Earticle

초록

영어

Deep learning is a rapidly growing technology repeating epoch-making development in the field of voice/text/image cognition. Its basic principle is to systematize information and let users find the pattern for themselves through the neural network using lots of layers. Technological core is anticipation by classification. This thesis uses SNS and webpage scrapping data and GIS data for consumer needs. Data will then be extracted by accurate classification for the purpose of spatial information data with deep learning algorithm. It is necessary to call shapefiles to R, improve the accessibility to data, and cross one data set to other data set areas. This thesis intends to analyze data of various environments with data analysis tool, R, and design the process combining data of spatial information and visualizing it based on deep learning algorithm

목차

Abstract
 1. Introduction
 2. Related Works
  2.1. Deep learning
  2.2. Geospatial Information Analysis
 3. Design and Analysis of Dataset
  3.1. Collection of Spatial Information Data
  3.2. Data Scrapping
  3.3. Data Processing
 4. Conclusion
 References

키워드

저자

• Se-Jeong Park [ Graduate School of Software, Soongsil University, 156-743, Seoul, Korea ]
• Kook-Hyun Choi [ Department of IT Policy and Mgmt, Graduate School of Soongsil University, 156-743, Seoul, Korea ]
• Jeawon Park [ Graduate School of Software, Soongsil University, 156-743, Seoul, Korea ]
• Jong-Bae Kim [ Graduate School of Software, Soongsil University, 156-743, Seoul, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605