Digital Library

KIPS Transactions on Software and Data Engineering, Vol. 7, No. 11, Nov. 2018


The Method to Reduce the Driving Time of Gentry
Kim Soon Ho, Kim Chi Su
KIPS Transactions on Software and Data Engineering, Vol. 7, No. 11, pp. 405-410, Nov. 2018
10.3745/KTSDE.2018.7.11.405
Keywords: SMT, SMD, Gantry, Vision Inspection, Driving Time

Automatic Object Extraction from Electronic Documents Using Deep Neural Network
Heejin Jang, Yeonghun Chae, Sangwon Lee, Jinyong Jo
KIPS Transactions on Software and Data Engineering, Vol. 7, No. 11, pp. 411-418, Nov. 2018
10.3745/KTSDE.2018.7.11.411
Keywords: Object Extraction, Deep Learning, Tensorflow, PDF Document

Sentiment Analysis of Foot-and-Mouth Disease Using Tweet Text-Mining Technique
Heechan Chae, Jonguk Lee, Yoona Choi, Daihee Park, Yongwha Chung
KIPS Transactions on Software and Data Engineering, Vol. 7, No. 11, pp. 419-426, Nov. 2018
10.3745/KTSDE.2018.7.11.419  
Keywords: Text Mining, sentiment analysis, FMD, Twitter, Deep Learning

An Analysis of Effects of Emergency Fine Dust Reduction Measures and National Petition Using Regression Analysis and Text Mining
Annie Kim, So-Hee Jeong, Hyun-Bin Choi, Hyon Hee Kim
KIPS Transactions on Software and Data Engineering, Vol. 7, No. 11, pp. 427-434, Nov. 2018
10.3745/KTSDE.2018.7.11.427
Keywords: Fine Dust, Transportation, Regression, Text Mining, topic modeling

Outlier Detection By Clustering-Based Ensemble Model Construction
Cheong Hee Park, Taegong Kim, Jiil Kim, Semok Choi, Gyeong-Hoon Lee
KIPS Transactions on Software and Data Engineering, Vol. 7, No. 11, pp. 435-442, Nov. 2018
10.3745/KTSDE.2018.7.11.435
Keywords: Streaming Data, Ensemble Method, Outlier Detection, K-Means Clustering

Building an Ontology-Based Diagnosis Process of Crohn’s Disease Using the Differentiation Rule
Dong Yeon Yoo, Ye-Seul Park, Jung-Won Lee
KIPS Transactions on Software and Data Engineering, Vol. 7, No. 11, pp. 443-450, Nov. 2018
10.3745/KTSDE.2018.7.11.443
Keywords: Medical Diagnosis, Diagnosis Process, Ontology, Crohn's Disease