2 citations · 6 across the 8 of their papers we have counts for
8 papers
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…
Cultural Analytics for Good: Building Inclusive Evaluation Frameworks for Historical IR
Suchana Datta, Dwaipayan Roy, Derek Greene +3
This work bridges the fields of information retrieval and cultural analytics to support equitable access to historical knowledge. Using the British Library BL19 digital collection…
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…
Unveiling Temporal Trends in 19th Century Literature: An Information Retrieval Approach
Suchana Datta, Dwaipayan Roy, Derek Greene +1
In English literature, the 19th century witnessed a significant transition in styles, themes, and genres. Consequently, the novels from this period display remarkable diversity. Th…
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…
On the Feasibility and Robustness of Pointwise Evaluation of Query Performance Prediction
Suchana Datta, Debasis Ganguly, Derek Greene +1
Despite the retrieval effectiveness of queries being mutually independent of one another, the evaluation of query performance prediction (QPP) systems has been carried out by measu…
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…