27 YouTube YouTube UGC User Generated Content CDN Content Delivery Networks LRU Least Recently Used UGC YouTube CGM Consumer Generated Media CGM CGM U

Size: px
Start display at page:

Download "27 YouTube YouTube UGC User Generated Content CDN Content Delivery Networks LRU Least Recently Used UGC YouTube CGM Consumer Generated Media CGM CGM U"

Transcription

1 YouTube

2 27 YouTube YouTube UGC User Generated Content CDN Content Delivery Networks LRU Least Recently Used UGC YouTube CGM Consumer Generated Media CGM CGM UGC UGC YouTube k-means YouTube YouTube 1

3 3 10 YouTube k-means 2

4 1 6 2 YouTube k-means YouTube

5 CCDF CCDF CCDF CCDF CCDF CCDF CCDF CCDF CCDF CCDF CCDF k-means k-means k-means Y = 3 d d = 7 Y d = 14 Y

6

7 1 YouTube[1] UGC User Generated Content OTT Over The Top (YouTube ) ISP Internet Service Provider CDN Contents Delivery Networks LRU Least Recently Used [2] UGC CGM Consumer Generated Media) CGM UGC VoD Video-on-Demand UGC [3] Digg[4] [5] YouTube 6

8 YouTube 3 [6] YouTube 1 [7] YouTube [8] Digg YouTube 30 [9] [8] x x [8] [10] YouTube [11] [12] 1 k-means YouTube [12] 1 1 k-means 7

9 1: 2 YouTube YouTube YouTube YouTube 2.1 YouTube YouTube 1 YouTube API YouTube Data API version3.0 [13] , , 900 8

10 ID YouTube API ID ID ( ID ) 1 1 YouTube API 1 1 YouTube API 1 87, YouTube [14] 1 ( 9

11 1, 000km) 30 ID ID 1 JP WestUS EastUS GB FR DE BR IN SNS Social Networking Service

12 hour 2hour 3hour 6hour CCDF e x10 6 1x10 7 View count 2: CCDF

13 day 2day 3day 7day 14day CCDF e x10 6 1x10 7 View count 3: CCDF day 2day 3day 7day 14day CCDF e x10 6 1x10 7 1x10 8 Total view count 4: CCDF 12

14 hour 4-7hour 8-11hour 12-15hour 16-19hour 20-23hour CCDF e x10 6 1x10 7 View count 5: 1 CCDF hour 4-7hour 8-11hour 12-15hour 16-19hour 20-23hour CCDF e x10 6 1x10 7 View count 6: 1 CCDF 13

15 hour 4-7hour 8-11hour 12-15hour 16-19hour 20-23hour CCDF e x10 6 1x10 7 View count 7: 7 CCDF hour 4-7hour 8-11hour 12-15hour 16-19hour 20-23hour CCDF e x10 6 1x10 7 1x10 8 Total view count 8: 7 CCDF 14

16 CCDF WestUS(5541) EastUS(9829) GB(4145) JP(3505) FR(5153) DE(4217) BR(2783) IN(5727) x10 6 View count 9: 1 CCDF CCDF WestUS(5541) EastUS(9829) GB(4145) JP(3505) FR(5153) DE(4217) BR(2783) IN(5727) x10 6 View count 10: 1 CCDF 15

17 CCDF WestUS(5541) EastUS(9829) GB(4145) JP(3505) FR(5153) DE(4217) BR(2783) IN(5727) x10 6 View count 11: 7 CCDF CCDF WestUS(5541) EastUS(9829) GB(4145) JP(3505) FR(5153) DE(4217) BR(2783) IN(5727) x10 6 1x10 7 Total view count 12: 7 CCDF 16

18 2.3 k-means n k-means YouTube [12] 1 k-means 1 k-means v n 0 1 n v k-means (a) (b) SNS (c) 13(a) (d) (a) 3 17

19 1 14(b) (c) (d) (a) (b) (c) (d) ,

20 Normalized view count cluster1 (29225) cluster2 (15564) cluster3 (17590) cluster4 (15036) cluster5 (10415) View count cluster1 (29225) cluster2 (15564) cluster3 (17590) cluster4 (15036) cluster5 (10415) Hour Hour after upload (a) (b) cluster1 (29225) cluster2 (15564) cluster3 (17590) cluster4 (15036) cluster5 (10415) cluster1 (29225) cluster2 (15564) cluster3 (17590) cluster4 (15036) cluster5 (10415) View count CCDF Day after upload 1e e+006 1e+007 View count (c) 1 (d) 7 13: k-means 19

21 Normalized view count cluster1 (25656) cluster2 (16873) cluster3 (12446) cluster4 (20304) cluster5 (12551) View count cluster1 (25656) cluster2 (16873) cluster3 (12446) cluster4 (20304) cluster5 (12551) Hour Hour after upload (a) (b) cluster1(25656) cluster2(16873) cluster3(12446) cluster4(20304) cluster5(12551) cluster1 (25656) cluster2 (16873) cluster3 (12446) cluster4 (20304) cluster5 (12551) View count CCDF Day after upload 1e e+006 1e+007 View count (c) 1 (d) 7 14: k-means 20

22 Normalized view count cluster1 (27234) cluster2 (12079) cluster3 (10727) cluster4 (18786) cluster5 (19004) View count cluster1 (27234) cluster2 (12079) cluster3 (10727) cluster4 (18786) cluster5 (19004) Hour Hour after upload (a) (b) cluster1 (27234) cluster2 (12079) cluster3 (10727) cluster4 (18786) cluster5 (19004) cluster1 (27234) cluster2 (12079) cluster3 (10727) cluster4 (18786) cluster5 (19004) View count CCDF Day after upload 1e e+006 1e+007 View count (c) 1 (d) 7 15: k-means 21

23 3 YouTube Y 3.1 A B P (B A) P (B A) = P (B)P (A B) P (A) n F 1,, F n C p(c F 1,, F n ) p(c F 1,, F n ) = p(c)p(f 1,, F n C) p(f 1,, F n ) C p(c, F 1,, F n ) = p(c)p(f 1 C)p(F 2 C)p(F 3 C) C classify classify(f 1,, f n ) = arg max c n p(c = c) p(f i = f i C = c) (1) i= H Y d H Y + d H Y Y Y 22

24 16: YouTube Data API 1 3. Y YouTube Data API Y d YouTube Data API Y + d Y Y d d 23

25 1: ID Y Y =H 1 2 Y =L abcdefghijk H lmnopqrstuv L wxyz H d 1 1% 2 d d 1% 3.1 n F 1,, F n 2.3 Y v Y 0 1 Y Y Y , 830 p(c = c) p(f i = f i C = c) p(c = c) p(f i = f i C = c) classify NBC: Naive Bayes Classifier VCS: View Count based Selection 24

26 Y d = 7 Y = % % 3 7 d = 14 Y = % % 3 14 Y = 3 d 1 17(a) 2 17(b) 1 2 d = 7 Y 1 18(a) 2 18(b) Y/3 25

27 2: % 2 8 1% : % % Y d = 14 Y 1 19(a) 2 19(b) d = 7 Y 3 26

28 1 0.8 Accuracy NBC VCS 21 d 28 (a) d Accuracy NBC VCS 21 d 28 (b) d 17: Y = 3 d 27

29 1 NBC VCS 0.8 Accuracy Y (hour) (a) d 1 NBC VCS 0.8 Accuracy Y (hour) (b) d 18: d = 7 Y 28

30 1 NBC VCS 0.8 Accuracy Y (hour) (a) d 1 NBC VCS 0.8 Accuracy Y (hour) (b) d 19: d = 14 Y 29

31 4 YouTube 1 k-means 3 Good 30

32 NTT 31

33 [1] YouTube. https://www.youtube.com/. [2] N. Kamiyama, R. Kawahara, T. Mori, and H. Hasegawa, Multicast Pre-distribution VoD System, IEICE transactions on communications, vol. E96-B, pp , June [3] K. Lerman and T. Hogg, Using a Model of Social Dynamics to Predict Popularity of News, in Proceedings of the nineteenth international conference on World Wide Web, pp , Apr [4] Digg. [5] F. Figueiredo, F. Benevenuto, and J. M. Almeida, The tube over time: characterizing popularity growth of YouTube videos, in Proceedings of the fourth ACM international conference on Web search and data mining, pp , Feb [6] Y. Borghol, S. Mitra, S. Ardon, N. Carlsson, D. Eager, and A. Mahanti, Characterizing and modelling popularity of user-generated videos, Performance Evaluation, vol. 68, pp , Nov [7] G. Gürsun, M. Crovella, and I. Matta, Describing and forecasting video access patterns, in Proceedings of IEEE INFOCOM, pp , Apr [8] G. Szabo and B. A. Huberman, Predicting the popularity of online content, Communications of the ACM, vol. 53, pp , Aug [9] H. Pinto, J. M. Almeida, and M. A. Gonçalves, Using early view patterns to predict the popularity of youtube videos, in Proceedings of the sixth ACM international conference on Web search and data mining, pp , Feb [10] G. Chatzopoulou, C. Sheng, and M. Faloutsos, A first step towards understanding popularity in YouTube, in Proceedings of INFOCOM IEEE Conference on Computer Communications Workshops, pp. 1 6, Mar [11] J. M. Tirado, D. Higuero, F. Isaila, and J. Carretero, Multi-model prediction for enhancing content locality in elastic server infrastructures, in Proceedings of the 32

34 eighteenth International Conference on High Performance Computing, pp. 1 9, Dec [12] Y. Kitade, Analyzing popularity dynamics of YouTube content and its application to content cache design, Master s thesis, Graduate School of Information Science and Technology, Osaka University, Feb [13] YouTube Data API. https://developers.google.com/youtube/v3/. [14] YouTube Help. https://support.google.com/youtube/answer/ /. 33

Web Social Networking Service Virtual Private Network 84

Web Social Networking Service Virtual Private Network 84 Promising business utilized five senses information media through the Next Generation Network Toshio ASANO Next Generation Network 2004 11 2010 6,000 3,000 2006 12 2008 83 Web Social Networking Service

More information

contents

contents 3 3 4 5 6 7 7 8 8 9 9 10 10 10 11 11 12 13 13 14 14 14 14 14 14 contents 3 3 4 5 6 7 7 8 8 9 9 10 10 10 11 11 12 13 13 14 14 14 14 14 14 01 1 22 3 3 44 studies 1 2 Hiroshima Univ. ACTIVITIES campus

More information

23

23 Master's Thesis / 修 士 論 文 映 像 配 信 の 中 断 から 復 旧 までの 時 間 を 短 縮 するネットワーク 再 構 築 手 法 の 改 良 隅 田, 貴 久 三 重 大 学, 2011. 三 重 大 学 大 学 院 地 域 イノベーション 学 研 究 科 博 士 前 期 課 程 地 域 イノベーション 学 専 攻 http://hdl.handle.net/10076/12400

More information

,, WIX. 3. Web Index 3. 1 WIX WIX XML URL, 1., keyword, URL target., WIX, header,, WIX. 1 entry keyword 1 target 1 keyword target., entry, 1 1. WIX [2

,, WIX. 3. Web Index 3. 1 WIX WIX XML URL, 1., keyword, URL target., WIX, header,, WIX. 1 entry keyword 1 target 1 keyword target., entry, 1 1. WIX [2 DEIM Forum 2013 B10-4 Web Index 223-8522 3-14-1 E-mail: haseshun@db.ics.keio.ac.jp, toyama@ics.keio.ac.jp, URL WIX, Web Web Index(WIX). WIX, WIX.,,. Web Index, Web, Web,, Related Contents Recommendation

More information

1., 1 COOKPAD 2, Web.,,,,,,.,, [1]., 5.,, [2].,,.,.,, 5, [3].,,,.,, [4], 33,.,,.,,.. 2.,, 3.., 4., 5., ,. 1.,,., 2.,. 1,,

1., 1 COOKPAD 2, Web.,,,,,,.,, [1]., 5.,, [2].,,.,.,, 5, [3].,,,.,, [4], 33,.,,.,,.. 2.,, 3.., 4., 5., ,. 1.,,., 2.,. 1,, THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS TECHNICAL REPORT OF IEICE.,, 464 8601 470 0393 101 464 8601 E-mail: matsunagah@murase.m.is.nagoya-u.ac.jp, {ide,murase,hirayama}@is.nagoya-u.ac.jp,

More information

2

2 2 485 1300 1 6 17 18 3 18 18 3 17 () 6 1 2 3 4 1 18 11 27 10001200 705 2 18 12 27 10001230 705 3 19 2 5 10001140 302 5 () 6 280 2 7 ACCESS WEB 8 9 10 11 12 13 14 3 A B C D E 1 Data 13 12 Data 15 9 18 2

More information

極地研 no174.indd

極地研 no174.indd C O N T E N T S 02 10 13 no.174 June.2005 TOPICS06 1 45 46 3 12 4546 47 14 10 15 15 16 NEWS no.174 june.2005 0 100 200 300 400 500 600 700 100 100 Diameter,nm 10 10 45 20042 Feb Mar Apr May Jun Jul Aug

More information

兵庫県立大学学報vol.17

兵庫県立大学学報vol.17 THE UNIVERSITY OF HYOGO NEWS 2014 VOL.17 THE UNIVERSITY OF HYOGO NEWS 2014 VOL.17 THE UNIVERSITY OF HYOGO NEWS 2014 VOL.17 THE UNIVERSITY OF HYOGO NEWS 2014 VOL.17 School of Human Science and Environment

More information

シリコンバレーとルート128における地域産業システムのその後の展開―経営学輪講 Saxenian (1994)

シリコンバレーとルート128における地域産業システムのその後の展開―経営学輪講 Saxenian (1994) ISSN 1347-4448 ISSN 1348-5504 8 3 (2009 3 ) 128 * Saxenian (1994) Saxenian, A. (1994). Regional advantage: Culture and competition in Silicon Valley and Route 128. Cambridge, MA: Harvard University Press.

More information

ディスプレイと携帯端末間の通信を実現する映像媒介通信技術

ディスプレイと携帯端末間の通信を実現する映像媒介通信技術 Data Transfer Technology to Enable Communication between Displays and Smart Devices 倉木健介 中潟昌平 田中竜太 阿南泰三 あらまし Abstract Recently, the chance to see videos in various places has increased due to the speedup

More information

Vol.7 6 No.3 2010 Contents June 03 06 10 14 16

Vol.7 6 No.3 2010 Contents June 03 06 10 14 16 Vol.7 2010 No.3 June 6 02 Feature 01 Feature Vol.7 6 No.3 2010 Contents June 03 06 10 14 16 6 Good 03 04 June 2010 NEW 05 06 June 2010 01 07 08 June 2010 01 09 q e w 10 June 2010 02 11 12 June 2010 02

More information

[5] [6] 23 YouTube 31% [5]. HTTP 12% YouTube 1 CoreLab [2], PlanetLab [3] [4] (In-Network ) CDN(Content Delivery Network) CDN CDN CDN CDN CDN CDN 1 IS

[5] [6] 23 YouTube 31% [5]. HTTP 12% YouTube 1 CoreLab [2], PlanetLab [3] [4] (In-Network ) CDN(Content Delivery Network) CDN CDN CDN CDN CDN CDN 1 IS THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS TECHNICAL REPORT OF IEICE. In-Network 113 0033 7 3 1 E-mail: ando@nakao-lab.org, nakao@iii.u-tokyo.ac.jp Youtube In-Network YouTube

More information

Wikipedia YahooQA MAD 4)5) MAD Web 6) 3. YAMAHA 7) 8) 2 3 4 5 6 2. Vocaloid2 2006 1 PV 2009 1 1100 200 YouTube 1 minato minato ussy 3D MAD F EDis ussy

Wikipedia YahooQA MAD 4)5) MAD Web 6) 3. YAMAHA 7) 8) 2 3 4 5 6 2. Vocaloid2 2006 1 PV 2009 1 1100 200 YouTube 1 minato minato ussy 3D MAD F EDis ussy 1, 2 3 1, 2 Web Fischer Social Creativity 1) Social Creativity CG Network Analysis of an Emergent Massively Collaborative Creation Community Masahiro Hamasaki, 1, 2 Hideaki Takeda 3 and Takuichi Nishimura

More information

ICT a) Caption Presentation Method with Speech Expression Utilizing Speech Bubble Shapes for Video Content Yuko KONYA a) and Itiro SIIO 1. Graduate Sc

ICT a) Caption Presentation Method with Speech Expression Utilizing Speech Bubble Shapes for Video Content Yuko KONYA a) and Itiro SIIO 1. Graduate Sc VOL. J98-A NO. 1 JANUARY 2015 本 PDFの 扱 いは 電 子 情 報 通 信 学 会 著 作 権 規 定 に 従 うこと なお 本 PDFは 研 究 教 育 目 的 ( 非 営 利 )に 限 り 著 者 が 第 三 者 に 直 接 配 布 すること ができる 著 者 以 外 からの 配 布 は 禁 じられている ICT a) Caption Presentation Method

More information

求人面接資料PPT

求人面接資料PPT Hair Salon TV etc. 250" 250" 200" 200" 150" 150" 100" 100" 50" 50" 0" 0" Nov)13" Dec)13" Jan)14" Feb)14" Mar)14" Apr)14" May)14" Jun)14" Jul)14" Dec)12" Jan)13" Feb)13" Mar)13" Apr)13"

More information

1. 1 1840-1919 2 1642 3 3 4 5 6 (1875-1950) 7 1879 8 1881-1946 9 10 1904-1998 11 12 1 2005 pp.17-19 2 1890 1959 p.21 3 1642 3 1893 11 1932 489,pp.340-

1. 1 1840-1919 2 1642 3 3 4 5 6 (1875-1950) 7 1879 8 1881-1946 9 10 1904-1998 11 12 1 2005 pp.17-19 2 1890 1959 p.21 3 1642 3 1893 11 1932 489,pp.340- * 12 Shigeru JOCHI ** 1642?-1708 300 1775-1849 1782-1838 1847-1931 12 1690-12 * 2007 8 21 ** (Graduate School of Japanese Studies, National Kaohsiung First University of Science and Technology) 1 1. 1

More information

スライド 1

スライド 1 JANOG 14 2004.07.23 NTT kamei.satoshi@lab.ntt.co.jp 1 Peer-to-Peer ISP P2P AS / Copyright 2004 NTT Corporation, All Rights Reserved 2 Peer-to-Peer ISP P2P AS Copyright 2004 NTT Corporation, All Rights

More information

YouTube [7] A B [8] [8] YouTube () ( ) YouTube YouTube 3. 3. 1 YouTube 3. 1. 1 YouTube Data API [6] ( 1) 2011 12 2012 1 ( ) YouTube ( 1 YouTube ) 2011

YouTube [7] A B [8] [8] YouTube () ( ) YouTube YouTube 3. 3. 1 YouTube 3. 1. 1 YouTube Data API [6] ( 1) 2011 12 2012 1 ( ) YouTube ( 1 YouTube ) 2011 DEIM Forum 2012 B4-1 700 8530 3-1-1 700 8530 3-1-1 E-mail:, {yoshio,ohta}@de.cs.okayama-u.ac.jp YouTube YouTube ( ) YouTube A recommendation system for unexpected videos using user connections Toru YOSHIO

More information

P07-08

P07-08 CLUSTER REPORT2010 http://www.noastec.jp Contents 4 3 2 1 01 02 03 04 05 06 07 12 13 16 17 18 3. 1. 2. 1 4 2 5 3 6 !? 1 2 Step.2 Step.3 Step.4 15,396 19,322 24,608 Step.1 1,051 575 27 27 145 118 476 331

More information

2 3, 4, 5 6 2. [1] [2] [3]., [4], () [3], [5]. Mel Frequency Cepstral Coefficients (MFCC) [9] Logan [4] MFCC MFCC Flexer [10] Bogdanov2010 [3] [14],,,

2 3, 4, 5 6 2. [1] [2] [3]., [4], () [3], [5]. Mel Frequency Cepstral Coefficients (MFCC) [9] Logan [4] MFCC MFCC Flexer [10] Bogdanov2010 [3] [14],,, DEIM Forum 2016 E1-4 525-8577 1 1-1 E-mail: is0111rs@ed.ritsumei.ac.jp, oku@fc.ritsumei.ac.jp, kawagoe@is.ritsumei.ac.jp 373 1.,, itunes Store 1, Web,., 4,300., [1], [2] [3],,, [4], ( ) [3], [5].,,.,,,,

More information

60 90% ICT ICT [7] [8] [9] 2. SNS [5] URL 1 A., B., C., D. Fig. 1 An interaction using Channel-Oriented Interface. SNS SNS SNS SNS [6] 3. Processing S

60 90% ICT ICT [7] [8] [9] 2. SNS [5] URL 1 A., B., C., D. Fig. 1 An interaction using Channel-Oriented Interface. SNS SNS SNS SNS [6] 3. Processing S 1,a) 1 1,b) 1,c) 1,d) Interaction Design for Communication Between Older Adults and Their Families Using Channel-Oriented Interface Takeda Keigo 1,a) Ishiwata Norihiro 1 Nakano Teppei 1,b) Akabane Makoto

More information

HTTP

HTTP 2008 P2P 2009 2 6 5107B024-5 1 5 1.1...................................... 5 1.2...................................... 6 1.3..................................... 7 2 HTTP 8 2.1.............................

More information

サービス仕様書

サービス仕様書 Adhoc NW/PF NW/PF NW/PF NW/PF HDD TV / HGW ( (PC) DB B A B C A IF CAMERA TV CAMERA TV NW VTR VTR NW IEEE1394 16 NW/PF Core Network web server video server cache with etc... cache cache CG Access Lines

More information

C O N T E N T S 1

C O N T E N T S 1 2014 Vol.107 C O N T E N T S 1 Communications 3 Vol.107 2 3 Communications Vol.107 4 5 Communications 7 6 Vol.107 6 7 Communications Vol.107 8 9 Communications Vol.107 10 11 Communications Vol.107 12 13

More information

finalrep.dvi

finalrep.dvi 18 Building a Knowledge Management System for Acquiring Wisdom of Crowds 1095701 2007 3 16 Blog Wiki Web Web Web i Abstract Building a Knowledge Management System for Acquiring Wisdom of Crowds Kazunori

More information

1 AND TFIDF Web DFIWF Wikipedia Web Web 2. 3. 4. AND 5. Wikipedia AND 6. Wikipedia Web 7. 8. 2. Ma [4] Ma URL AND Tian [8] Tian Tian Web Cimiano [3] [

1 AND TFIDF Web DFIWF Wikipedia Web Web 2. 3. 4. AND 5. Wikipedia AND 6. Wikipedia Web 7. 8. 2. Ma [4] Ma URL AND Tian [8] Tian Tian Web Cimiano [3] [ DEIM Forum 2015 B1-5 606 8501 606 8501 E-mail: komurasaki@dl.kuis.kyoto-u.ac.jp, tajima@i.kyoto-u.ac.jp Web Web AND AND Web 1. Twitter Facebook SNS Web Web Web Web [5] Bollegala [2] Web Web 1 Google Microsoft

More information

258 5) GPS 1 GPS 6) GPS DP 7) 8) 10) GPS GPS 2 3 4 5 2. 2.1 3 1) GPS Global Positioning System

258 5) GPS 1 GPS 6) GPS DP 7) 8) 10) GPS GPS 2 3 4 5 2. 2.1 3 1) GPS Global Positioning System Vol. 52 No. 1 257 268 (Jan. 2011) 1 2, 1 1 measurement. In this paper, a dynamic road map making system is proposed. The proposition system uses probe-cars which has an in-vehicle camera and a GPS receiver.

More information

Lyra 2 2 2 X Y X Y ivis Designer Lyra ivisdesigner Lyra ivisdesigner 2 ( 1 ) ( 2 ) ( 3 ) ( 4 ) ( 5 ) (1) (2) (3) (4) (5) Iv Studio [8] 3 (5) (4) (1) (

Lyra 2 2 2 X Y X Y ivis Designer Lyra ivisdesigner Lyra ivisdesigner 2 ( 1 ) ( 2 ) ( 3 ) ( 4 ) ( 5 ) (1) (2) (3) (4) (5) Iv Studio [8] 3 (5) (4) (1) ( 1,a) 2,b) 2,c) 1. Web [1][2][3][4] [5] 1 2 a) ito@iplab.cs.tsukuba.ac.jp b) misue@cs.tsukuba.ac.jp c) jiro@cs.tsukuba.ac.jp [6] Lyra[5] ivisdesigner[6] [7] 2 Lyra ivisdesigner c 2012 Information Processing

More information

_2009MAR.ren

_2009MAR.ren ISSN 0389-5254 2009 No.2 MAR JAPAN AIRCRAFT PILOT ASSOCIATION C O N T E N T S No.313 2009 No.2 MAR é 2009 MAR 2009 MAR 2009 MAR 2009 MAR 2009 MAR 2009 MAR 2009 MAR 2009 MAR 2009 MAR 2009 MAR 2009 MAR

More information

2 3 Pockets Pockest Java [6] API (Backtracking) 2 [7] [8] [3] i == Pockets 2.1 C3PV web [9] Pockets [10]Pockets 1 3 C

2 3 Pockets Pockest Java [6] API (Backtracking) 2 [7] [8] [3] i == Pockets 2.1 C3PV web [9] Pockets [10]Pockets 1 3 C 1,a) 2 3 1 1 API Pockets Pockets Investigating the Model of Automatically Detecting Exploratory Programming Behaviors Erina Makihara 1,a) Hiroshi Igaki 2 Norihiro Yoshida 3 Kenji Fujiwara 1 Hajimu Iida

More information

1 5 1.1..................................... 5 1.2..................................... 5 1.3.................................... 6 2 OSPF 7 2.1 OSPF.

1 5 1.1..................................... 5 1.2..................................... 5 1.3.................................... 6 2 OSPF 7 2.1 OSPF. 2011 2012 1 31 5110B036-6 1 5 1.1..................................... 5 1.2..................................... 5 1.3.................................... 6 2 OSPF 7 2.1 OSPF....................................

More information

1 3 1.1..................................... 3 1.2..................................... 4 1.3.................................... 4 2 DNS 5 2.1 DNS...

1 3 1.1..................................... 3 1.2..................................... 4 1.3.................................... 4 2 DNS 5 2.1 DNS... 2015 User-AgentDNS 2016 2 1 5114F058-7 1 3 1.1..................................... 3 1.2..................................... 4 1.3.................................... 4 2 DNS 5 2.1 DNS......................................

More information

1034 IME Web API Web API 1 IME Fig. 1 Suitable situations for context-aware IME. IME IME IME IME 1 GPS Web API Web API Web API Web )

1034 IME Web API Web API 1 IME Fig. 1 Suitable situations for context-aware IME. IME IME IME IME 1 GPS Web API Web API Web API Web ) Vol. 52 No. 3 1033 1044 (Mar. 2011) IME 1 2 1 1 IME Web PC Android Dynamic Dictionary Generation Method for Context-aware Input Method Editor Yutaka Arakawa, 1 Shinji Suematsu, 2 Shigeaki Tagashira 1 and

More information

untitled

untitled P04 P23 P21 01 CONTENTS P0305 P28 30 P28 1 2 3 4 5 P07 P09 P13 P15 P19 P30 6 P21 7 8 P22 P25 02 03 04 05 P04 P07P28 P29 06 1 2 3 4 1 07 5-1 -2 6 7-1 -2 8 08 1 2 3 4 2 1 09 5-1 -2 6 7-1 -2 8 10 1 2 3 4

More information

21 1 2 1 2

21 1 2 1 2 21 1 2 1 2 1 2 3 ( ) 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 210 0.0 0.0 22 23 25 27 28 29 30 31 32 33 34 35 36 74 pp.4362003.10 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 141224 14 48 10

More information

untitled

untitled 2003 8 ... 3... 4 360... 5... 6... 6... 7 OracleAS Personalization... 8 OracleAS Personalization... 9... 12... 14... 17 Web 1 E-Business E-Business E-Business 360 E-Business Web MySite.com MySite.com E-Business

More information

07九州工業大学.indd

07九州工業大学.indd 1 1 Journal of Multimedia Aided Education Research, 2004, No. 1, 45 58 e-learning e-learning e-learning Video On Demand e-learning e-learning e-learning e-learning 2004 e-learning e-learning OLU SCS 2

More information

Web Basic Web SAS-2 Web SAS-2 i

Web Basic Web SAS-2 Web SAS-2 i 19 Development of moving image delivery system for elementary school 1080337 2008 3 10 Web Basic Web SAS-2 Web SAS-2 i Abstract Development of moving image delivery system for elementary school Ayuko INOUE

More information

untitled

untitled CONTENTS P.3 P.5 P.7 P.13 P.21 P.31 P.33 P.3 P.3 P.3 1 2 3 4 4 1 5 6 2 7 8 2 2 9 10 2 2 1000 800 600 400 200 0 3 4 5 11 12 13 14 15 16 17 18 25 1 8 15 22 29 1 18 25 1 6 17 6 8 11 12 3 13 14 15 16 3 311

More information

PeerPool IP NAT IP UPnP 2) Bonjour 3) PeerPool CPU 4) 2 UPnP Bonjour PeerPool CPU PeerPool PeerPool PPv2 PPv2 2. PeerPool 2.1 PeerPool PeerPool PoolGW

PeerPool IP NAT IP UPnP 2) Bonjour 3) PeerPool CPU 4) 2 UPnP Bonjour PeerPool CPU PeerPool PeerPool PPv2 PPv2 2. PeerPool 2.1 PeerPool PeerPool PoolGW PPv2: 1 2 3 4 PeerPool PeerPool 3 PPv2(PeerPool version 2) PPv2: A Transparent Network Architecture for Naive Inter-Smart Environment Communication Michinobu Shimatani, 4 Yu Enokibori, 2 ismail Arai 3

More information

2002 ( 14 ) WIDE School on Internet

2002 ( 14 ) WIDE School on Internet 2002 1 2002 ( 14 ) WIDE School on Internet 6 22 50 1. 2. 3. 4. 5. 2 Abstract of Master s Thesis Academic Year 2002 A Research on Distance Education Studio using the Internet With distance edication using

More information

経済論集 46‐2(よこ)(P)☆/2.三崎

経済論集 46‐2(よこ)(P)☆/2.三崎 1 2 1869 11 17 5 10 1 3 1914 5 15 5 1872 9 12 3 1870 1 26 14 1881 11 11 12 6 11 1878 5 9 13 1880 6 17 1 15 1882 1 2 3 11 1828 2 26 24 1891 4 22 2 1849 12 1 3 1856 pp 20 21. 1971 p.429. 1973 1, pp.440 444.

More information

2 3 5 5 5 5 6 6 7 7 8 10 10 10 10 11 11 12 12 13 16 16 16 16 17 19 21 21 22 5

2 3 5 5 5 5 6 6 7 7 8 10 10 10 10 11 11 12 12 13 16 16 16 16 17 19 21 21 22 5 1D000425-2 1 2 3 5 5 5 5 6 6 7 7 8 10 10 10 10 11 11 12 12 13 16 16 16 16 17 19 21 21 22 5 3 29 29 29 30 31 31 32 35 35 35 36 41 41 41 46 48 48 48 52 57 4 700 13 1988 4 5 4 5 21 1 1 3 4 5 6 21 10 1888

More information

01.indd

01.indd 2 Vol. 27 1 1 2 2 4 Vol. 27 Contents 3 Vol. 27 2 01 02 03 04 14 24 28 37 38 4 Vol. 27.01 5 Vol. 27.01 6 Vol. 27 7 Vol. 27.01 8 Vol. 27.02 9 Vol. 27.02 10 Vol. 27 11 Vol. 27.02 12 Vol. 27 13 Vol. 27.02

More information

CONTENTS 2012 2 Vol.65 No.2 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~

CONTENTS 2012 2 Vol.65 No.2 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~ 2 2012 CONTENTS 2012 2 Vol.65 No.2 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~ 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

More information

CONTENTS 20103 Vol.63 No.3 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~ ~~~~~~~~

CONTENTS 20103 Vol.63 No.3 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~ ~~~~~~~~ 3 2010 CONTENTS 20103 Vol.63 No.3 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~ ~~~~~~~~ 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

More information

情報科学研究 第19号

情報科学研究 第19号 Research on Organizational Information Security Management and Privacy Protection of Personal Data in the Digital Surveillance Society Tadaaki Nemoto, Yoshihito Hattori, Ken-ichi Sato p. Mark Weiser 4.

More information

QoS [3], [4] [5], [6] [3] i3 (Internet Indirection Infrastructure) i3 i3 packet trigger i3 i3 trigger packet trigger QoS [7] P2P P2P (Peer-to-Peer) Gn

QoS [3], [4] [5], [6] [3] i3 (Internet Indirection Infrastructure) i3 i3 packet trigger i3 i3 trigger packet trigger QoS [7] P2P P2P (Peer-to-Peer) Gn THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS TECHNICAL REPORT OF IEICE. P2P 565 871 1 5 E-mail: {j-konisi,wakamiya,murata}@ist.osaka-u.ac.jp QoS P2P P2P P2P P2P (Peer-to-Peer)

More information

<30323334333697A796BD8AD991E58A77976C2D8CBE8CEA837083938374838C83628367945B956983665B835E2E706466>

<30323334333697A796BD8AD991E58A77976C2D8CBE8CEA837083938374838C83628367945B956983665B835E2E706466> 2Graduate School of Language Education and Information Science (LEIS) 3 4Graduate School of Language Education and Information Science (LEIS) 5 6Graduate School of Language Education and Information Science

More information

P2P P2P Winny 3 P2P 15 20 P2P 1 P2P, i

P2P P2P Winny 3 P2P 15 20 P2P 1 P2P, i 26 P2P Reduction of search packets by sharing peer information in P2P communication 1175073 2015 2 27 P2P P2P Winny 3 P2P 15 20 P2P 1 P2P, i Abstract Reduction of search packets by sharing peer information

More information

Vol. 23 No. 4 Oct. 2006 37 2 Kitchen of the Future 1 Kitchen of the Future 1 1 Kitchen of the Future LCD [7], [8] (Kitchen of the Future ) WWW [7], [3

Vol. 23 No. 4 Oct. 2006 37 2 Kitchen of the Future 1 Kitchen of the Future 1 1 Kitchen of the Future LCD [7], [8] (Kitchen of the Future ) WWW [7], [3 36 Kitchen of the Future: Kitchen of the Future Kitchen of the Future A kitchen is a place of food production, education, and communication. As it is more active place than other parts of a house, there

More information

昭和恐慌期における長野県下農業・農村と産業組合の展開過程

昭和恐慌期における長野県下農業・農村と産業組合の展開過程 No. 3, 96-107 (2002) Electronic Money and Strategy of Telecommunication Industry Oshima Kazuchika Nihon University, Graduate School of Social and Cultural Studies Information technology innovation came

More information

Web 1 q q 2 1 2 Step1) Twitter Step2) (w i, w j ) S(w i, w j ) Step3) q 2 2 2.1 I Twitter MeCab[6] URL http:// @ 2.2 (w i, w j ) S(w i, w j ) I w i w

Web 1 q q 2 1 2 Step1) Twitter Step2) (w i, w j ) S(w i, w j ) Step3) q 2 2 2.1 I Twitter MeCab[6] URL http:// @ 2.2 (w i, w j ) S(w i, w j ) I w i w ARG WI2 No.6, 2015 a b b 565-0871 2-1 a) yoshitake@nanase.comm.eng.osaka-u.ac.jp b) {naoko, babaguchi}@comm.eng.osaka-u.ac.jp 1 Citizen Sensor [1] Twitter 140 Twitter Sakaki [2] [3] Massoudi [4] [5] Copyright

More information

CJL NEWS VOL.18 2005 JANUARY contents

CJL NEWS VOL.18 2005 JANUARY contents CJL NEWS VOL.18 2005 JANUARY contents 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Information http://bbs12.otd.co.jp/1223567/bbs_plain Information Information 16 CENTER FOR JAPANESE LANGUAGE WASEDA UNIVERSITY

More information

Vol. 28 No. 2 Apr. 2011 173 1. 1 Web Twitter/Facebook UI 4 1. 2. 3. 4. Twitter Web Twitter/Facebook e.g., Web Web UI 1 2 SNS 1, 2 2

Vol. 28 No. 2 Apr. 2011 173 1. 1 Web Twitter/Facebook UI 4 1. 2. 3. 4. Twitter Web Twitter/Facebook e.g., Web Web UI 1 2 SNS 1, 2 2 172 SNS Web Web As social web sites such as blog and SNS(Social Network System) became popular, many people have communicated with their friends on the Web. Meanwhile, several problems of social web sites

More information

株式会社フジ・メディア・ホールディングス

株式会社フジ・メディア・ホールディングス 1 FUJI MEDIA HOLDINGS REPORT (Chairman & CEO) Top Message (President & COO) Contents Top Message1 Top Interview2 Fuji Media Holdings Outline6 CSR Vol.513 5014 17 19 20 21 22 FUJI MEDIA HOLDINGS REPORT

More information

27 28 2 15 14350922 1 4 1.1.................................... 4 1.2........................... 5 1.3......................... 6 1.4...................................... 7 2 9 2.1..........................

More information

初めに:

初めに: 2 Copyrightc2008 JETRO. All rights reserved. FAX 03-5572-7044 ...5...6 (1)...7... 11... 11...12...14...15...15...16...17...18 (4)...21 (5)...21 (6)...23 4 Copyrightc2008 JETRO. All rights reserved. 5 Copyrightc2008

More information

3 WOWOW The TV industry strategy with the use of the Internet community And Keitai WOWOW Initiative in the digital era ( ) Kazutaka S

3 WOWOW The TV industry strategy with the use of the Internet community And Keitai WOWOW Initiative in the digital era ( ) Kazutaka S Kochi University of Technology Aca Title ネットコミュニティを用いた 新たなテレビ局ビジネスモデルの構築とケータイ WOWOW 創業によるその実践 Author(s) 志村, 一隆 Citation 高知工科大学, 博士論文. Date of 2005-03 issue URL http://hdl.handle.net/10173/197 Rights Text

More information

SNS & Forecast ,000 2, I n t r o d u c t i o n 2 mif 6 Web MROC Market ing Research Online Communities ,0005,000 2,000 MROC

SNS & Forecast ,000 2, I n t r o d u c t i o n 2 mif 6 Web MROC Market ing Research Online Communities ,0005,000 2,000 MROC 2 0 3 SNS & Forecast 2069 30,000 2,000 20 I n t r o d u c t i o n 2 mif 6 Web MROC Market ing Research Online Communities 500 30,0005,000 2,000 MROC 200300 MROC O u t l i n e 7 P. 4 20 8 mif Market Intelligence

More information

A Study on Traffic Characteristics in Multi-hop Wireless Networks 2010 3 Yoichi Yamasaki ( ) 21 Local Area Network (LAN) LAN LAN LAN (AP, Access Point) LAN AP LAN AP AP AP (MWN, Multi-hop Wireless Network)

More information

T KALS T - 2 -

T KALS T - 2 - 2003 5 8 3 CONTENTS Page. 9 4 5 Page.11-1 - T KALS 4 1 1 3 5 4 80 2 8 10 1 2 T - 2 - KALS 2 6 7 1 TA 1 M 90 M1 ( ) - 3 - - 4 - TAT 5 M 90 10 MBA 3 MBA 11 MBA MBA 34 MBA 4 GSIM Graduate School of International

More information