activity
20192025
most citedApplication of Hierarchical Temporal Memory Theory for Document Categorization

8 citations · 9 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CL2025

Decoding News Bias: Multi Bias Detection in News Articles

Bhushan Santosh Shah, Deven Santosh Shah, Vahida Attar

News Articles provides crucial information about various events happening in the society but they unfortunately come with different kind of biases. These biases can significantly d…

cs.IR2024

A Framework for Ranking Content Providers Using Prompt Engineering and Self-Attention Network

Gosuddin Kamaruddin Siddiqi, Deven Santhosh Shah, Radhika Bansal +1

This paper addresses the problem of ranking Content Providers for Content Recommendation System. Content Providers are the sources of news and other types of content, such as lifes…

cs.IR20231 cited

Local Life: Stay Informed Around You, A Scalable Geoparsing and Geotagging Approach to Serve Local News Worldwide

Deven Santosh Shah, Gosuddin Kamaruddin Siddiqi, Shiying He +1

Local news has become increasingly important in the news industry due to its various benefits. It offers local audiences information that helps them participate in their communitie…

cs.CL20218 cited

Application of Hierarchical Temporal Memory Theory for Document Categorization

Deven Shah, Pinak Ghate, Manali Paranjape +1

The current work intends to study the performance of the Hierarchical Temporal Memory(HTM) theory for automated classification of text as well as documents. HTM is a biologically i…

cs.MM2021

Distantly Supervised Semantic Text Detection and Recognition for Broadcast Sports Videos Understanding

Avijit Shah, Topojoy Biswas, Sathish Ramadoss +1

Comprehensive understanding of key players and actions in multiplayer sports broadcast videos is a challenging problem. Unlike in news or finance videos, sports videos have limited…

cs.CL2019

Predictive Biases in Natural Language Processing Models: A Conceptual Framework and Overview

Deven Shah, H. Andrew Schwartz, Dirk Hovy

An increasing number of works in natural language processing have addressed the effect of bias on the predicted outcomes, introducing mitigation techniques that act on different pa…