Typographical data entry errors and incomplete documents, produce imperfect records in real world databases. These errors generate distinct records which belong to the same entity. The aim of Approximate Record Matching is to find multiple records which belong to an entity. In this paper, an algorithm for Approximate Record Matching is proposed that can be adapted automatically with input error...

typographical data entry errors and incomplete documents, produce imperfect records in real world databases. these errors generate distinct records which belong to the same entity. the aim of approximate record matching is to find multiple records which belong to an entity. in this paper, an algorithm for approximate record matching is proposed that can be adapted automatically with input error...

When data stores grow large, data quality, cleaning, and integrity become issues. The commercial sector spends a massive amount of time and energy canonicalizing customer and product records as their lists of products and consumers expand. An Accenture study in 2006 found that a high-tech equipment manufacturer saved $6 million per year by removing redundant customer records used in customer ma...

This paper seeks to describe the business requirements imposed on a record matching system along ten different dimensions. For each dimension, we present alternative requirements which different record matching clients might have. We seek to discuss the factors that might lead a client to determine that they have one requirement or another. The goal of the talk is to better prepare a client to ...

This paper describes the key features of an innovative record matching system called ChoiceMaker 2 developed by ChoiceMaker Technologies (CMT). We begin with an overview of the stages that a record matching system goes through to find an incoming “query record” in a database. We then consider the stages one by one: We sketch out our patent-pending process for identifying possible matches to the...

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, based on the semantics of the data. For all the reasons that FDs and their inference are needed, it is also important to develop dependencies and their reasoning techniques for matching tuples from unreliable data sou...

Every day of our lives, each of us is bombarded with an explosion of data, so that it is nearly impossible to ignore the increasing volume of and potential uses for Big Data. To tackle these difficulties, parallel and distributed computing platforms of Big Data are being considered to handle various aspects of large quantities of data. While considerable progress has been made in improving such...