Events Calendar

AI SEMINAR

Speaker: Mohsen Taheriyan, Ph.D at USC

Talk Title: Learning the Semantics of Structured Data Sources

Series: AI Seminar

Abstract: Information sources such as relational databases, spreadsheets, XML, JSON, and Web APIs contain a tremendous amount of structured data, however, they rarely provide a semantic model to describe their contents. Semantic models of data sources capture the intended meaning of data sources by mapping them to the concepts and relationships defined by a domain ontology. Such models are the key ingredients to automate many tasks such as source discovery, data integration, and publishing semantic content on the Web. Manually modeling the semantics of data sources requires significant effort and expertise, and although desirable, building these models automatically is a challenging problem. Most of the effort to automatically build semantic models is focused on labeling the data fields (source attributes) with ontology classes and/or properties, e.g., annotating the first column of a table with the class Person and the second one with the class Movie. However, a precise semantic model needs to explicitly represent the relationships between the attributes in addition to their semantic types, e.g., stating that the person is the director of the movie. Automatically constructing such precise models is a difficult task. In this talk, I present a novel approach that exploits the knowledge from a domain ontology, the semantic models of previously modeled sources, and the vast amount of data available in the Linked Open Data (LOD) cloud to automatically learn a rich semantic model for a new source. This model represents the semantics of the new source in terms of the concepts and relationships defined by the domain ontology. The approach takes into account user corrections to learn more accurate semantic models on future data sources. Our evaluation shows that our method generates expressive semantic models for data sources and services with minimal user input.


Biography: Mohsen Taheriyan is a newly graduated PhD from the University of Southern California. He worked at Information Integration Group at ISI on learning the semantics of structured data sources. His research focus is applying Semantic Web technologies and AI techniques to understand the meaning of data. He received his B.S. in Computer Engineering from University of Tehran and his M.S. in Software Engineering from Sharif University of Technology.

Webcast: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=500df65b10044d08837b95ecc188eecf1d

Location: Information Science Institute (ISI) - 1135 - 11th fl Large CR

WebCast Link: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=500df65b10044d08837b95ecc188eecf1d

Audiences: Everyone Is Invited

Contact: Alma Nava / Information Sciences Institute