Presentation 2021-03-04
A study of similarity prediction method for human activity by combining POI and GEO
Cao Qingying, Yoshikazu Ueda,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In the information-oriented society, SNS has permeated the society widely, and it is difficult to select the people who want to interact with each other from the participants. The purpose of this study is to build a judgment model for finding people with similar interests. The subject of interest is captured by classifying the photos uploaded to SNS by the DenseNet method. In addition, the range of action is captured by the shooting information GEO. The target of this time is China and Japan, and the travel route and travel time range are calculated. It was examined to calculate the similarity of human activity by using the activity data of each area of China / Japan considering staying time and POI: the similarity of the objects of interest.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Similarity of Human Activity / SNS / DenseNet / POI / GEO
Paper # LOIS2020-55
Date of Issue 2021-02-25 (LOIS)

Conference Information
Committee LOIS
Conference Date 2021/3/4(1days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Toru Kobayashi(Nagasaki Univ.)
Vice Chair Hiroyuki Toda(NTT)
Secretary Hiroyuki Toda(NTT)
Assistant Shigeru Fujimura(NTT)

Paper Information
Registration To Technical Committee on Life Intelligence and Office Information Systems
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A study of similarity prediction method for human activity by combining POI and GEO
Sub Title (in English)
Keyword(1) Similarity of Human Activity
Keyword(2) SNS
Keyword(3) DenseNet
Keyword(4) POI
Keyword(5) GEO
1st Author's Name Cao Qingying
1st Author's Affiliation Ibaraki University(Ibaraki University)
2nd Author's Name Yoshikazu Ueda
2nd Author's Affiliation Ibaraki University(Ibaraki University)
Date 2021-03-04
Paper # LOIS2020-55
Volume (vol) vol.120
Number (no) LOIS-417
Page pp.pp.47-52(LOIS),
#Pages 6
Date of Issue 2021-02-25 (LOIS)