Major Issues in Data Mining

Major Issues in Data Mining

Mining Methodology and User Interaction Issues

Mining Different kinds of knowledge in Data Bases
A dM should cover a wide spectrum of data analysis
A dMS should be able to do interactive mining of knowledge at different levels of interactions
Incorporation of background knowledge
DMQL need to be developed to allow users to do ad hoc mining
Discovered knowledge should be able to be expressed in HLL or visual representation
A DMS should be able to handle noisy or incomplete data
Some technique to develop the interestingness of patterns

Performance Issue
DM algorithm must be efficient and scalable ie. Express at different levels of granulities
Parallel, distributed and incremental mining should be developed

Parallel
Incremental- that incorporates data updates without having to mine data again “from scratch”
Issues related to diversity of data
Handling of relational and complex type of data
Mining knowledge from heterogeneous databases and global information system