- Intelligent Data Analytics Lab.
- Web site
- Courses - Undergraduate
- - Java Programming 2- Software Engineering Exercise- SCCP - Factory - Big Data and Situation Awareness
- Courses - Graduate
- - Advanced Internet Technology- Semantic Web Technologies- Introduction To Big Data Science
- - Semantic Web Services and Composition - Web Data Mining - Awareness Computing - Big Data Science and Infrastructure- Web Security and e-Business
- Educational Background, Biography
- - Diploma Taejeon High School, Taejeon. - Bachelor Department of Electronics, Korea University - Master Dept. of Electronics (Computer), Graduate School, Korea University - Ph.D Dept. of Electronics, Graduate School, Korea University
- Current Research Theme
- - Semantic Web Services- Awareness Computing on Big Data Infrastructure- Service Composition on Big Data
- Key Topic
- - Automatic Service Composition Framework- Global Social Service Network and Its Application- Big Data Mining and Analysis- Geo-Aware Optimal Big Data Infrastructure- Service Composition Framework on Big Data Science
- Affiliated Academic Society
- ACM, IEEE, IEICE, ISPJ, IEIE
- - Jogging, Basketball - Reading Books (Bible) and Prayer - Talking with Sincere Topics
- School days' Dream
- - Scientist
- Current Dream
- - To have a good personality as like Jesus
- - Love God with all heart and Love others as like you.
- Favorite Books
- - Bible
- Messages for Students
- - Your life is unique and more important than any others. - Set the highest and most valuable goal that you can decide, try with Your all heart and NEVER give up until it can be realized.
- Publications other than one's areas of specialization
- Service Computing on Big Data
The data explosion in recent years has led to a great rising demand for Big Data processing, and new intelligent approaches as a science are strongly required for discovering more competitive knowledge from the large data. Service Computing is a cross-disciplinary science that encompasses the science and technology of bridging the gap between business and IT services. In my research, key issues for intelligent services based on Big Data Science are studied.
- Machine Learning (Deep Learning) Applications - Neural Language Translation with Context
One of brilliant contribution of DL is language translator. We have studied on the Sequence to Sequence model and Transformer model for translation between Japanese and English. They have shown very good result. Now, a new architecture to reduce lexical ambiguity on Transformer using BERT.
- Machine Learning (Deep Learning) Applications - Other Applications on Service Computing, Medical Applications
Several applications are being studied such as discovering knowledge on service invocation using Transformer and BERT, Medical applications (Pneumonia analysis using DL, EEG signal analysis for depression patients using DL), Document classification, and Other data analysis.
- Big Data Processing and Infrastructure
Processing of big data requires a large amount of computation resource, big data infrastructure such as Hadoop and Spark of Apache support distributed processing for the big data. One important topic for parallel processing on the Big Data infrastructure is to develop faster algorithm to process the data efficiently. A new architecture for intelligent big data analytics using automatic service composition have studied during several years.
- Big Data Science using Machine Learning with Service Computing (Entire Summary)
The data explosion in recent years has led to a great rising demand for Big Data processing, and new intelligent approaches as a science are strongly required for discovering more competitive knowledge from the large data. Machine learning is a core technology for analyzing data and its technique is being developed very fast. Deep Learning (DL) is one of important technique and has applied many areas. Service Computing is a cross-disciplinary science that encompasses the science and technology of bridging the gap between business and IT services. The service computing enables to use the machine learning more intelligently. Core technologies and applications for Big Data analysis using intelligent services and machine learning are being studied as below.
- Automatic Deep Learning Service Generation
This research aims at dissemination of AI technologies to Non-AI domain people. Because there are many people who want to use AI technique such as deep learning for their business domain. A system to generate machine learning or deep learning architecture based on AI expert’s knowledge automatically and flexibly is being studied using automatic service composition technique.
- Machine Learning (Deep Learning) Applications - Automatic Ontology Generation
Extracting taxonomy such as super or sub relationship of terms from documents is studied using several DL architectures, RNN, VAE, and BERT.