Improving Efficiency of META Algorithm Using Record Reduction
Journal Title: INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY - Year 2013, Vol 8, Issue 1
Abstract
Erasable Itemset Mining is the key approach of data mining in production planning. The erasable itemset mining is the process of finding erasable itemsets that satisfy the constraint i.e. user defined threshold. Efficient algorithm to mine erasable itemsets is extremely important in data mining. Since the META Algorithm was proposed to generate the erasable itemsets. In last few years there have been several methods to improve its performance. But they do not consider the time constraint. If database is large META takes too much time to scan the database. In this paper, Author purposed an Improved META (I-META) algorithm which reduces the scanning time by reduction of production records. It also reduces the redundant generation of sub-items during trimming the candidate itemsets, which can find directly the set of erasable itemsets and removing candidate having a subset that is not erasable.
Authors and Affiliations
Shweta Bidhan, Dr. Kanwal Garg
Keywords
Related Articles
- EP ID EP650103
- DOI 10.24297/ijct.v8i1.6815
- Views 82
- Downloads 0
Logical Database Design
The design, development and implementation of every database are mainly to serve as an information hub for organisations. The database is a key factor to the success of most organisations. The process of designing a data...
Technological Approaches in Applied Social learning
Industry 4.0 covers the readiness of achieving expertise that impacts the society, strategy, talent and technology. Individual, social and economic demands pose ever-changing challenges for education and training even in...
An Evaluation for Model Testability approaches
Design for testability is a very important issue in software engineering. It becomes crucial in the case of Model Based Testing where models are generally not tested before using as input of Model Based Testing. The qual...
Economic Dispatch Optimization Using Imperialist Competitive Algorithm (ICA) and compare with PSO algorithm result
Measurement Imperialist Competitive Algorithm (ICA) is a population based stochastic optimization technique, originallydeveloped by Eberhart and Kennedy, inspired by simulation of a social psychological metaphor instea...
ANALYSIS AND COMPARISION OF SRG AND DFIG FOR WIND GENERATION APPLICATION
Renewable energy is very important topic to be study to find new sources of energy to produce electricity. The main advantages of the renewable energy are available, clean, low cost, and continuous energy.The main object...