Radhika Mundra

Fixing paper assignments

  1. Please select all papers that belong to the same person.
  2. Indicate below which author they should be assigned to.
Provide a valid ORCID iD here. This will be used to match future papers to this author.
Provide the name of the school or the university where the author has received or will receive their highest degree (e.g., Ph.D. institution for researchers, or current affiliation for students). This will be used to form the new author page ID, if needed.

TODO: "submit" and "cancel" buttons here

2024

pdf bib
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
Proceedings of the 21st International Conference on Natural Language Processing (ICON)

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
Search
Co-authors
Venues
Fix data