Ioana Manolescu

Structural Summarization of Semantic Graphs

 

Abstract:

RDF graphs comprise highly complex data, both from a structural and from a semantic perspective. This makes them hard to discover and learn, and hinders their usability.

An elegant basis for summarizing graphs is provided by the graph quotient formalism. In a nutshell, a graph quotient specifies a way to view some graph nodes as equivalent to each other, and represents a graph through its equivalence classes based on this equivalence.

I will present work carried in my last team over the last few years, on quotient summarization of semantic-rich RDF graph. In particular, I will introduce a set of summaries particularly suited for the heterogeneous structure of RDF graphs, and discuss novel results at the interplay of summarization and saturation with RDF Schema rules.

 

Bio:

Ioana Manolescu is the lead of the CEDAR Inria team, focusing on rich data analytics at cloud scale. She is a member of the PVLDB Endowment Board of Trustees, and a co-president of the ACM SIGMOD Jim Gray PhD dissertation committee. Recently, she has been a general chair of the IEEE ICDE 2018 conference, an associate editor for PVLDB 2017 and 2018, and the  program chair of SSDBBM 2016. She has co-authored more than 130 articles in international journals and conferences, and contributed to several books.  Her main research interests include data models and algorithms for computational fact-checking, performance optimizations for semistructured data and the Semantic Web, and distributed architectures for complex large data.