Value to User’s Voice: A Generative AI Framework for Actionable Insights from Customer Reviews in Consumer Electronics

Radhika Mundra, Bhavesh Kukreja, Aritra Ghosh Dastidar, Kartikey Singh, Javaid Nabi


Abstract
Customer reviews are a valuable asset for businesses, especially in the competitive consumer electronics sector, where understanding user preferences and product performance is critical. However, extracting meaningful insights from these unstructured and often noisy reviews is a challenging task that typically requires significant manual effort. We present
Anthology ID:
2024.icon-1.39
Volume:
Proceedings of the 21st International Conference on Natural Language Processing (ICON)
Month:
December
Year:
2024
Address:
AU-KBC Research Centre, Chennai, India
Editors:
Sobha Lalitha Devi, Karunesh Arora
Venue:
ICON
SIG:
Publisher:
NLP Association of India (NLPAI)
Note:
Pages:
337–348
Language:
URL:
https://aclanthology.org/2024.icon-1.39/
DOI:
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Cite (ACL):
Radhika Mundra, Bhavesh Kukreja, Aritra Ghosh Dastidar, Kartikey Singh, and Javaid Nabi. 2024. Value to User’s Voice: A Generative AI Framework for Actionable Insights from Customer Reviews in Consumer Electronics. In Proceedings of the 21st International Conference on Natural Language Processing (ICON), pages 337–348, AU-KBC Research Centre, Chennai, India. NLP Association of India (NLPAI).
Cite (Informal):
Value to User’s Voice: A Generative AI Framework for Actionable Insights from Customer Reviews in Consumer Electronics (Mundra et al., ICON 2024)
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PDF:
https://aclanthology.org/2024.icon-1.39.pdf