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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
DE 2021-07-24
Kanagawa KAIT IT extension center (Hybrid)
(Primary: On-site, Secondary: Online)
A Recommendation Method for Social Media Users based on Sentiment Analysis Model
Ying Hongda, Kosuke Takano (KAIT) DE2021-6
 [more] DE2021-6
OME 2020-12-25
Okinawa Okinawaken Seinen Kaikan
(Primary: On-site, Secondary: Online)
Fabrication of resistive gas sensor using reduced graphene oxide (rGO) thin films based different reduction methods and their gas sensing property.
Kosuke Takano, Eiji Itoh (Shinsyu Univ.), Hironobu Ono, Shun Goda (Nippon Shokubai) OME2020-8
In this study, we have investigated the sheet resistance Rs and the chemi-resistive gas sensing properties of the ultra-... [more] OME2020-8
- 2012-12-12
Kumamoto Kumamoto-Shintoshin-plaza Basic Investigation on Indoor Positioning System using Inertia Sensor embedded Terminal and Ultrasonic Sensors
Masaki Akiyama, Hiroyuki Shirai, Chokatsu Yara, Kosuke Takano, Shigenori Ioroi, Hiroshi Tanaka (KAIT)
Many schemes for indoor positioning have been investigated so far. The shortcoming of the system using wireless LAN is p... [more]
DE 2012-08-02
Aichi Nagoya University Information Recommender Based on User's Preference Extracted from Voice Data
Hiroshi Honda, Kosuke Takano (KAIT) DE2012-23
In this paper, we present a user preference profiling method from speech recognized information for personalized recomme... [more] DE2012-23
DE 2007-07-02
Miyagi Akiu hot springs (Sendai) Experiments of Improving a Document Vector Space Based on a Feature Extraction Method with a Dynamic Feedback Function
Kosuke Takano, Keisuke Masuda, Ami Uchiyama, Xing Chen (Kait) DE2007-32
 [more] DE2007-32
DE 2006-07-13
Niigata HOTEL SENKEI Experiments for Improving Document Retrieval Resluts based on a Feature Extraction Method.
Toshiaki Fukumura, Yuusuke Kidera, Kosuke Takano, Yukio Chen (KAIT)
We have developed an document retrieval system based on our proposed method FEM (Feature Extraction Model). In this meth... [more] DE2006-89
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