GPS , FLAG FLAG Twitter FLAG SNS GPS 6 2. [2] LLCDM Twitter SNS Foursquare Abe [3] GPS Abe GPS Daniel [4] GPS k-means Jong [5] G

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1 FLAG: 1 1,a) 1,b) GPS GPS FLAG FLAG Twitter FLAG 6 FLAG 2 FLAG,, GPS, FLAG: Lifelog aggregation system that was centered on position information Abstract: Recently, the application and the service which utilize location information from GPS have highly prevailed. In this paper, we developed the system called FLAG which aggregates the variety of Lifelog under location information. FLAG manages location information discriminate between moving and staying. With using FLAG, we visualize categorized location information on the map and the time table. And implement set the function which registers individual name according to users in the staying state. We also link the location information from FLAG to Twitter using the posting time for an example of aggregating various kinds of Lifelog, This function enables Lifelog to show on the map even if the Lifelog has no positional information. For an evaluation of the FLAG system, we created correct data of staying by six users. And we compared accuracies of staying by using two detection methods. As a result, we confirmed that FLAG can be detected high accuracy staying than the original data. Keywords: Lifelog, Location information, GPS, Behavior segmentation 1. GPS Global Positioning System Twitter *1 SNS [1] 1 Tsushima-naka 3 1 1, Kita-ku, Okayama, , Japan a) hara@okayama-u.ac.jp b) abe@cs.okayama-u.ac.jp *1 Twitter API Evernote *2 FLAG Flag management system for Lifelog and social data Aggregation FLAG GPS FLAG 2 *2 1

2 GPS , FLAG FLAG Twitter FLAG SNS GPS 6 2. [2] LLCDM Twitter SNS Foursquare Abe [3] GPS Abe GPS Daniel [4] GPS k-means Jong [5] GPS [6] 位置情報解析 デ タ ベ ス 編集機能 GPS データのアップロード 時間 緯度 経度の抽出 名称登録データベース 滞在 に個別の名称登録 逆ジオコーディングによる住所設定 滞在地 と 移動経路 に分類 位置情報データベース 滞在地 と 移動経路 の追加 飛び値の削除 地図上へ可視化 KML 作成 可視化機能 タイムテーブルへ可視化 アクティビティデータベース 行動のタスク付け SNS サービスと連携 1 FLAG Fig. 1 Primary function of FLAG 3. FLAG FLAG FLAG 1 GPS WWW 1 *3 SNS FLAG FLAG FLAG 1 MongoDB *4 MongoDB NoSQL RDBMS MongoDB *3 Yahoo! API jp/ *4 MongoDB 2

3 (i) (ii) (iii) 1 r 1 Table 1 2 FLAG Fig. 2 Interface screen of FLAG Development language and library GPS Perl MongoDB Perl Mojolicious Perl Mojolicious::Plugin::Mongodb Net::Twitter JavaScript HTML CSS JavaScript Google Maps JavaScript API v3 jquery OpenLayers DatePicker CSS BootStrap Google Chrome 32.0 Mozilla Firefox FLAG 1 GPS GPS P 1, P 2,, P N P i 1 P i P i P i+1 x i = 1, n P 1 P 2 P n 1 P N P i P i 1 P i P i P i+1 GPS P i S 1, S 2,, S N S i, S i+1,, S i+j r t S i S i+j FLAG GPS 2 1 P i P i P i+1 r P i+1 r t t 2 GPS GPS y GPS z GPS GPS z 3.3 Foursquare *5 API Foursquare API 3 *5 Foursquare 3

4 Fig. 3 3 Execution screen of name registration of staying Fig. 5 5 Execution screen of additional moving 2 Table 2 Position information management database The value created by the stay st time ed time loc detail loc center place name address dwell time Fig. 4 4 Execution screen of additional staying 3 FLAG Table 3 Parameter settings in FLAG x r t 2 y 3 z 0.5 m/s 300 m m 300 m 3.4 GPS FLAG GoogleAPI *6 A B *6 GoogleAPI FLAG FLAG 2 NoSQL RDBMS FLAG FLAG TwitterAPI *7 Twitter 7 FLAG FLAG *7 TwitterAPI 4

5 4 GPS Table 4 GPS data collection status of each subject 1 h A B C D E F Fig. 6 6 FLAG Visualization of position information in FLAG データベース 4 時間から位置情報の検索 6 位置情報 時間 :10/30 14:20 5 住所と名称を返却 内容 : ラーメン旨かった 住所 : 表町 3 丁目 名称 : 麺屋 FLAG 1 アプリ認証 ユーザ 2 つぶやき取得要求 3 時間と内容を返却 Twitter 時間 :10/30 14:20 内容 : ラーメン旨かった! 7 FLAG Twitter Fig. 7 Grant of location information to tweet conducted by Time synchronization feature of FLAG. A F GPS 24 GPS 30 GPS Global Sat DG GPS 4.2 GPS 6 FLAG GPS FLAG , Twitter FLAG Fig. 8 Example of displaying the tweet location on the map. (i) (ii) (iii) 5 TP: true positive (i) FP: false positive FN: false negative 8 Twitter 4. FLAG recall rate precision rate F F-measure F β = 1 (R) = (P ) = T P T P + F P T P T P + F N (1) (2) 4.1 GPS 6 F = (β2 + 1)RP β 2 P + R (3) 5

6 5 Table 5 Evaluation results of stay detection in each evaluation method. F Table 6 Detection result of each user by method one. A B C NaN D E NaN F NaN 7 2 Table 7 Detection result of each user by method two. A B C D E F GPS F 5 GPS F GPS TP FP / 6 1 C E F 1 A B D GPS B 4.6 D B A E F 20 B FLAG FLAG Twitter FLAG 2 F Twitter GPS F β FLAG GPS GPS [1] NII Today vol. 55 pp Mar [2], LOIS, vol.111, no.470, pp , Mar [3] M. Abe, et al., A life log collecting system supported by smartphone to model higher-level human behaviors, CISIS 2012 pp , Palermo, Italy, Jul [4] A. Daniel, et al., Using GPS to learn significant locations and predict movement across multiple users, Personal and Ubiquitous Computing, vol.7, no.5, pp , Oct [5] K. Jong, et al., Extracting places from traces of locations, Proc. WMASH 04, pp , [6], OIS vol.108 no.156 pp.7 12 Jul

7 4.2 (1) (R) = T P T P +F P 4.2 (2) (P ) = T P T P +F N (R) = (P ) = T P T P T +F P N T P +F P 5 F F GPS GPS

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