Mining frequent intemsets in memory-resident databases
Due to the present-day memory sizes, a memory-resident database has become a practical option. Consequently, new methods designed to mining in such databases are desirable. In the case of disk-resident databases, breadth-first search methods are commonly used. We propose a new algorithm, based upon depth-first search in a set-enumeration tree. For memory-resident databases, this method turns out to be superior to breadth-first search.
|Keywords||association rules, datamining, frequent itemsets|
|Publisher||Erasmus Research Institute of Management (ERIM)|
Pijls, W.H.L.M., & Bioch, J.C.. (2000). Mining frequent intemsets in memory-resident databases (No. ERS-2000-53-LIS). Erasmus Research Institute of Management (ERIM). Retrieved from http://hdl.handle.net/1765/61