Knowledge exploration in public linked data ontologies

Abstract

The internet is constantly expanding across millions of web pages. Using the internet effectively is a hard skill to learn both for humans and machines. The Semantic Web is an attempt to standardize the data across the web making it accessible and usable. This thesis is meant as a practical guide to using knowledge graphs the main building blocks of the Semantic Web. A knowledge graph is a large data source with facts about millions of real and fictional entities. Wikidata and DBpedia are two publicly available knowledge graphs that we use to look at three major aspects: Understanding knowledge graphs, finding relevant information from knowledge graphs, and creating features from knowledge graphs. These three aspects will be explained by using the task of finding similar entities,specifically similar artists.