Querying CityGML Data through Virtual Knowledge Graphs

Querying Large-scale Knowledge Graphs

Querying Large-scale Knowledge Graphs Shengqi Yang With the rise of the Internet, social computing and numerous mobile applications have brought about a large amount of unstructured entity data, including places, events, and things. On one hand, the entity data, populated by a variety of data sources, is growing at an ever increasing speed. On the other hand, the service suppliers expect to ren...

Querying Incomplete Graphs with Data

Graph databases underlie several modern applications such as social networks and the Semantic Web. In those scenarios, integrating and exchanging data is very common, which leads to proliferation of incomplete graph data. However, the well developed models of incompleteness of data do not apply to graph data. This is mainly due to the fact that standard graph query languages concentrate on grap...

Exploratory Querying of Extended Knowledge Graphs

Knowledge graphs (KGs) are important assets for search, analytics, and recommendations. However, querying a KG to explore entities and discover facts is difficult and tedious, even for users with skills in SPARQL. First, users are not familiar with the structure and labels of entities, classes and relations. Second, KGs are bound to be incomplete, as they capture only major facts about entities...

Explaining and Querying Knowledge Graphs by Relatedness

We demonstrate RECAP, a tool that explains relatedness between entities in Knowledge Graphs (KGs) and implements a query by relatedness paradigm that allows to retrieve entities related to those in input. One of the peculiarities of RECAP is that it does not require any data preprocessing and can combine knowledge from multiple KGs. The underlying algorithmic techniques are reduced to the execu...

Querying data through ontologies