4 citations · 4 across the 5 of their papers we have counts for
4 papers · 1 filter
FaiRIR: Mitigating Exposure Bias from Related Item Recommendations in Two-Sided Platforms
Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh +2
Related Item Recommendations (RIRs) are ubiquitous in most online platforms today, including e-commerce and content streaming sites. These recommendations not only help users compa…
Fairness for Whom? Understanding the Reader's Perception of Fairness in Text Summarization
Anurag Shandilya, Abhisek Dash, Abhijnan Chakraborty +2
With the surge in user-generated textual information, there has been a recent increase in the use of summarization algorithms for providing an overview of the extensive content. Tr…
A Network-centric Framework for Auditing Recommendation Systems
Abhisek Dash, Animesh Mukherjee, Saptarshi Ghosh
To improve the experience of consumers, all social media, commerce and entertainment sites deploy Recommendation Systems (RSs) that aim to help users locate interesting content. Th…
Summarizing User-generated Textual Content: Motivation and Methods for Fairness in Algorithmic Summaries
Abhisek Dash, Anurag Shandilya, Arindam Biswas +3
As the amount of user-generated textual content grows rapidly, text summarization algorithms are increasingly being used to provide users a quick overview of the information conten…