Search Results for author: Manas Gaur

Found 21 papers, 2 papers with code

Overview of the CLPsych 2022 Shared Task: Capturing Moments of Change in Longitudinal User Posts

no code implementations NAACL (CLPsych) 2022 Adam Tsakalidis, Jenny Chim, Iman Munire Bilal, Ayah Zirikly, Dana Atzil-Slonim, Federico Nanni, Philip Resnik, Manas Gaur, Kaushik Roy, Becky Inkster, Jeff Leintz, Maria Liakata

We provide an overview of the CLPsych 2022 Shared Task, which focusses on the automatic identification of ‘Moments of Change’ in lon- gitudinal posts by individuals on social media and its connection with information regarding mental health .

A Risk-Averse Mechanism for Suicidality Assessment on Social Media

no code implementations ACL 2022 Ramit Sawhney, Atula Neerkaje, Manas Gaur

Recent studies have shown that social media has increasingly become a platform for users to express suicidal thoughts outside traditional clinical settings.

KSAT: Knowledge-infused Self Attention Transformer -- Integrating Multiple Domain-Specific Contexts

no code implementations9 Oct 2022 Kaushik Roy, Yuxin Zi, Vignesh Narayanan, Manas Gaur, Amit Sheth

Domain-specific language understanding requires integrating multiple pieces of relevant contextual information.

Specificity

Process Knowledge-Infused AI: Towards User-level Explainability, Interpretability, and Safety

no code implementations9 Jun 2022 Amit Sheth, Manas Gaur, Kaushik Roy, Revathy Venkataraman, Vedant Khandelwal

For such applications, in addition to data and domain knowledge, the AI systems need to have access to and use the Process Knowledge, an ordered set of steps that the AI system needs to use or adhere to.

Food recommendation Management

Exo-SIR: An Epidemiological Model to Analyze the Impact of Exogenous Spread of Infection

no code implementations3 May 2022 Nirmal Kumar Sivaraman, Manas Gaur, Shivansh Baijal, Sakthi Balan Muthiah, Amit Sheth

In this paper, we introduce the Exo-SIR model, an extension of the popular SIR model and a few variants of the model.

Process Knowledge-infused Learning for Suicidality Assessment on Social Media

no code implementations26 Apr 2022 Kaushik Roy, Manas Gaur, Qi Zhang, Amit Sheth

Improving the performance and natural language explanations of deep learning algorithms is a priority for adoption by humans in the real world.

ISEEQ: Information Seeking Question Generation using Dynamic Meta-Information Retrieval and Knowledge Graphs

no code implementations13 Dec 2021 Manas Gaur, Kalpa Gunaratna, Vijay Srinivasan, Hongxia Jin

To address this open problem, we propose Information SEEking Question generator (ISEEQ), a novel approach for generating ISQs from just a short user query, given a large text corpus relevant to the user query.

Information Retrieval Knowledge Graphs +3

Knowledge-intensive Language Understanding for Explainable AI

no code implementations2 Aug 2021 Amit Sheth, Manas Gaur, Kaushik Roy, Keyur Faldu

To understand and validate an AI system's outcomes (such as classification, recommendations, predictions), that lead to developing trust in the AI system, it is necessary to involve explicit domain knowledge that humans understand and use.

Decision Making Fairness

Knowledge Infused Policy Gradients with Upper Confidence Bound for Relational Bandits

no code implementations25 Jun 2021 Kaushik Roy, Qi Zhang, Manas Gaur, Amit Sheth

Contextual Bandits find important use cases in various real-life scenarios such as online advertising, recommendation systems, healthcare, etc.

Multi-Armed Bandits Music Recommendation +1

"Who can help me?": Knowledge Infused Matching of Support Seekers and Support Providers during COVID-19 on Reddit

no code implementations12 May 2021 Manas Gaur, Kaushik Roy, Aditya Sharma, Biplav Srivastava, Amit Sheth

During the ongoing COVID-19 crisis, subreddits on Reddit, such as r/Coronavirus saw a rapid growth in user's requests for help (support seekers - SSs) including individuals with varying professions and experiences with diverse perspectives on care (support providers - SPs).

Natural Language Inference

Characterization of Time-variant and Time-invariant Assessment of Suicidality on Reddit using C-SSRS

no code implementations9 Apr 2021 Manas Gaur, Vamsi Aribandi, Amanuel Alambo, Ugur Kursuncu, Krishnaprasad Thirunarayan, Jonanthan Beich, Jyotishman Pathak, Amit Sheth

In this work, we address this knowledge gap by developing deep learning algorithms to assess suicide risk in terms of severity and temporality from Reddit data based on the Columbia Suicide Severity Rating Scale (C-SSRS).

Knowledge Infused Policy Gradients for Adaptive Pandemic Control

no code implementations11 Feb 2021 Kaushik Roy, Qi Zhang, Manas Gaur, Amit Sheth

To this end, we introduce a mathematical framework for KIPG methods that can (a) induce relevant feature counts over multi-relational features of the world, (b) handle latent non-homogeneous counts as hidden variables that are linear combinations of kernelized aggregates over the features, and (b) infuse knowledge as functional constraints in a principled manner.

Decision Making

Semantics of the Black-Box: Can knowledge graphs help make deep learning systems more interpretable and explainable?

no code implementations16 Oct 2020 Manas Gaur, Keyur Faldu, Amit Sheth

The recent series of innovations in deep learning (DL) have shown enormous potential to impact individuals and society, both positively and negatively.

Knowledge Graphs

Depressive, Drug Abusive, or Informative: Knowledge-aware Study of News Exposure during COVID-19 Outbreak

no code implementations30 Jul 2020 Amanuel Alambo, Manas Gaur, Krishnaprasad Thirunarayan

Further, apart from providing informative content to the public, the incessant media coverage of COVID-19 crisis in terms of news broadcasts, published articles and sharing of information on social media have had the undesired snowballing effect on stress levels (further elevating depression and drug use) due to uncertain future.

Informativeness Semantic Parsing +1

Unsupervised Detection of Sub-events in Large Scale Disasters

no code implementations13 Dec 2019 Chidubem Arachie, Manas Gaur, Sam Anzaroot, William Groves, Ke Zhang, Alejandro Jaimes

Given the large amounts of posts, a major challenge is identifying the information that is useful and actionable.

Knowledge Infused Learning (K-IL): Towards Deep Incorporation of Knowledge in Deep Learning

no code implementations1 Dec 2019 Ugur Kursuncu, Manas Gaur, Amit Sheth

Learning the underlying patterns in data goes beyond instance-based generalization to external knowledge represented in structured graphs or networks.

Knowledge Graphs

Modeling Islamist Extremist Communications on Social Media using Contextual Dimensions: Religion, Ideology, and Hate

no code implementations18 Aug 2019 Ugur Kursuncu, Manas Gaur, Carlos Castillo, Amanuel Alambo, K. Thirunarayan, Valerie Shalin, Dilshod Achilov, I. Budak Arpinar, Amit Sheth

Our study makes three contributions to reliable analysis: (i) Development of a computational approach rooted in the contextual dimensions of religion, ideology, and hate that reflects strategies employed by online Islamist extremist groups, (ii) An in-depth analysis of relevant tweet datasets with respect to these dimensions to exclude likely mislabeled users, and (iii) A framework for understanding online radicalization as a process to assist counter-programming.

A Hybrid Recommender System for Patient-Doctor Matchmaking in Primary Care

no code implementations9 Aug 2018 Qiwei Han, Mengxin Ji, Inigo Martinez de Rituerto de Troya, Manas Gaur, Leid Zejnilovic

We partner with a leading European healthcare provider and design a mechanism to match patients with family doctors in primary care.

Collaborative Filtering Recommendation Systems

Predictive Analysis on Twitter: Techniques and Applications

1 code implementation6 Jun 2018 Ugur Kursuncu, Manas Gaur, Usha Lokala, Krishnaprasad Thirunarayan, Amit Sheth, I. Budak Arpinar

Predictive analysis of social media data has attracted considerable attention from the research community as well as the business world because of the essential and actionable information it can provide.

Social and Information Networks

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