@inproceedings{mundra-etal-2024-value,
    title = "Value to User`s Voice: A Generative {AI} Framework for Actionable Insights from Customer Reviews in Consumer Electronics",
    author = "Mundra, Radhika  and
      Kukreja, Bhavesh  and
      Dastidar, Aritra Ghosh  and
      Singh, Kartikey  and
      Nabi, Javaid",
    editor = "Lalitha Devi, Sobha  and
      Arora, Karunesh",
    booktitle = "Proceedings of the 21st International Conference on Natural Language Processing (ICON)",
    month = dec,
    year = "2024",
    address = "AU-KBC Research Centre, Chennai, India",
    publisher = "NLP Association of India (NLPAI)",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2024.icon-1.39/",
    pages = "337--348",
    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"
}