115 Result(s)
within
Pushpak Bhattacharyya
-
Article
Development of Process-Structure Linkage Using Conditional Generative Adversarial Networks
Quantitative characterization of microstructures and understanding of how processing influences these characteristics, subsequently affecting the final properties, are pivotal pursuits for the advancement of m...
-
Article
Learning from Failure: Towards Develo** a Disease Diagnosis Assistant That Also Learns from Unsuccessful Diagnoses
In recent years, automatic disease diagnosis has gained immense popularity in research and industry communities. Humans learn a task through both successful and unsuccessful attempts in real life, and physicia...
-
Article
Open AccessPredicting multi-label emojis, emotions, and sentiments in code-mixed texts using an emojifying sentiments framework
In the era of social media, the use of emojis and code-mixed language has become essential in online communication. However, selecting the appropriate emoji that matches a particular sentiment or emotion in th...
-
Chapter and Conference Paper
Yes, This Is What I Was Looking For! Towards Multi-modal Medical Consultation Concern Summary Generation
Over the past few years, the use of the Internet for healthcare-related tasks has grown by leaps and bounds, posing a challenge in effectively managing and processing information to ensure its efficient utiliz...
-
Chapter and Conference Paper
Material Microstructure Design Using VAE-Regression with a Multimodal Prior
We propose a variational autoencoder (VAE)-based model for building forward and inverse structure-property linkages, a problem of paramount importance in computational materials science. Our model systematical...
-
Article
Affect-GCN: a multimodal graph convolutional network for multi-emotion with intensity recognition and sentiment analysis in dialogues
Emotion classification along with sentimental analysis in dialogues is a complex task that has currently attained immense popularity. When communicating their thoughts and feelings, humans are prone to having ...
-
Chapter
Conclusions
This monograph investigated two crucial problems in relation extraction: (i) end-to-end relation extraction involving joint extraction of entities and relations, and (ii) N-ary cross-sentence relation extraction.
-
Chapter and Conference Paper
Improving Low-Resource NMT with Parser Generated Syntactic Phrases
Recently, neural machine translation (NMT) has become highly successful achieving state-of-the-art results on many resource-rich language pairs. However, it fails when there is a lack of sufficiently large amo...
-
Chapter and Conference Paper
Take Help from Elder Brother: Old to Modern English NMT with Phrase Pair Feedback
Due to the ever-changing nature of the human language and the variations in writing style, age-old texts in one language may be incomprehensible to a modern reader. In order to make these texts familiar to the...
-
Chapter and Conference Paper
Related Tasks Can Share! A Multi-task Framework for Affective Language
Expressing the polarity of sentiment as ‘positive’ and ‘negative’ usually have limited scope compared with the intensity/degree of polarity. These two tasks (i.e. sentiment classification and sentiment intensity ...
-
Chapter
Recent Advances in Entity and Relation Extraction
In this chapter, we describe a few recent advances in joint entity and relation extraction as well as N-ary cross-sentence relation extraction.
-
Chapter and Conference Paper
Emotion-Aided Multi-modal Personality Prediction System
Cyber forensics, personalized services, and recommender systems require the development of automatic personality prediction systems. Current paper works on develo** a multi-modal personality prediction syste...
-
Chapter
Introduction
With the advent of the Internet, a large amount of digital text is generated every day, such as news articles, research publications, blogs, social media, and question answering forums.
-
Chapter and Conference Paper
“News Title Can Be Deceptive” Title Body Consistency Detection for News Articles Using Text Entailment
News Title (NT) and News Body (NB) consistency detection is a demanding problem in Fake News Detection. In this paper, we formulate consistency detection between NT and NB from the perspective of Textual Entai...
-
Chapter
N-ary Cross-Sentence Relation Extraction
Most of the past work in relation extraction deals with relations occurring within a sentence and having only two entity arguments.
-
Chapter and Conference Paper
DeCoDE: Detection of Cognitive Distortion and Emotion Cause Extraction in Clinical Conversations
Despite significant evidence linking mental health to almost every major development issue, individuals with mental disorders are among those most at risk of being excluded from development programs. We outlin...
-
Chapter and Conference Paper
Techniques for Jointly Extracting Entities and Relations: A Survey
Relation Extraction is an important task in Information Extraction which deals with identifying semantic relations between entity mentions. Traditionally, relation extraction is carried out after entity extrac...
-
Chapter and Conference Paper
Multi-lingual Event Identification in Disaster Domain
Information extraction in disaster domain is a critical task for effective disaster management. A high quality event detection system is the very first step towards this. Since disaster annotated data-sets are...
-
Chapter
Literature Survey
In this chapter, we describe some of the relevant past literature on Relation Extraction.
-
Chapter
Joint Model for End-to-End Relation Extraction
In this chapter, we propose a new approach which combines Neural Networks and Markov Logic Networks to address all the three sub-tasks of end-to-end relation extraction jointly—(i) identifying boundaries of en...
