OIDM: Online Interactive Data Mining

نویسندگان

  • Qijun Chen
  • Xindong Wu
  • Xingquan Zhu
چکیده

Facilitated by the achievements of various data mining techniques, both academic research and industrial applications are using data mining tools to explore knowledge from various databases. However, building a mining system is a nontrivial task, especially for a data mining novice. In this paper, we present an online interactive data mining toolbox − OIDM, which provides three categories (classification, association analysis, and clustering) of data mining tools, and interacts with the user to facilitate his/her mining process. The interactive mining is accomplished through interviewing the user about his/her data mining task. OIDM can help the user find the appropriate mining algorithm, refine the mining process, and finally get the best mining results. To evaluate the system, the website of OIDM (2003) has been released. The feedback is positive. Both students and senior researchers found that OIDM would be useful in conducting data mining research.

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تاریخ انتشار 2004