Header menu link for other important links
A novel rare itemset mining algorithm based on recursive elimination
M. Kataria, , B. Sivaselvan
Published in Springer Verlag
Volume: 731
Pages: 221 - 233
Pattern mining in large databases is the fundamental and a non-trivial task in data mining. Most of the current research focuses on frequently occurring patterns, even though less frequently/rarely occurring patterns benefit us with useful information in many real-time applications (e.g., in medical diagnosis, genetics). In this paper, we propose a novel algorithm for mining rare itemsets using recursive elimination (RELIM)-based method. Simulation results indicate that our approach performs efficiently than existing solution in time taken to mine the rare itemsets. © Springer Nature Singapore Pte Ltd 2019.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing
PublisherData powered by TypesetSpringer Verlag