Research
| Current |
Semantic Discovery (SemDis): Discovering Complex Relationships in Semantic Web This is an NSF Medium ITR project on Semantic Discovery: Discovering Complex Relationships in Semantic Web. The main aim in this project is to define and develop scalable implementations for operators that will support queries against RDF data stores to identify contextually relevant associations between entities. We are also exploring methods to rank the associations in order of relevance to the context of the query. My research is specifically focused on extracting subgraphs containing the most contextually relevant associations between the two given entities. Trust and Provenance in the Semantic Web Developing a model for describing and inferring over Trust and Provenance metrics of the Semantic Web. The testbed being used is SWETO - Semantic Web Technology Evaluation Ontology, populated with 811,819 entities and 1,545,320 relationships. The model enables users to quantify the amount of trust they can place in an assertion made by some source anywhere on the Semantic Web. |
| Previous |
METEOR-S: Semantic Web Services and Processes The project aims to extend Web Service industry standards like WSDL, BPEL4WS with Semantic Web technologies by applying semantics in the Annotation, Quality of Service, Discovery, Composition and Execution of web processes to achieve greater dynamism and scalability. My research focused on that calculation of Web Process QoS for the dynamic binding of Web Services. This leb to the development of a constraint analyzer which determines the optimal compatible set of Web Services. |
|
|
Willie Milnor |
