원문정보
국제인공지능학회(구 한국인터넷방송통신학회)
The International Journal of Advanced Smart Convergence
Volume 5 Number 4
2016.12
pp.32-39
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Machine learning is a field of artificial intelligence (AI), and a technology that collects, forecasts, and analyzes securities data is developed upon machine learning. The difference between using machine learning and not using machine learning is that machine learning—seems similar to big data—studies and collects data by itself which big data cannot do. Machine learning can be utilized, for example, to recognize a certain pattern of an object and find a criminal or a vehicle used in a crime. To achieve similar intelligent tasks, data must be more effectively collected than before. In this paper, we propose a method of effectively collecting data.
목차
Abstract
1. Introduction
1.1 The Reason We Need Machine Learning for Securities Data Prediction
1.2 Drawback of Securities Data Collection
1.3. Solution of Securities Data Collection
2. Securities Data Extraction Using API
2.1. Data Extraction using API of Kiwoom Securities
2.2. Difference Between Web Crawling and API
3. Expected Effect
4. Test and Result
5. Conclusion
References
1. Introduction
1.1 The Reason We Need Machine Learning for Securities Data Prediction
1.2 Drawback of Securities Data Collection
1.3. Solution of Securities Data Collection
2. Securities Data Extraction Using API
2.1. Data Extraction using API of Kiwoom Securities
2.2. Difference Between Web Crawling and API
3. Expected Effect
4. Test and Result
5. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보