We propose approaches based on probability statistics, signal processing, and machine learning to analyze and support intellectual creation activities.
We are conducting sentiment analysis and popularity prediction of multimedia contents. We are also studying classification and retrieval methods for data in specific domains such as map images and fashion images.
We propose a method for automatically assigning emotion scores to words not included in general dictionaries (e.g. pictographs and slang).
The system estimates the researcher's expert topic from the text of the article title, keywords, and abstract, and applies it to the search of related researchers and author identification.
Knowing people's interests helps in strategy development and marketing. Analyze large amounts of data to extract and visualize prevailing topics in each age group.