1. Mining first-order maximal frequent patterns
- Creator:
- Blaťák, Jan and Popelínský, Luboš
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- knowledge discovery in databases, inductive logic programming, relational data mining, frequent patterns, feature construction, and propositionalization
- Language:
- English
- Description:
- The frequent patterns discovery is one of the most important data mining tasks. We introduce RAP, the hrst systém for finding first-order maximal frequent patterns. We describe search strategies and methods of pruning the search space. RAP which generates long patterns much faster than other systems has been ušed for feature construction for propositional cis well as multi-relational data. We prove that a partial search for maximal frequent patterns as new features is competitive with other approaches and results in classification accuracy increase.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public