Short note on Interactive Visual Data Mining and Audio Data Mining,

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 Interactive Visual Data Mining

  • In (interactive) visual data mining, visualization tools can be used in the data mining process to help users make smart data mining decisions. For example, the data distribution in a set of attributes can be displayed using colored sectors (where the whole space is represented by a circle). This display helps users determine which sector should first be selected for classification and where a good split point for this sector may be. An example of this is which is the output of a perception-based classification (PBC) system developed at the University of Munich.
                                             OR,
  • Using visualization tools in the data mining process to help users make smart data mining decisions.
  • Example

– Display the data distribution in a set of attributes using colored sectors or columns (depending on whether the whole space is represented by either a circle or a set of columns)

– Use the display to which sector should first be selected for classification and where a good split point for this sector may be.



Audio Data Mining

Audio data mining uses audio signals to indicate the patterns of data or the features of data mining results. Although visual data mining may disclose interesting patterns using graphical displays, it requires users to concentrate on watching patterns and identifying interesting or novel features within them. This can sometimes be quite tiresome. If patterns can be transformed into sound and music, then instead of watching pictures, we can listen to pitch, rhythm, tune, and melody to identify anything interesting or unusual. This may relieve some of the burdens of visual concentration and be more relaxing than visual mining. Therefore, audio data mining is an interesting complement to visual mining.

  • Uses audio signals to indicate the patterns of data or the features of data mining results
  • An interesting alternative to visual mining
  • An inverse task of mining audio (such as music) databases is to find patterns from audio data
  • Visual data mining may disclose interesting patterns using graphical displays but requires users to concentrate on watching patterns
  • Instead, transform patterns into sound and music and listen to pitches, rhythms, tune, and melody in order to identify anything interesting or unusual


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