Ontology learning is the process of acquiring (constructing or integrating) an ontology (semi-
) automatically. Being a knowledge acquisition task, it is a complex activity, which becomes …

The widespread availability of powerful geocoding tools in commercial GIS software and the
interest in spatial analysis at the individual level have made address geocoding a widely …

This book is the result of a study path that started in 2006, when the two authors of this book
published the book Data Quality: Concepts, Methodologies and Techniques. After 8 years …

The rapid growth of the Web in the past two decades has made it the largest publicly
accessible data source in the world. Web mining aims to discover useful information or …

Entity matching is a crucial and difficult task for data integration. Entity matching frameworks
provide several methods and their combination to effectively solve different match tasks. In …

We consider the entity resolution (ER) problem (also known as deduplication, or merge–
purge), in which records determined to represent the same real-world entity are successively …

Sensitive personal data are created in many application domains, and there is now an
increasing demand to share, integrate, and link such data within and across organisations in …

Reference reconciliation is the problem of identifying when different references (ie, sets of
attribute values) in a dataset correspond to the same real-world entity. Most previous …

Gaining access to high-quality data is a vital necessity in knowledge-based decision
making. But data in its raw form often contains sensitive information about individuals …

Modern enterprise applications are forced to deal with unreliable, inconsistent and
imprecise information. Probabilistic databases can model such data naturally, but SQL query …