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1.2 COMPUTER AND INFORMATION SCIENCE
With thousands of data sources available on the web as well as within organisations, data scientists increasingly spend more time searching for data than analysing it. To ease the task of find and integrating relevant data for data mining projects, this dissertation presents two new methods for automatic table extension. Automatic table extension systems take over the task of tata discovery and data integration by adding new columns with new information (new attributes) to any table. The data values in the new columns are extracted from a given corpus of tables.
Kleppman, Benedikt. (2018). Automatic Table Extension with Open Data. M.Sc. in Computing, (Advanced Software Development,Dublin Institute of Technology.