Association Rule Mining for Both Frequent and Infrequent Items Using Particle Swarm Optimization Algorithm
Journal Title: International Journal on Computer Science and Engineering - Year 2014, Vol 6, Issue 7
Abstract
In data mining research, generating frequent items from large databases is one of the important issues and the key factor for implementing association rule mining tasks. Mining infrequent items such as relationships among rare but expensive products is another demanding issue which have been shown in some recent studies. Therefore this study considers user assigned threshold values as a constraint which helps users mine those rules which are more interesting for them. In addition, in real world users may prefer to know relationships among frequent items along with infrequent ones. The particle swarm optimization algorithm is an important heuristic technique in recent years and this study uses this technique to mine association rules effectively. If this technique considers user defined threshold values, interesting association rules can be generated more efficiently. Therefore this study proposes a novel approach which includes using particle swarm optimization algorithm to mine association rules from databases. Our implementation of the search strategy includes bitmap representation of nodes in a lexicographic tree and from superset-subset relationship of the nodes it classifies frequent items along with infrequent itemsets. In addition, this approach avoids extra calculation overhead for generating frequent pattern trees and handling large memory which store the support values of candidate item sets. Our experimental results show that this approach efficiently mines association rules. It accesses a database to calculate a support value for fewer numbers of nodes to find frequent itemsets and from that it generates association rules, which dramatically reduces search time. The main aim of this proposed algorithm is to show how heuristic method works on real databases to find all the interesting association rules in an efficient way.
Authors and Affiliations
MIR MD. JAHANGIR KABIR , SHUXIANG XU , BYEONG HO KANG , ZONGYUAN ZHAO
Keywords
Related Articles
- EP ID EP126711
- DOI -
- Views 111
- Downloads 0
A PATTERN BASED KEY GENERATION TO AUTHENTICATION FOR MULTIHOP ROUTING IN WMSN
Recent research work in the Wireless Sensor Networks involves the homogeneous networks in which the sensor nodes in the specific cluster can get the key value from any other cluster. Most existing key management schemes...
An Efficient Semantic Model For Concept Based Clustering And Classification
Usually in text mining techniques the basic measures like term frequency of a term (word or phrase) is computed to compute the importance of the term in the document. But with statistical analysis, the original semantics...
Reclaiming Individuality of Mysterious Passage
Authorship attribution, the science of inferring characteristics of author from characteristics of documents written by that author become an urgent need to find the original author of anonymous text. In this paper, a no...
Cloud Computing: A solution to Geographical Information Systems (GIS) Cloud Computing and GIS
Geographical Information Systems or Geospatial Information Systems (GIS) is a collection of tools that captures, stores, analyzes, manages, and presents data that are linked to geographical locations. GIS plays an essent...
Mobile Wireless Enhanced Routing Protocol in Adhoc Networks
Adhoc network consists of peer-to-peer communicating nodes that are highly mobile. As such, an ad-hoc network lacks nfrastructure and the topology of the network changes ynamically. The task of routing data from a source...