원문정보
보안공학연구지원센터(IJDTA)
International Journal of Database Theory and Application
Vol.6 No.2
2013.04
pp.1-18
피인용수 : 0건 (자료제공 : 네이버학술정보)
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
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
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자료제공 : 네이버학술정보