Earticle

초록

영어

As the industry grows, the amount of data grows exponentially, and data analysis using these serves as a predictable solution. As data size increases and processing speed increases, it has begun to be applied to new fields by combining artificial intelligence technology as well as simple big data analysis. In this paper, we propose a method to quickly apply a machine learning based algorithm through efficient resource allocation. The proposed algorithm allocates memory for each attribute. Learning Distinct of Attribute and allocating the right memory. In order to compare the performance of the proposed algorithm, we compared it with the existing K-means algorithm. As a result of measuring the execution time, the speed was improved.

목차

Abstract
 1. Introduction
 2. Main Subject
  2.1 WEKA API
  2.2 Experimental data
 3. Algorithm through efficient memory utilization
  3.1 Preprocessing
  3.2 Memory allocation
  3.3 Clustering
 4. Experiment result
 5. Conclusion
 References

키워드

저자

• Beom-Joo Park [ Department of Medical IT Marketing, Eulji University, Korea ]
• Min-Soo Kang [ Department of Medical IT Marketing, Eulji University, Korea ]
• Minho Lee [ Department of Food and Nutrition, Eulji University, Korea ] Corresponding author
• Yong Gyu Jung [ Department of Medical IT Marketing, Eulji University, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  The International Journal of Advanced Smart Convergence

• 간기

  계간

• pISSN

  2288-2847

• eISSN

  2288-2855

• 수록기간

  2012~2025

• 십진분류

  KDC 326 DDC 380