25 citations · 64 across the 12 of their papers we have counts for
6 papers · 1 filter
A Domain-Agnostic Neurosymbolic Approach for Big Social Data Analysis: Evaluating Mental Health Sentiment on Social Media during COVID-19
Vedant Khandelwal, Manas Gaur, Ugur Kursuncu +2
Monitoring public sentiment via social media is potentially helpful during health crises such as the COVID-19 pandemic. However, traditional frequency-based, data-driven neural net…
Grounding from an AI and Cognitive Science Lens
Goonmeet Bajaj, Srinivasan Parthasarathy, Valerie L. Shalin +1
Grounding is a challenging problem, requiring a formal definition and different levels of abstraction. This article explores grounding from both cognitive science and machine learn…
Enhancing Cross-Modal Contextual Congruence for Crowdfunding Success using Knowledge-infused Learning
Trilok Padhi, Ugur Kursuncu, Yaman Kumar +2
The digital landscape continually evolves with multimodality, enriching the online experience for users. Creators and marketers aim to weave subtle contextual cues from various mod…
A Cross Attention Approach to Diagnostic Explainability using Clinical Practice Guidelines for Depression
Sumit Dalal, Deepa Tilwani, Kaushik Roy +4
The lack of explainability using relevant clinical knowledge hinders the adoption of Artificial Intelligence-powered analysis of unstructured clinical dialogue. A wealth of relevan…
Why Do We Need Neuro-symbolic AI to Model Pragmatic Analogies?
Thilini Wijesiriwardene, Amit Sheth, Valerie L. Shalin +1
A hallmark of intelligence is the ability to use a familiar domain to make inferences about a less familiar domain, known as analogical reasoning. In this article, we delve into th…
Knowledge Graph semantic enhancement of input data for improving AI
Shreyansh Bhatt, Amit Sheth, Valerie Shalin +1
Intelligent systems designed using machine learning algorithms require a large number of labeled data. Background knowledge provides complementary, real world factual information t…