Earticle

초록

영어

Business intelligence has an important role in effective decision making to improve the business performance and opportunities by understanding the organization’s environments through the systematic process of information. This paper proposes a novel framework based on data mining technologies for making a prediction of business environment. We present a business intelligence model to predict the business performance by using dimensionality reduction as preprocessing data then applying Sequential Minimal Optimization based on the Support Vector Machine algorithm to generate future data. To examine the approach, we apply them on stock price data set obtained from Yahoo Finance.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Problem Statement and Definitions
 4. Our Approach
  4.1. Business Intelligence
  4.2. Reducing points by matching sample
  4.3. Stream time series prediction
  4.4. Predictive analysis evaluation
 5. Experimental Evaluation
  5.1. Experimental Environment and Dataset
  5.2. Experimental Results and Analysis
 6. Conclusion and Future Work
 Acknowledgements
 References

키워드

저자

• Van Vo [ School of Information Science and Engineering, Hunan University, China, Faculty of Information Technology, Ho Chi Minh University of Industry, Vietnam ]
• Luo Jiawei [ School of Information Science and Engineering, Hunan University, China ] Corresponding Author
• Bay Vo [ Information Technology College, Ho Chi Minh, Vietnam. ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605