Presentation | 2021-03-01 A Comparison of Context Analysis and Estimation Methods for Mobile Users Considering the Time Series of Data Hiromi Shimizu, Mutsumi Suganuma, Wataru Kameyama, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Recently, the demand for analyzing mobile user’s activities has been increasing in the fields such as customer behavior analysis. In our previous study, we conduct mobile user’s context analysis and estimation using various sensor data of mobile phone and user’s bio-signals, and achieve the accuracy of more than 97% by applying convolutional neural network (CNN) considering the time series of data. However, the number of subjects is limited to 2, and the optimization of various parameters for machine learning methods is not sufficiently studied. So, in this paper, we increase the number of subjects to 8, and compare the accuracy of context analysis and estimation by examining various parameters for machine learning methods including CNN. The results show that CNN achieves the highest macro F1-score for many of the subjects where its values are more than 98%. Therefore, it is suggested that the proposed methods considering the time series of data are effective and versatile. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Mobile User / Behavior Analysis / Context Analysis / Context Estimation / Bio-signal / Sensor Data / CNN |
Paper # | CQ2020-107 |
Date of Issue | 2021-02-22 (CQ) |
Conference Information | |
Committee | MVE / IMQ / IE / CQ |
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Conference Date | 2021/3/1(3days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | Online |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | |
Chair | Masayuki Ihara(NTT) / Toshiya Nakaguchi(Chiba Univ.) / Hideaki Kimata(NTT) / Hideyuki Shimonishi(NEC) |
Vice Chair | Kiyoshi Kiyokawa(NAIST) / Mitsuru Maeda(Canon) / Kenya Uomori(Osaka Univ.) / Kazuya Kodama(NII) / Keita Takahashi(Nagoya Univ.) / Jun Okamoto(NTT) / Takefumi Hiraguri(Nippon Inst. of Tech.) |
Secretary | Kiyoshi Kiyokawa(Oosaka Inst. of Tech.) / Mitsuru Maeda(NTT) / Kenya Uomori(Univ. of ToKyo) / Kazuya Kodama(Shizuoka Univ.) / Keita Takahashi(Sony Semiconductor Solutions) / Jun Okamoto(KDDI Research) / Takefumi Hiraguri(Nagoya Inst. of Tech.) |
Assistant | Naoya Isoyama(NAIST) / Takenori Hara(DNP) / Mitsuhiro Goto(NTT) / Hiroaki Kudo(Nagoya Univ.) / Masaru Tsuchida(NTT) / Keita Hirai(Chiba Univ.) / Shunsuke Iwamura(NHK) / Shinobu Kudo(NTT) / Yoshiaki Nishikawa(NEC) / Takuto Kimura(NTT) / Ryoichi Kataoka(KDDI Research) |
Paper Information | |
Registration To | Technical Committee on Media Experience and Virtual Environment / Technical Committee on Image Media Quality / Technical Committee on Image Engineering / Technical Committee on Communication Quality |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | A Comparison of Context Analysis and Estimation Methods for Mobile Users Considering the Time Series of Data |
Sub Title (in English) | |
Keyword(1) | Mobile User |
Keyword(2) | Behavior Analysis |
Keyword(3) | Context Analysis |
Keyword(4) | Context Estimation |
Keyword(5) | Bio-signal |
Keyword(6) | Sensor Data |
Keyword(7) | CNN |
1st Author's Name | Hiromi Shimizu |
1st Author's Affiliation | Waseda University(Waseda Univ.) |
2nd Author's Name | Mutsumi Suganuma |
2nd Author's Affiliation | Waseda University(Waseda Univ.) |
3rd Author's Name | Wataru Kameyama |
3rd Author's Affiliation | Waseda University(Waseda Univ.) |
Date | 2021-03-01 |
Paper # | CQ2020-107 |
Volume (vol) | vol.120 |
Number (no) | CQ-392 |
Page | pp.pp.1-5(CQ), |
#Pages | 5 |
Date of Issue | 2021-02-22 (CQ) |