Extending RapidMiner with Data Search and Integration Capabilities

نویسندگان

  • Anna Lisa Gentile
  • Sabrina Kirstein
  • Heiko Paulheim
  • Christian Bizer
چکیده

Analysts are increasingly confronted with the situation that data which they need for a data mining project exists somewhere on the Web or in an organization’s intranet but they are unable to find it. The data mining tools that are currently available on the market offer a wide range of powerful data mining methods but hardly support analysts in searching for suitable data as well as in integrating data from multiple sources. This demo shows an extension to RapidMiner, a popular data mining framework, which enables analysts to search for relevant datasets and integrate discovered data with data that they already know. In particular, we support the iterative extension of data tables with additional attributes. We will demonstrate the usage of the extension with a large corpus of tabular data extracted from Wikipedia.

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تاریخ انتشار 2016