This chapter provides an overview of the data matching process, and describes the five
major steps involved in this process: data pre-processing (cleaning and standardisation) …

Despite the huge amount of recent research efforts on entity resolution (matching) there has
not yet been a comparative evaluation on the relative effectiveness and efficiency of …

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 …

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Cardinality estimation of an approximate substring query is an important problem in
database systems. Traditional approaches build a summary from the text data and estimate …

Accurate selectivity estimation for string predicates is a long-standing research challenge in
databases. Supporting pattern matching on strings (such as prefix, substring, and suffix) …

Due to the huge amount of involved data and time-consuming process of join operations, the
exact-match joins are rarely used for big data. The most common alternative for exact-match …

Duplicate detection, also known as entity matching or record linkage, was first defined by
Newcombe et al.[19] and has been a research topic for several decades. The challenge is to …

We present FEVER, a new evaluation platform for entity resolution approaches. The modular
structure of the FEVER framework supports the incorporation or reconstruction of many …