Graduate School of Science and Engineering Information and Computer Science
- Course Outline
- Laboratory for Information Theory and its Applications
- Information Systems Laboratory
- Intelligent Information Processing Laboratory
- Intelligent Mechanism Laboratory
- Intelligent Systems Design Laboratory
- Socio-informatics Laboratory
- Co-Creation Informatics Laboratory
- Applied Media Information Laboratory
- Network Information Systems Laboratory
- Intelligent Mechatro-Informatics Laboratory
- Spoken Language Processing Laboratory
Intellligent Mechanism Laboratory
Website of Assistant Professor Marie Katsurai 【In Japanese】Multimedia Understanding, Data Mining, and Visualization
Staff
OKUDA Masahiro
[Professor]
| Acceptable course | |
|---|---|
| Master's degree course | ✓ |
| Doctoral degree course | ✓ |
Telephone : 81-774-65-6976
masokuda@mail.doshisha.ac.jp
Office : KC-316
Database of Researchers
KATSURAI Marie
[Associate Professor]
| Acceptable course | |
|---|---|
| Master's degree course | ✓ |
| Doctoral degree course | |
Telephone : 81-774-65-7687
mkatsura@mail.doshisha.ac.jp
Office : KC-318
Database of Researchers
Research Topics
Multimedia Understanding: Content, Context, and Sentiment
With the popularity of image-capturing devices and the success of Web 2.0 applications, people have seen a dramatic increase in their ability to collect digital information in various situations and share them on the Web. To develop a system that automatically recognizes the content of multimedia data, we study the complementary use of multi-modal features (e.g., visual features and textual features). We also investigate how to automatically understand images’ semantics, context, and sentiment
Knowledge Acquisition From Academic Databases
Discovering hot research topics or active research groups from academic databases can contribute to grasping scientific technology trends or to promoting collaborative researches. We, in cooperation with National Institute of Informatics, develop new techniques for analyzing CiNii Articles, the largest academic database in Japan. Specifically, we study the automatic construction of researcher networks based on research topics’ similarities. Visualizing such networks can provide us with new findings about the range of researchers’ interests or changes of research themes over time.
Keywords
- Data Mining
- Multimedia Recognition
- Image Annotation
- Scientific Mapping
- Academic Database
- Pattern Recognition and Machine Learning