UMBC ebiquity
Discovering and Querying Hybrid Linked Data

Discovering and Querying Hybrid Linked Data

Tim Finin, 9:00am 5 June 2015


New paper: Zareen Syed, Tim Finin, Muhammad Rahman, James Kukla and Jeehye Yun, Discovering and Querying Hybrid Linked Data, Third Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data, held in conjunction with the 12th Extended Semantic Web Conference, Portoroz Slovenia, June 2015.

In this paper, we present a unified framework for discovering and querying hybrid linked data. We describe our approach to developing a natural language query interface for a hybrid knowledge base Wikitology, and present that as a case study for accessing hybrid information sources with structured and unstructured data through natural language queries. We evaluate our system on a publicly available dataset and demonstrate improvements over a baseline system. We describe limitations of our approach and also discuss cases where our system can complement other structured data querying systems by retrieving additional answers not available in structured sources.

Comments are closed.