Partitioning approach to collocation pattern mining in limited memory environment using materialized iCPI-trees
[ 1 ] Instytut Informatyki, Wydział Informatyki, Politechnika Poznańska | [ P ] employee
2013
paper
english
EN Collocation pattern mining is one of the latest data mining techniques applied in Spatial Knowledge Discovery. We consider the problem of executing collocation pattern queries in a limited memory environment. In this paper we introduce a new method based on iCPI-tree materialization and a spatial partitioning to efficiently discover collocation patterns. We have implemented this new solution and conducted series of experiments. The results show a significant improvement in processing times both on synthetic and real world datasets.
19 - 30
WoS (15)