Febrl - A Parallel Open Source Data Linkage System: http://datamining.anu.edu.au/linkage.html

Febrl -- A Parallel Open Source Record Linkage System

Febrl – A Freely Available Record Linkage System with a Graphical User Interface

Record or data linkage is an important enabling technology in the health sector, as linked data is a costeffective resource that can help to improve research into health policies, detect adverse drug reactions, reduce costs, and uncover fraud within the health system. Significant advances, mostly originating from data mining and machine learning, have been made in recent years in many areas of ...

A Probabilistic Deduplication, Record Linkage and Geocoding System

In many data mining projects in the health sector information from multiple data sources needs to be cleaned, deduplicated and linked in order to allow more detailed analysis. The aim of such linkages is to merge all records relating to the same entity, such as a patient. Most of the time the linkage process is challenged by the lack of a common unique entity identifier. Additionally, personal ...

A Probabilistic Geocoding System based on a National Address File

It is estimated that between 80% and 90% of governmental and business data collections contain address information. Geocoding – the process of assigning geographic coordinates to addresses – is becoming increasingly important in many application areas that involve the analysis and mining of such data. In many cases, address records are captured and/or stored in a free-form or inconsistent manne...

An Efficient way of Record Linkage System and Deduplication using Indexing techniques, Classification and FEBRL Framework

Record linkage is an important process in data integration, which is used in merging, matching and duplicate removal from several databases that refer to the same entities. Deduplication is the process of removing duplicate records in a single database. In recent years, data cleaning and standardization becomes an important process in data mining task. Due to complexity of today’s database, fin...