One of the most critical tasks for improving data quality and increasing the reliability of data
analytics is Entity Resolution (ER), which aims to identify different descriptions that refer to …

Entity Resolution (ER), a core task of Data Integration, detects different entity profiles that
correspond to the same real-world object. Due to its inherently quadratic complexity, a series …

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 …

Nowadays information is crucial in many fields such as medicine, science and business,
where databases are used effectively for information sharing. However, the databases face …

One of the most important tasks for improving data quality and the reliability of data analytics
results is Entity Resolution (ER). ER aims to identify different descriptions that refer to the …

Entity Resolution (ER) is the task of finding entity profiles that correspond to the same real-
world entity. Progressive ER aims to efficiently resolve large datasets when limited time …

Data linkage refers to the process of identifying and linking records that refer to the same
entity across multiple heterogeneous data sources. This method has been widely utilized …

We present SparkER, an ER tool that can scale practitioners' favorite ER algorithms.
SparkER has been devised to take full ad-vantage of parallel and distributed computation as …

In big data sources, real-world entities are typically represented with a variety of schemata
and formats (eg, relational records, JSON objects, etc.). Different profiles (ie …

Efficiency techniques are an integral part of Entity Resolution, since its infancy. In this
survey, we organized the bulk of works in the field into Blocking, Filtering and hybrid …