A5031254664- Semantic Web and Ontologies
- Biomedical Text Mining and Ontologies
- Data Quality and Management
- Natural Language Processing Techniques
- Service-Oriented Architecture and Web Services
- Data Management and Algorithms
- Library Science and Information Systems
- Big Data and Business Intelligence
- Digital Rights Management and Security
- Vasculitis and related conditions
- Sarcoidosis and Beryllium Toxicity Research
- Context-Aware Activity Recognition Systems
- Web Data Mining and Analysis
- Genomics and Rare Diseases
- Cell Adhesion Molecules Research
- Advanced Graph Neural Networks
- Geographic Information Systems Studies
Dublin City University
2009-2024
Trinity College Dublin
2023-2024
University of Genoa
2015-2019
Ontology alignment is performed to combine or integrate multiple knowledge bases at the elemental and structural levels. The current state-of-the-art systems use many different approaches match semantics, syntax, terminologies of ontological entities. However, most ontology depend on domain knowledge, which makes process domain-specific. To address this challenge, we aim developing an approach that independent knowledge. achieve goal, proposed exploits unsupervised learning method using a...
This work describes the application of semantic web standards to data quality governance production pipelines in architectural, engineering, and construction (AEC) domain for Ordnance Survey Ireland (OSi). It illustrates a new approach based on establishing unified knowledge graph measurements across complex, heterogeneous, quality-centric pipeline. provides first comprehensive formal mappings between models dimensions defined by four International Organization Standardization (ISO) World...
In recent years we have seen a proliferation of Linked Open Data (LOD) compliant datasets becoming available on the web, leading to an increased number opportunities for data consumers build smarter applications which integrate coming from disparate sources. However, often integration is not easily achievable since it requires discovering and expressing associations across heterogeneous sets. The goal this work increase discoverability reusability scholarly by integrating them highly...
The traditional Web is evolving into the of Data, which gathers huge collections structured data over distributed, heterogeneous sources. Live queries are needed to get current information out this global space. In live query processing, source selection deserves special attention, because it allows us identify sources that most likely contain relevant content. Due semantic heterogeneity however, not always easy assess relevancy. Context might help in interpreting user needs. Moreover,...