27 citations · 95 across the 53 of their papers we have counts for
14 papers · 1 filter
Cost Characterization of Vertically Partitioned Federated Knowledge Graphs
Md Saikat Islam Khan Bappy, Oshani Seneviratne
Knowledge graphs are increasingly distributed across autonomous organizations that share an entity space but own disjoint subsets of relations, forming a vertical partition. Answer…
FedV-KGQA in Practice: Design Lessons and an Interactive Prototype
Md Saikat Islam Khan Bappy, Oshani Seneviratne
Knowledge graph question answering usually assumes that one system can reach the whole graph. In practice, facts are often held by organizations that share entity identifiers but o…
FedV-KGQA: Multi-Hop Question Answering over Vertically Partitioned Knowledge Graphs
Md Saikat Islam Khan Bappy, Oshani Seneviratne
Real-world data for knowledge graph question answering is often distributed across different organizations due to governance and data sovereignty constraints. While centralized sys…
Towards Automated Ontology Generation from Unstructured Text: A Multi-Agent LLM Approach
Abid Talukder, Maruf Ahmed Mridul, Oshani Seneviratne
Automatically generating formal ontologies from unstructured natural language remains a central challenge in knowledge engineering. While large language models (LLMs) show promise,…
A Benchmark for Gap and Overlap Analysis as a Test of KG Task Readiness
Maruf Ahmed Mridul, Rohit Kapa, Oshani Seneviratne
Task-oriented evaluation of knowledge graph (KG) quality increasingly asks whether an ontology-based representation can answer the competency questions that users actually care abo…
Explainability-Driven Quality Assessment for Rule-Based Systems
Oshani Seneviratne, Brendan Capuzzo, William Van Woensel
This paper introduces an explanation framework designed to enhance the quality of rules in knowledge-based reasoning systems based on dataset-driven insights. The traditional metho…
Trust, Accountability, and Autonomy in Knowledge Graph-based AI for Self-determination
Luis-Daniel Ibáñez, John Domingue, Sabrina Kirrane +3
Knowledge Graphs (KGs) have emerged as fundamental platforms for powering intelligent decision-making and a wide range of Artificial Intelligence (AI) services across major corpora…
Semantic Modeling for Food Recommendation Explanations
Ishita Padhiar, Oshani Seneviratne, Shruthi Chari +2
With the increased use of AI methods to provide recommendations in the health, specifically in the food dietary recommendation space, there is also an increased need for explainabi…
Applying Personal Knowledge Graphs to Health
Sola Shirai, Oshani Seneviratne, Deborah L. McGuinness
Knowledge graphs that encapsulate personal health information, or personal health knowledge graphs (PHKG), can help enable personalized health care in knowledge-driven systems. In…
Explanation Ontology: A Model of Explanations for User-Centered AI
Shruthi Chari, Oshani Seneviratne, Daniel M. Gruen +3
Explainability has been a goal for Artificial Intelligence (AI) systems since their conception, with the need for explainability growing as more complex AI models are increasingly…
Explanation Ontology in Action: A Clinical Use-Case
Shruthi Chari, Oshani Seneviratne, Daniel M. Gruen +3
We addressed the problem of a lack of semantic representation for user-centric explanations and different explanation types in our Explanation Ontology (https://purl.org/heals/eo).…
Directions for Explainable Knowledge-Enabled Systems
Shruthi Chari, Daniel M. Gruen, Oshani Seneviratne +1
Interest in the field of Explainable Artificial Intelligence has been growing for decades and has accelerated recently. As Artificial Intelligence models have become more complex,…
Foundations of Explainable Knowledge-Enabled Systems
Shruthi Chari, Daniel M. Gruen, Oshani Seneviratne +1
Explainability has been an important goal since the early days of Artificial Intelligence. Several approaches for producing explanations have been developed. However, many of these…
Knowledge Integration for Disease Characterization: A Breast Cancer Example
Oshani Seneviratne, Sabbir M. Rashid, Shruthi Chari +4
With the rapid advancements in cancer research, the information that is useful for characterizing disease, staging tumors, and creating treatment and survivorship plans has been ch…