Distribution-Based Synthetic Database Generation Techniques for Itemset Mining

The resource requirements of frequent pattern mining algorithms depend mainly on the length distribution of the mined patterns in the database. Synthetic databases, which are used to benchmark performance of algorithms, tend to have distributions far different from those observed in real datasets. In this paper we focus on the problem of synthetic database generation and propose algorithms to effectively embed within the database, any given set of maximal pattern collections, and make the following contributions:

• Type: Conference
• Year: 2005
• Where: IDEAS
• Authors: Ganesh Ramesh, Mohammed Javeed Zaki, William Maniatty
• Keywords: Database, IDEAS 2005, Pattern Mining Algorithms, Synthetic Database, Synthetic Database Generation