Domain-Specific Knowledge Graph Construction for Semantic Analysis

Nitisha Jain

Abstract: Knowledge graphs are widely used for systematic representation of real-world data. Large-scale, general purpose knowledge graphs, having millions of facts, have been constructed through automated techniques from publicly available datasets such as Wikipedia. However, these knowledge graphs are typically incomplete and often fail to correctly capture the semantics of the data. This holds true particularly for domain-specific data, where the generic techniques for automated knowledge graph creation often fail due to several challenges, such as lack of training data, semantic ambiguities and absence of representative ontologies. The focus of this thesis is on automated knowledge graph construction for the cultural heritage domain. The goal is to tackle the research challenges encountered during the creation of an ontology and a knowledge graph from digitized collections of cultural heritage data. This paper identifies the specific research problems for these tasks and presents a methodology and approach for a solution, along with preliminary results.