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20132023
most citedOverview of the HASOC Subtrack at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages

8 citations · 36 across the 12 of their papers we have counts for

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6 papers · 1 filter

cs.IR2019★ 1 cited

An Empirical Evaluation of Text Representation Schemes on Multilingual Social Web to Filter the Textual Aggression

Sandip Modha, Prasenjit Majumder

This paper attempt to study the effectiveness of text representation schemes on two tasks namely: User Aggression and Fact Detection from the social media contents. In User Aggress…

cs.IR2018★ 2 cited

Exploiting local and global performance of candidate systems for aggregation of summarization techniques

Parth Mehta, Prasenjit Majumder

With an ever growing number of extractive summarization techniques being proposed, there is less clarity then ever about how good each system is compared to the rest. Several studi…

cs.IR2018★ 6 cited

Attention based Sentence Extraction from Scientific Articles using Pseudo-Labeled data

Parth Mehta, Gaurav Arora, Prasenjit Majumder

In this work, we present a weakly supervised sentence extraction technique for identifying important sentences in scientific papers that are worthy of inclusion in the abstract. We…

cs.IR2018

Content based Weighted Consensus Summarization

Parth Mehta, Prasenjit Majumder

Multi-document summarization has received a great deal of attention in the past couple of decades. Several approaches have been proposed, many of which perform equally well and it…

cs.IR2017★ 1 cited

Re-evaluating the need for Modelling Term-Dependence in Text Classification Problems

Sounak Banerjee, Prasenjit Majumder, Mandar Mitra

A substantial amount of research has been carried out in developing machine learning algorithms that account for term dependence in text classification. These algorithms offer acce…

cs.IR2015★ 2 cited

A comparative study of approaches in user-centered health information retrieval

Harsh Thakkar, Ganesh Iyer, Prasenjit Majumder

In this paper, we survey various user-centered or context-based biomedical health information retrieval systems. We present and discuss the performance of systems submitted in CLEF…