Year Report 2022 (research in the energy sector)
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Publication Type
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Supervisor
Publication Year
2023
Journal
Book
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Publication Issue
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Publication End page
Publication Number of pages
12
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Abstract
The 2022 Year Report for the PhD project between an energy business partner and Vlerick Business School highlights the research activities executed in 2022. The research began with an extensive literature review to explore the role of machine learning in analyzing customer service interactions. Emotion Recognition in Conversations (ERC) was identified as a key area of focus, and concept-based emotion detection frameworks were evaluated. Initial studies highlighted the challenges posed by inconsistent emotion labeling in existing datasets, prompting an investigation into dataset enrichment techniques. Mid-year, experiments were conducted to compare machine learning-based approaches with lexicon-based emotion detection methods. The results demonstrated the advantages of data-driven models for recognizing emotional cues in service conversations. Additionally, the research explored the integration of customer feedback with conversational data to develop predictive models for customer experience metrics. Toward the end of the year, efforts shifted toward establishing an emotion recognition pipeline and refining dataset annotation strategies to improve model accuracy and generalizability. Future research will build upon these foundations to enhance predictive modeling in service interactions.
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Keywords
Energy, Machine Learning