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20122024
most citedAutomatic Sarcasm Detection: A Survey

108 citations · 707 across the 92 of their papers we have counts for

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Showing cs.IRShow all

8 papers · 1 filter

cs.IR2023★ 1 cited

Decision Knowledge Graphs: Construction of and Usage in Question Answering for Clinical Practice Guidelines

Vasudhan Varma Kandula, Pushpak Bhattacharyya

In the medical domain, several disease treatment procedures have been documented properly as a set of instructions known as Clinical Practice Guidelines (CPGs). CPGs have been deve…

cs.IR2019★ 3 cited

Tale of tails using rule augmented sequence labeling for event extraction

Ayush Maheshwari, Hrishikesh Patel, Nandan Rathod +3

The problem of event extraction is a relatively difficult task for low resource languages due to the non-availability of sufficient annotated data. Moreover, the task becomes compl…

cs.IR2018★ 1 cited

Is your Statement Purposeless? Predicting Computer Science Graduation Admission Acceptance based on Statement Of Purpose

Diptesh Kanojia, Nikhil Wani, Pushpak Bhattacharyya

We present a quantitative, data-driven machine learning approach to mitigate the problem of unpredictability of Computer Science Graduate School Admissions. In this paper, we discu…

cs.IR2018★ 7 cited

Feature Assisted bi-directional LSTM Model for Protein-Protein Interaction Identification from Biomedical Texts

Shweta Yadav, Ankit Kumar, Asif Ekbal +2

Knowledge about protein-protein interactions is essential in understanding the biological processes such as metabolic pathways, DNA replication, and transcription etc. However, a m…

cs.IR2012★ 17 cited

TwiSent: A Multistage System for Analyzing Sentiment in Twitter

Subhabrata Mukherjee, Akshat Malu, A. R. Balamurali +1

In this paper, we present TwiSent, a sentiment analysis system for Twitter. Based on the topic searched, TwiSent collects tweets pertaining to it and categorizes them into the diff…

cs.IR2012★ 24 cited

WikiSent : Weakly Supervised Sentiment Analysis Through Extractive Summarization With Wikipedia

Subhabrata Mukherjee, Pushpak Bhattacharyya

This paper describes a weakly supervised system for sentiment analysis in the movie review domain. The objective is to classify a movie review into a polarity class, positive or ne…