Querying and Clustering on Knowledge Graphs: A dominant-set based approach.

Abstract

The thesis is part of the Horizon 2020 MEMEX project. MEMEX is a social project that promotes cultural heritage and social inclusion focusing on the minor communities of our society. This would be accomplished by the research and development of new technologies. The main treated topics are knowledge graphs (KG), localization based on computer vision and augmented reality. In this thesis we will focus on KG. This kind of graphs are a collection of interlinked entities and different types of edges. Each edge, with its description, represents a formal semantic. Entities, throughout descriptions and their attributes, contribute to each other creating a network which can be easily interpreted. KG in literature are not a new concept, however only in the recent years have acquired relevance in the development of new technologies. Our work will focus on their analysis, specifically in the study of clustering techniques that take into account both entities attributes and relationships semantics.