Keyword Search over RDF Datasets
Keyword search is typically associated with information retrieval systems, especially those designed for the Web. By contrast, database management systems offer sophisticated query languages to access structured data. It is up to the database applications to implement user interfaces that hide the complexity of the query language. Keyword search applications over relational databases and RDF datasets have also been studied for some time as an alternative to this traditional database interface design practice. In particular, an RDF keyword-based query processing tool can be categorized as schema-based, when it exploits the RDF schema to compile a keyword-based query into a SPARQL query, or as graph-based, when it directly explores the RDF dataset. Hitting the middle ground, there are also approaches that explore or summarize the RDF graph to guide the translation of keyword-based queries into SPARQL queries. This talk first addresses the problem of implementing keyword search for RDF datasets that do not necessarily feature an RDF schema. Then, it introduces the question of serendipitous search as a strategy to diversify answers. Finally, if briefly covers the especial case of the entity relatedness problem, which refers to the problem of exploring an RDF dataset to discover and understand how two entities are connected.
Marco A. Casanova is Full Professor at the Department of Informatics and Coordinator of the Central Planning and Evaluation Office of the Pontifical Catholic University of Rio de Janeiro – PUC-Rio. He graduated in Electronic Engineering at the Military Institute of Engineering (1974), obtained a M.Sc. in Informatics from PUC-Rio (1976) and a M.Sc. (1977) and a Ph.D. (1979) in Applied Mathematics from Harvard University. He was Graduate Program Coordinator (2005-2007) and Director (2007-2011) of the Department of Informatics of PUC-Rio. His research interests concentrate on database conceptual modeling and construction of database management systems. In July 2012, he received the Scientific Merit Award from the Brazilian Computer Society.