2 citations · 3 across the 5 of their papers we have counts for
5 papers · 1 filter
MIRA: An LLM-Assisted Benchmark for Multi-Category Integrated Retrieval
Mehmet Deniz Türkmen, Suchana Datta, Dwaipayan Roy +3
Users increasingly expect modern search systems to offer a unified interface that seamlessly retrieves information from diverse data sources and formats. However, current informati…
Combining Query Performance Predictors: A Reproducibility Study
Sourav Saha, Suchana Datta, Dwaipayan Roy +2
A large number of approaches to Query Performance Prediction (QPP) have been proposed over the last two decades. As early as 2009, Hauff et al. [28] explored whether different QPP…
A Deep Learning Approach for Selective Relevance Feedback
Suchana Datta, Debasis Ganguly, Sean MacAvaney +1
Pseudo-relevance feedback (PRF) can enhance average retrieval effectiveness over a sufficiently large number of queries. However, PRF often introduces a drift into the original inf…
Deep-QPP: A Pairwise Interaction-based Deep Learning Model for Supervised Query Performance Prediction
Suchana Datta, Debasis Ganguly, Derek Greene +1
Motivated by the recent success of end-to-end deep neural models for ranking tasks, we present here a supervised end-to-end neural approach for query performance prediction (QPP).…
An Analysis of Variations in the Effectiveness of Query Performance Prediction
Debasis Ganguly, Suchana Datta, Mandar Mitra +1
A query performance predictor estimates the retrieval effectiveness of an IR system for a given query. An important characteristic of QPP evaluation is that, since the ground truth…