The week's pick
Reseach Article
A Novel Case base Indexing Model based on Power Set Tree
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 97 - Number 7 |
| Year of Publication: 2014 |
| Authors: Khaled El-bahnasy, Kareem Mohamed Naguib, Mostafa Aref |
10.5120/17016-7298
|
Khaled El-bahnasy, Kareem Mohamed Naguib, Mostafa Aref . A Novel Case base Indexing Model based on Power Set Tree. International Journal of Computer Applications. 97, 7 ( July 2014), 1-8. DOI=10.5120/17016-7298
Abstract
CBR has been successfully applied to the areas of planning, diagnosis, law and decision making among others. It uses useful prior cases to solve the new problems. CBR must accurately retrieve similar prior cases for getting a good performance. Throughout this thesis The Novel Case Base Indexing Model based on Power Set Tree has been introduced. A custom solution designed and built to find the unique combinations for each case in a Case Base. Then use these unique combinations to build the Case Base Index. Finally, a better algorithm has been built to balance the resources consumptions and harness them to serve the purpose of finding the unique combinations for large cases that has more than 38 finding.
References
- Yumin Chen, Duoqian Miao, Ruizhi Wangb, Keshou Wua , A rough set approach to feature selection based on power set tree, Knowledge-Based Systems, 275–281, 2011.
- Sunita Beniwal, Jitender Arora, Classification and Feature Selection Techniques in Data Mining, Department of Information Technology, Maharishi Markandeshwar University, Mullana,, August 2012, Ambala-133203, India
- Yumin Chen, Duoqian Miao, Ruizhi Wangb, Keshou Wua , A rough set approach to feature selection based on power set tree, Knowledge-Based Systems, 24 (2011) 275–281.
- Ohbyung Kwon, Jae Mun Sim, Effects of data set features on the performances of classification algorithms, Expert Systems with Applications, 40 (2013) 1847–1857
- Manyika, J. , Chi, M. , Brown, B. , Bughin, J. , Dobbs, R. , Roxburgh, C. . Big data: the next frontier for innovation, competition, and productivity. McKinsey Global Institute, 2011
- Bradbury, D. Data mining with LinkedIn. Computer Fraud and Security, 2011(10), 5–8.
- Cao, L. , Domain-driven data mining: challenges and prospects. IEEE Transactions on Knowledge and Data Engineering, 22(6), 755–769, 2010
- Yuan-Hai Shao, Wei-Jie Chen, Wen-Biao Huang, Zhi-Min Yang, Nai-Yang Deng, The best separating decision tree twin support vector machine for multi-class classification, Procedia Computer Science 17 1032 – 1038, 2013.
- Ohbyung Kwon, Jae Mun Sim, Effects of data set features on the performances of classification algorithms, Expert Systems with Applications, 40,1847–1857, 2013.
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