An Efficient Pruning Technique for Mining Frequent Itemsets in Spatial Databases
Journal Title: International Journal on Computer Science and Engineering - Year 2016, Vol 8, Issue 7
Abstract
Frequent Itemset Mining is evaluating the rules and relationship within the data items are optimizing it, in the large spatial databases (for e.g. Images, Docs, AVI files etc).It is one of the major problems in DM (Data mining) domain. Finding frequent item set in the large set is one of the computational complexities in mining. To improve the efficiency and performance of the mining frequent item set algorithm, the key term is to apply pruning techniques which reduces the search space and its complexity of the algorithm. Here we proposed a robust technique of pruning called SP pruning for uncertain data’s. Here our methodology is used to mine the data sources of uncertain data model. We have analyzed and implemented all well known algorithmic models for mining frequent item sets for both binaries and uncertain data’s. Our experimental results show that FPgrowth performance is high for binary data sets where our method performs at high rate of accuracy for uncertain data sets.
Authors and Affiliations
G. Parthasarathy , D. C. Tomar
Keywords
Related Articles
- EP ID EP144017
- DOI -
- Views 84
- Downloads 0
Face and Gender Recognition Using Principal Component Analysis
Face recognition is a biometric analysis tool that has enabled surveillance systems to detect humans and recognize humans without their co-operation. In this paper we evaluate the basics of the Principal Component Analys...
Assessment of Fraud Pretentious Business Region Research Articles Using Data Mining Approaches
In any organization, fraud detection and prevention is daunting task because millions of dollars lost with the different nature of fraudulent activities. Organizations got to engage intelligent and innovative techniques...
k-dominant and Extended k-dominant Skyline Computation by Using Statistics
Skyline queries have recently attracted a lot of attention for its intuitive query formulation. It can act as a filter to discard ub-optimal objects. However, a major drawback of skyline is that, in datasets with many d...
Obstacle Avoidance of mobile robot using PSO based Neuro Fuzzy Technique
Abstract— Navigation and obstacle avoidance are very important issues for the successful use of an autonomous mobile robot. To allow the robot to move between its current and final configurations without any collision wi...
Clustering of Sedimentary Basins Using Associative Neural memories (ART2)
Associative Memory (AM) research covers technologies enabling implementation of associative memory which enables thought process and links previous experience to novel situations. Each neural network system requires a me...