learning classifiers. Since MITA uses a three-tier service hierarchy to label email requests, we assess the viability of both flat and hierarchical classification. We also fine-tuned BERT for text classification and compared it to the traditional machine learning classifiers. Moreover, we assess the effects of partial layer freezing to reduce training time while still retaining a suitable level of performance. Our study shows that fine-tuning BERT provides the best results within our IT support ticket classification scenario. However, a support vector machine classifier in conjunction with TF-IDF-based text vectors provides comparable results while requiring significantly less training time and compute resources. | en_GB |
dc.language.iso | en | en_GB |
dc.rights | info:eu-repo/semantics/openAccess | en_GB |
dc.subject | MITA (Malta) -- Customer services | en_GB |
dc.subject | Call centers -- Malta | en_GB |
dc.subject | Electronic mail systems -- Malta | en_GB |
dc.subject | Electronic mail systems -- Automation | en_GB |
dc.title | Automated email customer service : a local, low-resource IT scenario | en_GB |
dc.type | masterThesis | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.publisher.institution | University of Malta | en_GB |
dc.publisher.department | Faculty of Information and Communication Technology. Department of Artificial Intelligence | en_GB |
dc.description.reviewed | N/A | en_GB |
dc.contributor.creator | Agius, Julian George (2022) | - |
Appears in Collections: | Dissertations - FacICT - 2022 Dissertations - FacICTAI - 2022 |
Files in This Item:
File | Description | Size | Format | |
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2219ICTICS520000005951_1.PDF | 1.47 MB | Adobe PDF | View/Open |
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