Another freshly minted Ph.D.!
Dr. Garima Gaur successfully defended her Ph.D. thesis titled Provenance-Aware Computation and Maintenance of Graph Query Results under Dynamic Knowledge Graphs. Her examination committee included Profs. Kamal Karlapalem (IIITH), Subhajit Roy (IIT-K), Santosha Pattanayak (IIT-K), Amey Karkare (IIT-K). Hearty congratulations to Dr. Gaur on her excellent defense presentation!
Abstract Knowledge graphs (KGs) are graphical data models that are best suited for network data such as social networks, research community networks, protein-protein interactions, etc. This is due to their intrinsic capability to represent real-world entities as nodes and capture inter-entity relationships using edges. It represents these relationships among entities as facts. Knowledge graphs are central to knowledge-centric systems ranging from drug administration to web search engines. Often, knowledge graph construction is an automated and continuous process that involves collation of information from various sources using automated knowledge extractor algorithms. The features of the construction procedure manifest different challenges for query processing over the KG. In this thesis, we have identified and addressed some of these challenges.
In this thesis, we address the research problem of how query results and their provenance can be efficiently maintained in the face of fact updates—edge addition and edge deletion—for both deterministic and probabilistic knowledge graphs. We work with conjunctive graph queries and adopt the existing semiring based how provenance model.
