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SemDis: Semantic Annotation and Browsing

This application identifies named entities from a populated ontology as they appear in text (e.g, web pages). Semantic annotation and browsing to other web pages is provided through hyperlinks that are added dynamically. Semantic browsing uses data from the ontology to enable browsing using relationships of the entities defined in the ontology. For example, topic names identified and details thereof can be provided using the ontology, hyperlinks are created to other pages containing the same topic name; the data from the ontology is used to include additional links to pages that contain sub-topics and/or related topics.

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Active Semantic Documents: Active Semantic Electronic Medical Record

Active Semantic Documents (ASD) are typically XML documents which are semantic since they are automatically annotated using one or more relevant ontologies and nomenclatures. ASDs are active because they support automatic and dynamic validation, as well as decision making on the content of the document by executing relevant rules on annotations. ASDs also provide the ability to modify semantic and lexical components in an ontology-supported manner. We describe and demonstrate ASEMR application which uses ASD technology implemented using various W3C recommendations (OWL, SWRL/RQL) and Semantic Web technologies, and is deployed at the Athens Heart Center. ASEMR's objective include reducing medical errors, improving physician efficiency and improving patient satisfaction. ASEMR is showcased for the W3C interest group in Semantic Web in Health-care and Life Sciences. An evaluation of the application involving measurable criteria is in progress and will also be presented, which will exemplify a clear ROI case study.

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SemDis: Financial Irregularity Detection

This application involves an ontological approach to financial analysis and monitoring by extracting, disambiguating and merging financial data from multiple heterogeneous sources into a common ontological framework. Analysis of the data and inference of semantic relations may then be conducted in a coherent, incorporated and consistent manner. Financial inconsistencies and/or "suspicious activity" can then be detected automatically. MathML, the Mathematical Modeling Language, is being utilyzed to represent financial formulas and then extended to provide semantic provenance of data within an ontology.

For further information, please contact Amit Sheth
SemDis: Insider Threat

An Ontological approach for Document Access Problem of Insider Threat, where BRAHMS is used as RDF/S store engine. BRAHMS was used to implement algorithms for pre-computing neighborhood of entities, which were needed for document ranking.

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SemDis: Peer-to-Peer Discovery of Semantic Associations

BRAHMS is a RDF knowledge base on each of peers with implemented specific algorithms for association search inside the peer.

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SemDis: Top-k Path Query Evaluation in Semantic Web Databases

BRAHMS is an RDF storage with implemented specific algorithms (used from Java level, but pushed down to C level for speed) for handling calculation of statistics needed by Top-k system.

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