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 …

Data quality is one of the most important problems in data management. A database system
typically aims to support the creation, maintenance and use of large amount of data …

Entity matching (EM), also known as entity resolution, fuzzy join, and record linkage, refers to
the process of identifying records corresponding to the same real-world entities from …

To accurately match records it is often necessary to utilize the semantics of the data.
Functional dependencies (FDs) have proven useful in identifying tuples in a clean relation …

We present a declarative framework for collective deduplication of entity references in the
presence of constraints. Constraints occur naturally in many data cleaning domains and can …

The importance of difference semantics (eg,“similar” or “dissimilar”) has been recently
recognized for declaring dependencies among various types of data, such as numerical …

Data warehouses consolidate various activities of a business and often form the backbone
for generating reports that support important business decisions. Errors in data tend to creep …

Named entity recognition aims at extracting named entities from unstructured text. A recent
trend of named entity recognition is finding approximate matches in the text with respect to a …

This paper investigates constraints for matching records from unreliable data sources.(a) We
introduce a class of matching dependencies (md s) for specifying the semantics of unreliable …

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