Y
Yuichiro Takeuchi
Researcher at University of Tokyo
Publications - 10
Citations - 314
Yuichiro Takeuchi is an academic researcher from University of Tokyo. The author has contributed to research in topics: Collaborative filtering & Recommender system. The author has an hindex of 7, co-authored 9 publications receiving 308 citations.
Papers
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Book ChapterDOI
CityVoyager: an outdoor recommendation system based on user location history
TL;DR: In this paper, a real-world recommendation system based on users' past location data history is proposed. But the system uses a newly devised place learning algorithm, which can efficiently find users' frequented places, complete with their proper names (e.g. “The Ueno Royal Museum”).
An Outdoor Recommendation System based on User Location History
TL;DR: A novel real-world recommendation system, which makes recommendations of shops based on users’ past location data history, which uses a newly devised place learning algorithm, which can efficiently find Users’ frequented places, complete with their proper names.
Journal ArticleDOI
A user-adaptive city guide system with an unobtrusive navigation interface
TL;DR: An intelligent location-aware city guide system, which adapts to each user’s preferences, and uses an intuitive “metal detector” interface for navigation, which allows users to find shops that match their tastes in the same way a metal detector would be used to detect metal objects.
Proceedings ArticleDOI
CarettaKids: a system for supporting children's face-to-face collaborative learning by integrating personal and shared spaces
Akiko Deguchi,Masanori Sugimoto,Tomokazu Yamamoto,Etsuji Yamaguchi,Fusako Kusunoki,Takao Seki,Shigenori Inagaki,Sanae Tachibana,Yuichiro Takeuchi +8 more
TL;DR: CarettaKids's feature of transition between two spaces, makes it possible for children to reflect on problems detected in a shared space so as to find solutions in their respective personal space, and to engage in an active exchange of opinions in the shared space, based on ideas generated from personal-space learning.
Proceedings ArticleDOI
User-adaptive home video summarization using personal photo libraries
TL;DR: A user-adaptive video summarization system which accounts for individual preferences by analyzing contents of the user's personal photo library, which shows that the overall approach has the potential to serve as a powerful automatic/semi-automatic video summarizing solution.