It is well understood from literature that the performance of a machine learning (ML) model is
upper bounded by the quality of the data. While researchers and practitioners have focused …

The exploration of data to extract information or knowledge to support decision making is a
critical success factor for an organization in today's society. However, several problems can …

High data quality is fundamental for today's AI-based systems. However, although data
quality has been an object of research for decades, there is a clear lack of research on …

The quality of data is a key factor that determines the performance of information systems, in
particular with regard (1) to the amount of exceptions in the execution of business processes …

The internet is currently evolving from the" Web of Documents" into the" Web of Data" where
data is available on web-scale in the so called Semantic Web (1) to retrieve information or …

Data quality tools aim at detecting and correcting data problems that affect the accuracy and
efficiency of data analysis applications. We propose a classification of the most relevant …

As discussed in section 2.1 of this thesis we regard semantic technologies “as technical
approaches that facilitate or make use of the interpretation of meaning by machines” …

In a context of Data Integration Systems (DIS) providing access to large amounts of data
extracted and integrated from autonomous data sources, users are highly concerned about …

In the big data domain, data quality assessment operations are often complex and must be
implementable in a distributed and timely manner. This article tries to generalize the quality …

Reliable decision-making and reliable information based on Semantic Web data requires
methodologies and techniques for managing the quality of the published data. To make …