Comparative Investigations and Performance Evaluation for Multiple-Level Association Rules Mining Algorithm

Provided by: National Institute of Technology Jalandhar
Topic: Big Data
Format: PDF
Various applications of computers, database technologies and automated data collection techniques require large amount of data to be collected into databases. It, therefore, creates great demands for analyzing such data and turning it into useful knowledge. Data mining or Knowledge Discovery in Database (KDD) emerges as a solution to the data analysis problem. Association rules is one of the data mining techniques that can be used to discover interesting rules or relationships among attributes in databases. It is often desirable to discover knowledge at multiple conceptual levels, which shall provide a spectrum of understanding, from general to specific, for the underlying data. Mining association rules from large data sets has been a focused topic in recent research into knowledge discovery in databases.

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