Knowledge discovery refers to discovering intelligent data from a huge set of digital database. The quantity of information and data is so much that one could get lost in it. How do we sort about and move such huge quantities of data? Well today there are specialized techniques that are used to move around data, analyze them and also identify useful patterns within them. This is the process called knowledge discovery in data base and data mining is an application of knowledge discovery.
Knowledge discovery is actually from the field of computer science and the term software mining is related to data mining where knowledge discovery is made from existing software systems.
The following are the input data for knowledge discovery.
- Gene/protein sequences
- Data warehouses
- TextGraph mining (molecules)
Once knowledge discovery has been made it has to be used and applied in different areas. Hence the output of discovered data is very important. Some of the knowledge discovery data output formats include,
- KDM (knowledge discovery meta model)
- Knowledge representation in Artificial intelligence
- Business rule/ logicSoftware metric
- BPMN (business process modeling notations)
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