Hiroshi Ishikawa Laboratory
Professor Hiroshi Ishikawa
Big data / Real world data / Social data / Open data / Data mining / Machine learning / Artificial Intelligence / Tourism / MaaS / Lunar and planetary science
Constructing general theories and modeling frameworks on social big data to contribute to the further evolution of the social big data field
Big data, which are attracting attention as an important source of knowledge, include data derived from social media (social data), observational data derived from the real world (real world data), and open access data (open data). It is possible to discover new values by analyzing these interrelatedly, and the results of doing so can be used in important fields such as tourism, disaster prevention, MaaS (Mobility as a Service), and lunar and planetary science through analysis and prediction of users behaviors, optimization of facilities and social infrastructures, and AI (Artificial Intelligence) based scientific analysis. These kinds of data and analysis activities are collectively known as social big data.
Social big data normally have all or some of spatial information, temporal information and semantic information. For example, social data can have explicit semantics (contents and tags), but real world data only have latent semantics. On the other hand, temporal information universally exists in data and, in many cases, spatial information also exists in data due to the development of GPS. Social big data are useful, but in its present condition, there are also important research issues in analysis and visualization.
At this laboratory, in order to construct general theories and modeling frameworks on social big data, our main themes are research and development on: [1] the foundations for the visualization of analysis of temporal and spatial information; [2] the scalable and robust natural language analysis technology required for information extraction from social data; [3] technology to discover the relationships between multiple data sources required for integrated analysis; and [4] parallel visualization technology including the collection and processing of social data.
The characteristic feature of this laboratory is the provision of integrated foundations to discover and use new values and knowledge from real world data and open data by leveraging social data. It has advanced and practical aims. Our university is also contributing its international strengths to the further evolution of the big data field, which is currently strengthening. In addition, through the use of social big data, we are also contributing to the construction of “an advanced knowledge society with a dynamic industrial structure,” one of our university’s principles and “Society5.0”, one of Japanese Government goals as well. Moreover, by applying research outcomes to the resolution of various issues related to the disaster prevention, MaaS, and tourism areas in a metropolis, we are also able to contribute to the “improvement of the urban environments,” another principle of our university and an important issue for Tokyo as well.
