An Algorithm for Inferring Big Data Objects Correlation Using Word Net
Mohamed Basel Almourad, Mohammed Abdulla Hussain, Talal Bonny · Procedia Computer Science · 2016
The value of big data comes from its variety where data is collected from various sources. One of the key big data challenges is identifying which data objects are relevant or refer to the same logical entity across various data sources. This challenge is traditionally known as schema matching. Due to big data velocity traditional approaches to data matching can no longer be used. In this paper we present an approach for inferring data objects correlation. We present our algorithm that relies on the objects meta-data and it consults the Word Net thesaurus