Large-scale Entity Extraction and Probabilistic Record Linkage Tuesday, August 19, 2014 Large-scale entity extraction, disambiguation and linkage in Big Data can challenge the traditional methodologies developed over the last three decades. Entity linkage, in particular, is cornerstone for a wide…
Large-scale Entity Extraction and Probabilistic Record Linkage
Large-scale Entity Extraction and Probabilistic Record Linkage
Tuesday, August 19, 2014
Large-scale entity extraction, disambiguation and linkage in Big Data can challenge the traditional methodologies developed over the last three decades. Entity linkage, in particular, is cornerstone for a wide spectrum of applications, such as Master Data Management, Data Warehousing, Social Graph Analytics, Fraud Detection and Identity Management. Traditional rules based heuristic methods usually don’t scale properly, are language specific and require significant maintenance over time.
We will introduce the audience to the use of probabilistic record linkage, also known as specificity based linkage, on Big Data, to perform language independent large-scale entity extraction, resolution and linkage across diverse sources. We will also present a live demonstration reviewing the different steps required during the data integration process (ingestion, profiling, parsing, cleansing, standardization and normalization), and show the basic concepts behind probabilistic record linkage on a real-world application.
