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Shintani Lab
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A data mining lab that extracts valuable information from massive amounts of data.
AboutAbout the lab
Finding valuable information in massive amounts of data.
The Shintani Lab studies the foundational technologies for extracting valuable information that could not be found before from massive amounts of data, and their application to real-world data.
The lab studies data mining methods that efficiently process a wide variety of data even under constraints, such as data being stored in separate locations or its contents being kept confidential.
The lab also works on lifelog mining, which extracts characteristics of people's daily lives from data collected by wristband-type sensors worn on the wrist.
Key terms
- Data Mining
- Technology for extracting valuable information, which could not be found before, from massive amounts of data
- Lifelog
- Records of daily life, such as a person's movement and body temperature, measured continuously by a wristband-type sensor or similar device
- Daily Activity Classification
- Sensor data converted into categories that show what a person was doing, and from when to when
ResearchResearch themes
As technologies for making use of large-scale data, the Shintani Lab studies the foundational technologies for extracting valuable information from massive amounts of data, and their application to real-world data. It works on three areas: improving the availability and performance of data mining, lifelog mining, and information extraction from real-world data.
*Illustrative imageImproving the Availability and Performance of Data Mining
The lab studies, from both the algorithm and system sides, data mining technologies that efficiently process massive and highly diverse data and extract valuable information from it, under constraints such as distributed data placement and the need to keep data confidential.
*Illustrative imageLifelog Mining
The lab studies technologies that convert movement and body temperature data, measured 24 hours a day, 365 days a year by a wristband-type sensor, into daily activity classifications, as well as technologies that extract regularities and changes in trends of daily activities from them.
*Illustrative imageExtracting High-Value Information from Real-World Data
The lab performs data analysis that applies data mining technologies to large-scale real-world data to extract valuable information.
MembersFaculty
- Associate ProfessorTakahiko Shintani
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Xiaomi Mi band 2 18” Nahid.rajbd / CC BY-SA 4.0 (cropped)
- Improving the Availability and Performance of Data Mining: “Wikimedia Foundation Servers-8055 35” Victor Grigas / CC BY-SA 3.0 (cropped)
- Lifelog Mining: “SmartCare wrist-worn pulse oximeter” Peter H Charlton / CC BY 4.0 (cropped)
- Extracting High-Value Information from Real-World Data: “BMW 320i E46 instrument cluster during fuel cut-off (aka)” André Karwath aka Aka / CC BY-SA 2.5 (cropped)
- Related lab (Orihara Lab): “Young people in Hong Kong using smartphones whilst walking” Ccmsharma2 / CC BY-SA 4.0 (cropped)
- Related lab (Harada Lab): “Real-time bus tracking control room in Lebanon” UrusHyby / CC0 (cropped)
- Related lab (Kano Lab): “Simplified neural network example” Mikael Häggström, M.D. Author info - Reusing images- Conflicts of interest: None Mikael Häggström, M.D. / CC0 (cropped)
- Related lab (Sei Lab): “Playing with Kilobots” QuarkyTale / CC BY-SA 4.0 (cropped)
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