In action prediction (early action recognition), the goal is to predict the class label of an
ongoing action using its observed part so far. In this paper, we focus on online action …

Recent advances in Web-information extraction have led to the creation of several large
Knowledge Bases (KBs). Querying these KBs often results in empty answers that do not …

We show how to achieve fast autocompletion for SPARQL queries on very large knowledge
graphs. At any position in the body of a SPARQL query, the autocompletion suggests …

This paper addresses the problem of failing RDF queries. Query relaxation is one of the
cooperative techniques that allows providing users with alternative answers instead of an …

We present the Linked SPARQL Queries (LSQ) dataset, which currently describes 43.95
million executions of 11.56 million unique SPARQL queries extracted from the logs of 27 …

Recent years have witnessed the development of large knowledge bases (KBs). Due to the
lack of information about the content and schema semantics of KBs, users are often not able …

SPARQL is the standard query language used to access RDF linked data sets available on
the Web. However, designing a SPARQL query can be a tedious task, even for experienced …

Several large uncertain knowledge bases (KBs) are available on the Web where facts are
associated with a certainty degree. When querying these uncertain KBs, users seek high …

This dissertation addresses several problems in the context of publishing and consuming
Linked Data. It describes these problems from the perspectives of three stakeholders: the …

A major obstacle to the wider use of semantic technology is the perceived complexity of RDF
data by stakeholders who are not familiar with the Linked Data paradigm, or are otherwise …