Future direction of incremental association rules mining

ABSTRACT

Data mining has been attracted much attention from practitioners and researchers in recent years. Association rules are one of the most important research areas of data mining. Association Rule Mining (ARM) aims to discovers the relationship between the most frequent itemsets. Many algorithms have been developed for mining static datasets. It is nontrivial to maintain such discovered rules from large datasets, this was the main idea behind Incremental Association Rules Mining (IARM), which recently has received much attention from the Data Mining researcher. In this paper, a survey of Incremental Association Rule Mining (IARM) techniques and algorithms that had been developed are categorized and analyzed.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Retrieval models

  I. Computing Methodologies
  I.6 SIMULATION AND MODELING
      I.6.4 Model Validation and Analysis
      I.6.5 Model Development
          Subjects: Modeling methodologies

General Terms:
Algorithms, Design, Performance

Keywords:
association rule mining (ARM), data mining (DM), data mining algorithms, incremental association rule mining (IARM), updating association rule mining