|
|
- なつき しろみず
- 7 years ago
- Views:
Transcription
1 2012 STUDIES ON RANKING DOCUMENTS WITH QUERY-INTENT SENSITIVITY 11R3129 Shota HATAKENAKA
2 PageRank PageRank PageRank Topic Sensitive PageRank
3 Rocchio
4 1 1.1,,,,, Web, Wiki, blog, twitters,, (query),, (term-matching) (term frequency), (inverse document frequency), TF*IDF,,,,,,,,,,.,,,,,. 3
5 1.2, ,,, Web (theme) (authoritative) (distributive),, Web PageRank [1] ,, Web PageRank HITS,??,,, Topic Sensitive PageRank 10 4 Topic Sensitive PageRank [2] 4
6 1.1: 1.2.3?? Bhattacharyya.[3] 1.2:
7 , Rocchio 5 3 Rocchio [4] PageRank , : 3 (DEIM ), PageRank 2., : Ranking Documents using Similarity-based PageRanks, IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PacRim), PageRank 6
8 3., : PageRank, 4 (DEIM ), 2012., 2, 4., : Ranking Documents with Query and Topic Sensitivity, 7th International Conference on Digital Information Management (ICDIM ), 2012., 2, 5., : Query and Topic Sensitive PageRank for General Documents, 14th IEEE International Symposium on Web Systems Evolution (WSE), 2012., 2, 6.,, :, 11 FIT, 2012.,,, Bhattacharyya.,Bhattacharyya,. 7.,, : Ranking Documents with Query-Topic Sensitivity, International Workshop on Web Information Retrieval Support Systems in IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology(WIRSS), , 7
9 . 8.,, :, 5 (DEIM ), Web 8
10 2 PageRank 2.1,,, Web, Wiki, blog, twitters,, (query),, (term-matching) (term frequency) (inverse document frequency) TF*IDF,, ( ) 9
11 , Web (theme) (authoritative) (distributive),,,,,,,,,,, Web PageRank HITS, Web PageRank d d =< v 1,..., v n > i = 1,..., n w i v i 2 TF*IDF q d i 10
12 cos(d i q) cos(d i q) cos(d i, q) = d i q d i q q d 1, d 2 d n PageRank PageRank Web Web Web PageRank Web PageRank A B PageRank 11
13 P i PageRank P R i P j PageRank P R j P R i = P j B Pi P R j P R j B Pi P i P R j P j PageRank 1 n PageRank H 1 n t t = t+1 H H 2 PageRank H Web Web PageRank 1 Web Web 2 Web Web 2 H H H = (1 d)h + d N N Web d Web Web PageRank Web PageRank Web 12
14 d i d j cos(d i, d j ) = d i d j d i d j 0 PageRank 2 d 0 d 1 d n N ( ) d 1 d 0 r 01 r 01 = 1 N r 01 d 1 d n d 0 d 0 d 1 d n d 1 d 0 rw 01 rw 01 = w 01 ni=1 w 0i w 01 d 0 d 1 d 0 d PageRank 2 1/N N M M = (1 d)m + d d 0.15 M PageRank 13
15 A B B C A C ( ) PageRank PageRank r 1 r 2 10 Sim(r 1, r 2 ) = (A B) k A B r 1 r 2 k PageRank PageRank PageRank 2 3 PageRank
16 (PageRank) Web PageRank 2.5 Web 15
17 2.1: PageRank Top10 PR
18 2.2: TOP : k Sim (PageRank, )
19 3 PageRank, 2, 3.1,,,,, Web, Wiki, blog, twitters,,, (query),, (term-matching) (term frequency), (inverse document frequency), TF*IDF,,,,,,,,,, ( ),, 18
20 ,,, (Topic Driftting), Web PageRank HITS,,,, Web PageRank
21 2 3.3 d d =< v 1,..., v n > i = 1,..., n w i v i 2 TF*IDF q d i cos(d i q) cos(d i q) cos(d i, q) = d i q d i q q d 1, d 2 d n 3.4 PageRank PageRank PageRank PageRank A B PageRank 20
22 d i PageRank P R i d j PageRank P R j P R i = d j B di P R j P R j B di d i P R j d j PageRank 1 n PageRank H 1 n t t = t+1 H H 2 PageRank H Web PageRank H H H = (1 d)h + d N N Web d Topic Sensitive PageRank Topic Sensitive PageRank [7] Web ODP ODP PageRank 2 PageRank ODP c j PageRank d PageRank rank jd q PageRank c j q P (c j q ) P (c j q ) = P (c j) P (q c j ) P (q ) P (c j ) P (q c j ) 21
23 s qd s qd = n P (c j q ) rank jd j ODP [?] PageRank 2 d i t j T ji T ji = d i t j d i t j t j t j s j t j s j d i d j w ij w ij = d i d j d i d j 0 22
24 PageRank 2 d 0 d 1 d n N ( ) d 1 d 0 r 01 r 01 = 1 N r 01 d 1 d n d 0 d 0 d 1 d n d 1 d 0 r 01 r 01 = w 01 ni=1 w 0i d 0 d PageRank PageRank 2 1/N N t j M M = (1 d)m + d d PageRank 0.15 M PageRank s j PageRank PageRank s j d i PageRank P R ji P R ji = s j nk=1 s k P R ji s j d i PageRank P R ji 23
25 3.5.3 t j t j q m s j Q mj s j w j Q jm = q m w j q m w j Q jm q m d i n v mi = T ji P R ji Q jm j=1 q m d i v mi PageRank [?]
26 8 ( ) PageRank Topic Sensitive PageRank Topic Sensitive PageRank PageRank 2 ODP 8 PageRank : TSPR MYPR TSPR MYPR ,3,5 3,4, Topic Sensitive PageRank
27 10 4 Topic Sensitive PageRank 4 2 Topic Sensitive PageRank Topic Sensitive PageRank Topic Sensitive PageRank Topic Sensitive PageRank Topic Sensitive PageRank Topic Sensitive PageRank Topic Sensitive PageRank Topic Sensitive PageRank
28 3.2: (TSPR) 4.56E E E-08 0 (MYPR) (TSPR) E E-08 (MYPR) Topic Sensitive PageRank 1 Topic Sensitive PageRank ODP Web
29 3.3: Topic Sensitive PageRank PageRank ( ) : PageRank * ( ) : Topic Sensitive PageRank PageRank ( )
30 3.6: PageRank * ( ) : TD
31 3.8: TD
32 4 4.1 Blog twitter 31
33 4.2 ( ) ( ) Bhattacharyya [6] Bhattacharyya Bhattacharyya 1 L = m u=1 P u Q u p q m u=1 P u = m u=1 Q u = 1 blog twitter Bhattacharyya Bhattacharyya 2 d q = N n=1 tf i Bha i N q d d q tf i d i Bha q i q i Bhattacharyya N d q q q Bhattacharyya q Bhattacharyya 0 Bhattacharyya 32
34 q Bhattacharyya q Bhattacharyya Bhattacharyya Bhattacharyya q q Bhattacharyya Bhattacharyya 0 Bhattacharyya Bhattacharyya q q d , ,000 6, Bhattacharyya 4.1 Bhattacharyya 4.2 Bhattacharyya ID
35 4.1: Bhattacharyya Bhattacharyya ID : Bhattacharyya ( ) Bhattacharyya ID Bhattacharyya 4.3 Bhattacharyya Bhattacharyya Bhattacharyya 34
36 4.3: Bhattacharyya ( ) Bhattacharyya ID Bhattacharyya Bhattacharyya Bhattacharyya 4.6 Bhattacharyya Bhattacharyya 35
37 4.4: 5 ID: : : : : : 28 36
38 5 5.1 Blog twitter,,,, ( ) ( ) 37
39 3 Rocchio 5.2 Rocchio d d =< v 1,..., v n > i = 1,..., n w i v i 2 TF*IDF q d i cos(d i q) cos(d i q) 38
40 cos(d i, q) = d i q d i q q d 1, d 2 d n Rocchio [15] q D r D n TF*IDF q q q = q + D R d i D R d i D N d j D N d j D R D N Bhattacharyya [?] Bhattacharyya Bha = m u=1 P u Q u (0 Bha 1) p q ( m u=1 P u = m u=1 Q u = 1) blog twitter 39
41 Bhattacharyya Bhattacharyya q q i BC iq 1 BC iq = Bha iq log( ) CO iq Bha iq q i Bhattacharyya CO iq q i 2 Bha CO Bha Bha Bha CO iq CO iq = c a + b c a i b q c i q q q BC dr N BC iq,n+1 = BC iq,n (1 + w i,d + N + w i,d N ) BC i,n n q i N N + n w i,d + w i,d i i n+1 j dr j,n+1 Nn=1 tf i,j BC iq,n+1 dr j,n+1 = N tf i,j j i N j j CO j CO j = Nn=1 tf i,j CO iq N 40
42 q i BC iq 2. N BC i,n , ,000 6, Rocchio 3 =1.0 =0.8 =
43 Rocchio 3 top10 R) Rocchio Rocchio Rocchio 5 ( ), 1, 4 5 Rocchio
44 5.1: Rocchio FB[0] FB[1] FB[2] FB[3] R) R) R) R) ( ) R) ( ) ( ) ( )
45 5.2: Rocchio SMAP SMAP , 44
46 5.3: ??NY, , ASEM ASEM
47 5.4: Rocchio ?? PT ?? , 18 PT
48 5.5: ?? , NHK
49 5.6: ?? ,
50 6,. Web,,,,,,,,, 49
51 50
52 [1] Hatakenaka, S. and Miura, T.: Ranking Documents using Similarity-based Page- Ranks, IEEE Pacific Rim Conference on Communications, Computers and Signal Processing(PacRim), [2] Hatakenaka, S. and Miura, T.: Query and Topic Sensitive PageRank for General Documents, 14th IEEE International Symposium on Web Systems Evolution(WSE), [3] :, 11 FIT, [4] :, 5 (DEIM), [5] S. Brin and L. Page The anatomy of a large scale hypertextual Web search engine. ComputerNetworks and ISDN Systems, 30, , [6] Oren. Kurland and Lillian Lee PageRank without hyperlinks: Structural reranking using links induced by language models. Proceedings of the 28th annual international ACM SIGIR, [7] T. H. Haveliwala Topic-sensitive PageRank. Proceedings of the 11th international conference on World Wide Web, [8] Amy N. Langville, Carl D. Meyer,,, Google PageRank 2009 [9] J. Kleinberg Bursty and hierarchical structure in streams. Proc. 8th SIGKDD,2002, [10] Masaya Murata, Hiroyuki Toda, Yumiko Matsuura and Ryoji Kataoka, A Query Expansion Method Using Access Concentration Sites in Search Result Proceedings of the DataBase and Web symposium,
53 [11] Hang Cui, Ji-RongWen, Jian-Yun Nie andwei-yingma, Probabilistic Query Expansion Using Quer Logs Proceedingsof the 11th international conference on World Wide Web 2002, [12] Georges E. Dupret and Benjamin Piwowarski. A user browsing model to predict search engine click data from past observations ACM SIGIR , [13] KMamoru Komachi, Shimpei Makimoto, Kei Uchiumi, and Manabu Sassano. Learning semanticcategories from clickthrough logs ACLIJCNLP , [14] Qingshan LIU and Dimitris N METAXAS Unifying Subspace and Distance Metric Learning with Bhattacharyya Coefficient for Image Classification Lecture Notes in Computer Science 2009 Volume 5416/ , [15] Rocchio, J.J Relevance fssdback in information retrieval. The SMART Retrieval Systems, pp , Prentice-Hall,
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,, 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独立行政法人情報通信研究機構 Development of the Information Analysis System WISDOM KIDAWARA Yutaka NICT Knowledge Clustered Group researched and developed the infor
独立行政法人情報通信研究機構 KIDAWARA Yutaka NICT Knowledge Clustered Group researched and developed the information analysis system WISDOM as a research result of the second medium-term plan. WISDOM has functions that
More informationuntitled
IT E- IT http://www.ipa.go.jp/security/ CERT/CC http://www.cert.org/stats/#alerts IPA IPA 2004 52,151 IT 2003 12 Yahoo 451 40 2002 4 18 IT 1/14 2.1 DoS(Denial of Access) IDS(Intrusion Detection System)
More informationTrial for Value Quantification from Exceptional Utterances 37-066593 1 5 1.1.................................. 5 1.2................................ 8 2 9 2.1.............................. 9 2.1.1.........................
More information2 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 informationTF-IDF TDF-IDF TDF-IDF Extracting Impression of Sightseeing Spots from Blogs for Supporting Selection of Spots to Visit in Travel Sat
1 1 2 1. TF-IDF TDF-IDF TDF-IDF. 3 18 6 Extracting Impression of Sightseeing Spots from Blogs for Supporting Selection of Spots to Visit in Travel Satoshi Date, 1 Teruaki Kitasuka, 1 Tsuyoshi Itokawa 2
More informationVol.55 No (Jan. 2014) saccess 6 saccess 7 saccess 2. [3] p.33 * B (A) (B) (C) (D) (E) (F) *1 [3], [4] Web PDF a m
Vol.55 No.1 2 15 (Jan. 2014) 1,a) 2,3,b) 4,3,c) 3,d) 2013 3 18, 2013 10 9 saccess 1 1 saccess saccess Design and Implementation of an Online Tool for Database Education Hiroyuki Nagataki 1,a) Yoshiaki
More informationVol.6 No (Aug. 2013) Twitter 1,a) , Twitter Twitter Study of Twitter s Follow Mechanism Based on Network
Twitter 1,a) 1 2 3 2012 11 3 2013 1 25, 2013 3 27 Twitter Twitter Study of Twitter s Follow Mechanism Based on Network Analysis Akihiro Koide 1,a) Kazumi Saito 1 Kazuhiro Kazama 2 Fujio Toriumi 3 Received:
More information2. Twitter Twitter 2.1 Twitter Twitter( ) Twitter Twitter ( 1 ) RT ReTweet RT ReTweet RT ( 2 ) URL Twitter Twitter 140 URL URL URL 140 URL URL
1. Twitter 1 2 3 3 3 Twitter Twitter ( ) Twitter (trendspotter) Twitter 5277 24 trendspotter TRENDSPOTTER DETECTION SYSTEM FOR TWITTER Wataru Shirakihara, 1 Tetsuya Oishi, 2 Ryuzo Hasegawa, 3 Hiroshi Hujita
More informationIPSJ SIG Technical Report Vol.2014-DBS-159 No.6 Vol.2014-IFAT-115 No /8/1 1,a) 1 1 1,, 1. ([1]) ([2], [3]) A B 1 ([4]) 1 Graduate School of Info
1,a) 1 1 1,, 1. ([1]) ([2], [3]) A B 1 ([4]) 1 Graduate School of Information Science and Technology, Osaka University a) kawasumi.ryo@ist.osaka-u.ac.jp 1 1 Bucket R*-tree[5] [4] 2 3 4 5 6 2. 2.1 2.2 2.3
More information[1] [3]. SQL SELECT GENERATE< media >< T F E > GENERATE. < media > HTML PDF < T F E > Target Form Expression ( ), 3.. (,). : Name, Tel name tel
DEIM Forum 2011 C7-5 SuperSQL 223 8522 3 14 1 E-mail: tomonari@db.ics.keio.ac.jp, toyama@ics.keio.ac.jp SuperSQL, SQL SELECT GENERATE SQL., SuperSQL HTML,.,. SuperSQL, HTML, Equivalent Transformation on
More information22 Google Trends Estimation of Stock Dealing Timing using Google Trends
22 Google Trends Estimation of Stock Dealing Timing using Google Trends 1135064 3 1 Google Trends Google Trends Google Google Google Trends Google Trends 2006 Google Google Trend i Abstract Estimation
More informationŁ\1.pdf
8 Page1 : 7 8 8 8 8 8 8 44,245 696 11,337 32,212 49,313 370 14,768 34,175 3,352 152 1,268 1,932 28,721 118 3,699 24,904 35,152 98 5,349 29,705 2,994 114 1,069 1,811 64.9% 17.0% 32.6% 77.3% 71.3% 26.5%
More information1 Fogg Fogg Behavior Model [1] information cascade [2] TPO [3] Fig. 2 Target area of this paper. 1 Fig. 1 Fogg b
1,a) 1 1 1 2014 9 20, 2015 1 5 TPO Extracting Purpose-for-Action to Enhance Local Information Service Noriko Yokoyama 1,a) Kaname Funakoshi 1 Hiroyuki Toda 1 Yoshimasa Koike 1 Received: September 20, 2014,
More informationIPSJ SIG Technical Report Vol.2013-HCI-152 No /3/13 1,a) 1,b) 2,c) / GPS Bluetooth(BT) WiFi BT WiFi 1. Bluetooth WiFi 1 / 1 2 a)
1,a) 1,b) 2,c) / GPS Bluetooth(BT) WiFi BT WiFi 1. Bluetooth WiFi 1 / 1 2 a) rtokuami@kwansei.ac.jp b) kono@kwansei.ac.jp c) nakamura@dl.kuis.kyoto-u.ac.jp / 2. Apple iphoto Google Picasa GPS GPS GPS [1][2]
More information2 2.1 SNS web Facebook Google+ SNS web SNS web HITS ANT(Auction Network Trust) web [4] SNS WEB PageRank HITS HITS web authorities, hubs Pagerank web S
SNS Evaluation and Development reputation network for SNS user evaluation using realistic distance 1 3 1,2 Takanobu Otsuka 1 Takuya Yoshimura 3 Takayuki Ito 1,2 1 1 Center for Green Computing, Nagoya Institute
More informationDEIM Forum 2012 E Web Extracting Modification of Objec
DEIM Forum 2012 E4-2 670 0092 1 1 12 E-mail: nd11g028@stshse.u-hyogo.ac.jp, {dkitayama,sumiya}@shse.u-hyogo.ac.jp Web Extracting Modification of Objects for Supporting Map Browsing Junki MATSUO, Daisuke
More information1 Broder Navigational URL URL Informational Web Transactional Web Web Web 2 Broder [16] SearchLife Broder [16] Daniel [17] Broder
DEIM Forum 2010 B9-4 432 8011 3 5 1 432 8011 3 5 1 E-mail: gs08062@s.inf.shizuoka.ac.jp, {yokoyama,fukuta,ishikawa}@inf.shizuoka.ac.jp Web Web. Evaluation of a Multiple Viewpoints Clustering Search Engine
More information[2][3][4][5] 4 ( 1 ) ( 2 ) ( 3 ) ( 4 ) 2. Shiratori [2] Shiratori [3] [4] GP [5] [6] [7] [8][9] Kinect Choi [10] 3. 1 c 2016 Information Processing So
1,a) 2 2 1 2,b) 3,c) A choreographic authoring system reflecting a user s preference Ryo Kakitsuka 1,a) Kosetsu Tsukuda 2 Satoru Fukayama 2 Naoya Iwamoto 1 Masataka Goto 2,b) Shigeo Morishima 3,c) Abstract:
More informationmain.dvi
DEIM Forum 2018 J7-3 305-8573 1-1-1 305-8573 1-1-1 305-8573 1-1-1 () 151-0053 1-3-15 6F URL SVM Identifying Know-How Sites basedonatopicmodelandclassifierlearning Jiaqi LI,ChenZHAO, Youchao LIN, Ding YI,ShutoKAWABATA,
More information([ ]!) name1 name2 : [Name]! name10 2. 3 SuperSQL,,,,,,, (@) < >@{ < > } =,,., 200,., TFE,, 1 2.,, 4, 3.,,,, Web EGG [5] SSVisual [6], Java SSedit( ss
DEIM Forum 2016 H6-3 SuperSQL CSS 223 8522 3-14-1 E-mail: {ryosuke,goto}@db.ics.keio.ac.jp, toyama@ics.keio.ac.jp SuperSQL, SQL. SuperSQL HTML, PHP,,,, SuperSQL Web, CSS 1. SQL, SuperSQL, CSS SuperSQL,
More information: ( 1) () 1. ( 1) 2. ( 1) 3. ( 2)
Acquiring Organized Information from News by Incremental Theme Refinements 1 1 1 Yutaro Taniguchi 1 Tetsunori Kobayashi 1 Yoshihiko Hayashi 1 1 1 School of Science and Engineering, Waseda University Abstract:
More informationMicrosoft Word - toyoshima-deim2011.doc
DEIM Forum 2011 E9-4 252-0882 5322 252-0882 5322 E-mail: t09651yt, sashiori, kiyoki @sfc.keio.ac.jp CBIR A Meaning Recognition System for Sign-Logo by Color-Shape-Based Similarity Computations for Images
More informationmain.dvi
305 8550 1 2 CREST fujii@slis.tsukuba.ac.jp 1 7% 2 2 3 PRIME Multi-lingual Information Retrieval 2 2.1 Cross-Language Information Retrieval CLIR 1990 CD-ROM a. b. c. d. b CLIR b 70% CLIR CLIR 2.2 (b) 2
More informationIT,, i
22 Retrieval support system using bookmarks that are shared in an organization 1110250 2011 3 17 IT,, i Abstract Retrieval support system using bookmarks that are shared in an organization Yoshihiko Komaki
More informationIPSJ SIG Technical Report Vol.2013-ICS-172 No /11/12 1,a), 1,b) Anomaly Detection 1. 1 Nagoya Institute of Technology 1 Presently with Nagoya In
1,a), 1,b) Anomaly Detection 1. 1 Nagoya Institute of Technology 1 Presently with Nagoya Institute of Technology a) otsuka.takanobu@nitech.ac.jp b) ito.takayuki@nitech.ac.jp Anomaly Detection 2 3 4 5 6
More information3 2 2 (1) (2) (3) (4) 4 4 AdaBoost 2. [11] Onishi&Yoda [8] Iwashita&Stoica [5] 4 [3] 3. 3 (1) (2) (3)
(MIRU2012) 2012 8 820-8502 680-4 E-mail: {d kouno,shimada,endo}@pluto.ai.kyutech.ac.jp (1) (2) (3) (4) 4 AdaBoost 1. Kanade [6] CLAFIC [12] EigenFace [10] 1 1 2 1 [7] 3 2 2 (1) (2) (3) (4) 4 4 AdaBoost
More informationWISS 2018 [2 4] [5,6] Query-by-Dancing Query-by- Dancing Cao [1] OpenPose 2 Ghias [7] Query by humming Chen [8] Query by rhythm Jang [9] Query-by-tapp
Query-by-Dancing: WISS 2018. Query-by-Dancing Query-by-Dancing 1 OpenPose [1] Copyright is held by the author(s). DJ DJ DJ WISS 2018 [2 4] [5,6] Query-by-Dancing Query-by- Dancing Cao [1] OpenPose 2 Ghias
More informationDEIM Forum 2017 E Netflix (Video on Demand) IP 4K [1] Video on D
DEIM Forum 2017 E1-1 700-8530 3-1-1 E-mail: inoue-y@mis.cs.okayama-u.ac.jp, gotoh@cs.okayama-u.ac.jp 1. Netflix (Video on Demand) IP 4K [1] Video on Demand ( VoD) () 2. 2. 1 VoD VoD 2. 2 AbemaTV VoD VoD
More information20mm 63.92% ConstantZoom U 5
29 30 2 13 16350926 20mm 63.92% ConstantZoom U 5 1 3 1.1...................................... 3 1.2................................. 4 2 8 2.1............... 8 2.2............................ 8 2.3..
More information48_14_11.dvi
Vol. 48 No. SIG 14(TOD 35) Sep. 2007 BLOGRANGER Web Web Web 2191 Web 2 BLOGRANGER: Implementation of Goal-oriented Blog Search Engine Hiroyuki Toda, Ko Fujimura, Takafumi Inoue, Nobuaki Hiroshima, Masayuki
More information再発見を試みるユーザ 入力閲覧ページ出力同位ページ 以前に閲覧したページ 同位ページの推定 2. 1 [4], [13] Dubroy [4] [13] 4 [1], [2], [8], [10], [12] Nshmoto [8] Capra [2] Exact Path Su
DEIM Forum 2015 B2-5 606 8501 E-mal: {takeda,ohshma,tanaka}@dl.kus.kyoto-u.ac.jp Web 1. Web Web 44% [9] 33% [11] Web 2 3 4 5 6 再発見を試みるユーザ 入力閲覧ページ出力同位ページ 以前に閲覧したページ 同位ページの推定 2. 1 [4], [13] Dubroy [4] [13]
More informationFIT2014( 第 13 回情報科学技術フォーラム ) RD-002 Web SNS Yuanyuan Wang Gouki Yasui Yuji Hosokawa Yukiko Kawai Toyokazu Akiyama Kazutoshi Sumiya 1. Twitter 1 Facebo
RD-002 Web SNS Yuanyuan Wang Gouki Yasui Yuji Hosokawa Yukiko Kawai Toyokazu Akiyama Kazutoshi Sumiya 1. Twitter 1 Facebook 2 SNS SNS SNS Twitter SNS [1] SNS [2] Twitter Web Web Web Web SNS Web Web 2 Web
More information2
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 information27 AR
27 AR 28 2 19 12111002 AR AR 1 3 1.1....................... 3 1.1.1...................... 3 1.1.2.................. 4 1.2............................ 4 1.2.1 AR......................... 5 1.2.2......................
More informationWeb情報検索の新技術と動向
Web ダイナミクスを利用した 情報探索支援 NTT 未来ねっと研究所 風間一洋 発表概要 分散情報探索インフラストラクチャ リンク解析によるランキングの改善 リンクによる関連ページの発見 Web 空間からの人間関係の発見 Blogのトラックバックネットワーク解析 企業におけるネットワーク科学研究 分散情報探索インフラストラクチャ Ingrid (INformaton GRID) [Paul et
More information( 1) 3. Hilliges 1 Fig. 1 Overview image of the system 3) PhotoTOC 5) 1993 DigitalDesk 7) DigitalDesk Koike 2) Microsoft J.Kim 4). 2 c 2010
1 2 2 Automatic Tagging System through Discussing Photos Kazuma Mishimagi, 1 Masashi Toda 2 and Toshio Kawashima 2 Many media forms can be stored easily at present. Photographs, for example, can be easily
More information1. [5] Wikipedia 4. ( ) Wikipedia 5. 3 ( ) ( ) ( ) Wikipedia ( ) ( ) 2.2 Global Database of Events, Language and Tone (GDELT) Global Datab
GDELT Multifacet comparative analysis of newspaper articles from different conutries - Analysis based on Global Database of Events, Language and Tone (GDELT) - 1 2 Masaharu Yoshioka 1 Noriko Kando 2 1
More information3807 (3)(2) ,267 1 Fig. 1 Advertisement to the author of a blog. 3 (1) (2) (3) (2) (1) TV 2-0 Adsense (2) Web ) 6) 3
Vol. 52 No. 12 3806 3816 (Dec. 2011) 1 1 Discovering Latent Solutions from Expressions of Dissatisfaction in Blogs Toshiyuki Sakai 1 and Ko Fujimura 1 This paper aims to find the techniques or goods that
More information( : A8TB2163)
2011 2012 3 26 ( : A8TB2163) ( A B [1] A B A B B i 1 1 2 3 2.1... 3 2.1.1... 3 2.1.2... 4 2.2... 5 3 7 3.1... 7 3.2... 7 3.3 A B... 7 4 8 4.1... 8 4.1.1... 9 4.1.2... 9 4.1.3... 9 4.1.4... 10 4.2 A B...
More informationAHPを用いた大相撲の新しい番付編成
5304050 2008/2/15 1 2008/2/15 2 42 2008/2/15 3 2008/2/15 4 195 2008/2/15 5 2008/2/15 6 i j ij >1 ij ij1/>1 i j i 1 ji 1/ j ij 2008/2/15 7 1 =2.01/=0.5 =1.51/=0.67 2008/2/15 8 1 2008/2/15 9 () u ) i i i
More information27 28 2 15 14350922 1 4 1.1.................................... 4 1.2........................... 5 1.3......................... 6 1.4...................................... 7 2 9 2.1..........................
More informationmain.dvi
1 1 1 2 3 LDA Estimating and Analyzing a Domain Topic Model of Entries Kensaku Makita 1 Hiroko Suzuki 1 Daichi Koike 1 Takehito Utsuro 2 Yasuhide Kawada 3 Abstract: In order to address the issue of quickly
More informationMicrosoft Word - deim2011_new-ichinose-20110325.doc
DEIM Forum 2011 B7-4 252-0882 5322 E-mail: {t08099ai, kurabaya, kiyoki}@sfc.keio.ac.jp A Music Search Database System with a Selector for Impressive-Sections of Continuous Data Aya ICHINOSE Shuichi KURABAYASHI
More information. Yahoo! 1!goo 2 QA..... QA Web Web 2 3 4 5 6 7 8 2. [1]Web Web Yin [2] Web Web Web. [3] Web Wikipedia 1 2
DEIM Forum 211 F6-3 Web 35 855 1 2 35 855 1 2 11 843 2 1 2 E-mail: s913153@klis.tsukuba.ac.jp, {yohei,satoh}@slis.tsukuba.ac.jp, kando@nii.ac.jp QA Web Web Web QA Diversified-query Generating System Using
More informationVol.20, No.1, 2018 Castillo [10] Yang [11] Sina Weibo 3 Castillo [10] Twitter 4 Twitter [12] Twitter ) 2 Twitter [13] 3. Twitter Twitter 3
Vol.20 No.1, 2018 1 2 3 4 Construction of Information-credibility Verification-behavior Facilitation System for Preventing False Rumors Spreading Daisuke Kakimoto 1, Mai Miyabe 2, Eiji Aramaki 3 and Takashi
More informationIPSJ SIG Technical Report Vol.2010-CVIM-170 No /1/ Visual Recognition of Wire Harnesses for Automated Wiring Masaki Yoneda, 1 Ta
1 1 1 1 2 1. Visual Recognition of Wire Harnesses for Automated Wiring Masaki Yoneda, 1 Takayuki Okatani 1 and Koichiro Deguchi 1 This paper presents a method for recognizing the pose of a wire harness
More informationDEIM Forum 2010 A Web Abstract Classification Method for Revie
DEIM Forum 2010 A2-2 305 8550 1 2 305 8550 1 2 E-mail: s0813158@u.tsukuba.ac.jp, satoh@slis.tsukuba.ac.jp Web Abstract Classification Method for Reviews using Degree of Mentioning each Viewpoint Tomoya
More information2reN-A14.dvi
340 30 1 SP2-N 2015 Onomatoperori : Ranking Cooking Recipes by using Onomatopoeias which Express their Tastes and Textures Chiemi Watanabe Satoshi Nakamura Graduate School of Systems and Information Engineering,
More informationHonda 3) Fujii 4) 5) Agrawala 6) Osaragi 7) Grabler 8) Web Web c 2010 Information Processing Society of Japan
1 1 1 1 2 Geographical Feature Extraction for Retrieval of Modified Maps Junki Matsuo, 1 Daisuke Kitayama, 1 Ryong Lee 1 and Kazutoshi Sumiya 1 Digital maps available on the Web are widely used for obtaining
More informationWII-D 2017 (1) (2) (1) (2) [Tanaka 07] [ 04] [ 10] [ 13, 13], [ 08] [ 13] (1) (2) 2 2 e.g., Wikipedia [ 14] Wikipedia [ 14] Linked Open
Web 2017 Original Paper Supporting Exploratory Information Access Based on Comic Content Information 1 Ryo Yamashita Byeongseon Park Mitsunori Matsushita Nomura Research Institute, LTD. r-yamashita@nri.co.jp
More information2 JAWS web web Share = authorities ReShare = (hubs SNS i j i authorities j i i hubs 1 User i 情報が j によってシェアされる (authorities) j の情報をシェアする (hu
JAWS2012 JAWS2012 SNS Evaluation and Development reputation network for SNS user evaluation using realistic distance 1 Takanobu Otsuka Takuya Yoshimura Takayuki Ito Center for Green Computing, Department
More informationIPSJ SIG Technical Report Vol.2009-DPS-141 No.20 Vol.2009-GN-73 No.20 Vol.2009-EIP-46 No /11/27 1. MIERUKEN 1 2 MIERUKEN MIERUKEN MIERUKEN: Spe
1. MIERUKEN 1 2 MIERUKEN MIERUKEN MIERUKEN: Speech Visualization System Based on Augmented Reality Yuichiro Nagano 1 and Takashi Yoshino 2 As the spread of the Augmented Reality(AR) technology and service,
More information卒論タイトル
1 Web, [ ] [ ] [ ] [ ] [ ],.,,.,,., Web, Web 3. Web., 3,, IDF. 2 1 4 1.1... 4 1.2... 4 1.3... 4 1.4... 5 1.5... 5 2 6 2.1 Web UI[2]... 6 2.1.1... 6 2.1.2... 7 2.2 [3]... 7 2.2.1... 7 2.2.2... 7 2.3 Web
More informationIPSJ SIG Technical Report Vol.2011-EC-19 No /3/ ,.,., Peg-Scope Viewer,,.,,,,. Utilization of Watching Logs for Support of Multi-
1 3 5 4 1 2 1,.,., Peg-Scope Viewer,,.,,,,. Utilization of Watching Logs for Support of Multi-View Video Contents Kosuke Niwa, 1 Shogo Tokai, 3 Tetsuya Kawamoto, 5 Toshiaki Fujii, 4 Marutani Takafumi,
More information1: 2: 3: 4: 2. 1 Exploratory Search [4] Exploratory Search 2. 1 [7] [8] [9] [10] Exploratory Search
DEIM Forum 2013 D2-1 112 8610 2-1-1 E-mail: {aco,itot}@itolab.is.ocha.ac.jp, chiemi@is.ocha.ac.jp Exploratory Search A product Search System for women adjusting amount of browsed items Abstract Eriko KOIKE,
More information1 4 4 [3] SNS 5 SNS , ,000 [2] c 2013 Information Processing Society of Japan
SNS 1,a) 2 3 3 2012 3 30, 2012 10 10 SNS SNS Development of Firefighting Knowledge Succession Support SNS in Tokyo Fire Department Koutarou Ohno 1,a) Yuki Ogawa 2 Hirohiko Suwa 3 Toshizumi Ohta 3 Received:
More information1 IDC Wo rldwide Business Analytics Technology and Services 2013-2017 Forecast 2 24 http://www.soumu.go.jp/johotsusintokei/whitepaper/ja/h24/pdf/n2010000.pdf 3 Manyika, J., Chui, M., Brown, B., Bughin,
More information2015 9
JAIST Reposi https://dspace.j Title ウェブページからのサイト情報 作成者情報の抽出 Author(s) 堀, 達也 Citation Issue Date 2015-09 Type Thesis or Dissertation Text version author URL http://hdl.handle.net/10119/12932 Rights Description
More information教師情報を必要としないWebページ群のコンテンツ自動抽出ツールの提案
DEIM Forum 2009 A8-4 Web 305-8573 1-1-1 305-8573 1-1-1 E-mail: m.yoshida@mibel.cs.tsukuba.ac.jp, myama@cs.tsukuba.ac.jp CMS Web Web Web Web Web Web Web Web,,, HTML, Web, Web, Primary Content Extraction
More informationDEIM Forum 2012 E8-4 Wikipedia y
DEIM Forum 2012 E8-4 Wikipedia 658-8501 8-9-1 464-8601 658-8501 8-9-1 658-8501 8-9-1 E-mail: life.of.151a@gmail.co.jp, suzuki@db.itc.nagoya-u.ac.jp, ykonishi@center.konan-u.ac.jp, nadamoto@konan-u.ac.jp
More information1 Web,.,, Web..,, Web.,,,.,,,., CGI.,, Web, Web.,,. PC,,.
Web 1 Web,.,, Web..,, Web.,,,.,,,., CGI.,, Web, Web.,,. PC,,. 2 1 6 1.1............................................... 6 1.2.............................................. 6 1.3...............................................
More information3 Venue Venue Venue Venue Venue Venue SNS [2] Venue Venue [3] Venue Venue Venue [4] / Venue [5] Venue Venue Foursquare Venue Foursquare
DEIM Forum 2016 H5-5 432 8011 3 5 1 870 0152 1666 432 8002 1933 1 2F 432 8011 3 5 1 E-mail: gs14043@s.inf.shizuoka.ac.jp, m-hirota@oita-ct.ac.jp, hiro@c-point.co.jp, yokoyama@inf.shizuoka.ac.jp (Venue)
More information& Vol.5 No (Oct. 2015) TV 1,2,a) , Augmented TV TV AR Augmented Reality 3DCG TV Estimation of TV Screen Position and Ro
TV 1,2,a) 1 2 2015 1 26, 2015 5 21 Augmented TV TV AR Augmented Reality 3DCG TV Estimation of TV Screen Position and Rotation Using Mobile Device Hiroyuki Kawakita 1,2,a) Toshio Nakagawa 1 Makoto Sato
More information5 2 3 4 5 2. Berchtold 1) ActiServ 1 ALKAN Fig. 1 ALKAN overview 10 3 3 Herren 2) 20 HASC Challenge 3) HASC Challenge 540 6700 2.1 ALKAN 4),5) ALKAN i
情 報 処 理 学 会 インタラクション 2012 IPSJ Interaction 2012 2012-Interacti 2012/3/16 3 Hierarchical Annotation Management Method for Activity Information Gathering System Yuichi HATTORI, Syota TANAKA and Sozo INOUE
More information1.0, λ. Holt-Winters t + h,ỹ t ỹ t+h t = ỹ t + hf t.,,.,,,., Hassan [5],,,.,,,,,,Hassan EM,, [6] [8].,,,,Stenger [9]. Baum-Welch, Baum-Welch (Incremen
DEIM Forum 2009 E8-4 HMM 184 8584 3-7-2 E-mail: kei.wakabayashi.bq@gs-eng.hosei.ac.jp, miurat@k.hosei.ac.jp, (HMM)., EM HMM, Baum-Welch,,,, Forecasting Time-Series on Data Stream using Incremental Hidden
More information2009 2
2009 2 350603022 ( ) Wii iii 1 1 2 7 2.1............................ 7 2.1.1...................... 7 2.1.2........... 8 2.1.3......................... 10 2.2....................... 11 2.2.1.................
More informationmain.dvi
DEIM Forum 2012 E2-4 1 2 2 2 3 4 5 6 7 1 305-8573 1-1-1 2 305-8573 1-1-1 3 305-8573 1-1-1 4 ( ) 141-0031 8-3-6 5 060-0808 8 5 6 101-8430 2-1-2 7 135-0064. 2-3-26 113-0033 7-3-1 305-8550 1-2 Analyzing Correlation
More informationIPSJ SIG Technical Report Vol.2014-MBL-70 No.49 Vol.2014-UBI-41 No /3/15 2,a) 2,b) 2,c) 2,d),e) WiFi WiFi WiFi 1. SNS GPS Twitter Facebook Twit
2,a) 2,b) 2,c) 2,d),e) WiFi WiFi WiFi 1. SNS GPS Twitter Facebook Twitter Ustream 1 Graduate School of Information Science and Technology, Osaka University, Japan 2 Cybermedia Center, Osaka University,
More informationDEIM Forum 2009 E
DEIM Forum 2009 E5-3 464-8601 1 606-8501 464 8601 1 E-mail: lifushi@arch.itc.nagoya-u.ac.jp, mayumi@mm.media.kyoto-u.ac.jp, {hirano,kajita,mase}@itc.nagoya-u.ac.jp Abstract Study on a Recipe Recommendation
More information”‰−ofiI…R…fi…e…L…X…g‡ðŠp‡¢‡½„�“õ„‰›Ê‡Ì™ñ”¦
1 1 5 1.1........................................... 5 1.2.................................. 6 1.2.1.............. 6 1.2.2........................... 7 1.3........................................... 7
More informationIPSJ SIG Technical Report Vol.2011-MUS-91 No /7/ , 3 1 Design and Implementation on a System for Learning Songs by Presenting Musical St
1 2 1, 3 1 Design and Implementation on a System for Learning Songs by Presenting Musical Structures based on Phrase Similarity Yuma Ito, 1 Yoshinari Takegawa, 2 Tsutomu Terada 1, 3 and Masahiko Tsukamoto
More information[12] Qui [6][7] Google N-gram[11] Web ( 4travel 5, 6 ) ( 7 ) ( All About 8 ) (1) (2) (3) 3 3 (1) (2) (3) (a) ( (b) (c) (d) (e) (1
RD-003 Building a Database of Purpose for Action from Word-of-mouth on the Web y Hiromi Wakaki y Hiroko Fujii y Michiaki Ariga y Kazuo Sumita y Kouta Nakata y Masaru Suzuki 1 ().com 1 Amazon 2 3 [10] 2007
More informationIPSJ SIG Technical Report Vol.2010-SLDM-144 No.50 Vol.2010-EMB-16 No.50 Vol.2010-MBL-53 No.50 Vol.2010-UBI-25 No /3/27 Twitter IME Twitte
Twitter 1 1 1 IME Twitter 2009 12 15 2010 2 1 13590 4.83% 8.16% 2 3 Web 10 45% Relational Analysis between User Context and Input Word on Twitter Yutaka Arakawa, 1 Shigeaki Tagashira 1 and Akira Fukuda
More information<> <name> </name> <body> <></> <> <title> </title> <item> </item> <item> 11 </item> </>... </body> </> 1 XML Web XML HTML 1 name item 2 item item HTML
DEWS2008 C6-4 XML 606-8501 E-mail: yyonei@db.soc.i.kyoto-u.ac.jp, {iwaihara,yoshikawa}@i.kyoto-u.ac.jp XML XML XML, Abstract Person Retrieval on XML Documents by Coreference that Uses Structural Features
More information和文タイトル
Twitter A Proposal of a Topic Transition Analysis System for Tweets 1 1 1 Center for Information and Communication Technology, Hitotsubashi University Abstract: In this paper, we propose an interactive
More informationDEIM Forum 2019 H2-2 SuperSQL SuperSQL SQL SuperSQL Web SuperSQL DBMS Pi
DEIM Forum 2019 H2-2 SuperSQL 223 8522 3 14 1 E-mail: {terui,goto}@db.ics.keio.ac.jp, toyama@ics.keio.ac.jp SuperSQL SQL SuperSQL Web SuperSQL DBMS PipelineDB SuperSQL Web Web 1 SQL SuperSQL HTML SuperSQL
More informationLyra 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 informationDEIM Forum 2014 B Twitter Twitter Twitter 2006 Twitter 201
DEIM Forum 2014 B2-4 305 8550 1 2 305 8550 1 2 E-mail: {yamaguchi,yamahei,satoh}@ce.slis.tsukuba.ac.jp Twitter Twitter 2 1 1. Twitter 2006 Twitter 2012 5 [1]Twitter RT RT Twitter Twitter RT Twitter 2 1
More informationDEIM Forum 2015 F8-4 Twitter Twitter 1. SNS
DEIM Forum 2015 F8-4 Twitter 432 8011 3-5-1 432 8011 3-5-1 E-mail: cs11032@s.inf.shizuoka.ac.jp, {yokoyama,fyamada}@inf.shizuoka.ac.jp Twitter 1. SNS SNS SNS Twitter 1 Twitter SNS facebook 2 mixi 3 Twitter
More informationDEIM Forum 2014 P3-3 A Foreseeing System of Search Results based on Query Operations on the Graph Interface
DEIM Forum 2014 P3-3 A Foreseeing System of Search Results based on Query Operations on the Graph Interface 163-8677 1-24-2 E-mail: j110015@ns.kogakuin.ac.jp, kitayama@cc.kogakuin.ac.jp Web web 1. Web
More information_314I01BM浅谷2.indd
587 ネットワークの表現学習 1 1 1 1 Deep Learning [1] Google [2] Deep Learning [3] [4] 2014 Deepwalk [5] 1 2 [6] [7] [8] 1 2 1 word2vec[9] word2vec 1 http://www.ai-gakkai.or.jp/my-bookmark_vol31-no4 588 31 4 2016
More information地図操作 操作解析 チャンク判定 アプリケーション判定 提示画面決定 1 緯度経度情報抽出 注記 DB 領域 DB Gemini (Geographical Enhanced Map Interface for Navigation on the Internet)
DEWS2007 A9-6 GeminiMap: 670-0092 1 1-12 670-0092 1 1-12 670-0092 1 1-12 E-mail: {na02x165,nd06c019}@stshse.u-hyogo.ac.jp, sumiya@shse.u-hyogo.ac.jp,,.,,.,,. Gemini (Geographical Enhanced Map Interface
More informationuntitled
DEIM Forum 2019 B3-3 305 8573 1-1-1 305 8573 1-1-1 ( ) 151-0053 1-3-15 6F word2vec, An Interface for Browsing Topics of Know-How Sites Shuto KAWABATA, Ohkawa YOUHEI,WenbinNIU,ChenZHAO, Takehito UTSURO,and
More informationWeb 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和文タイトル
Paper Browsing System with Structure Analysis and Displaying Annotation on Side-note Windows Takeshi Abekawa Akiko Aizawa National Institute of Informatics Abstract: In this paper, we introduce our on-going
More informationuntitled
DEIM Forum 2019 C1-2 305-8573 1-1-1 305-8573 1-1-1 () 151-0053 1-3-15 6F QA,,,, Detecting and Analysing Chinese Web Sites for Collecting Know-How Knowledge Wenbin NIU, Yohei OHKAWA,ShutoKAWABATA,ChenZHAO,TianNIE,
More informationIPSJ SIG Technical Report Vol.2009-DBS-149 No /11/ Bow-tie SCC Inter Keyword Navigation based on Degree-constrained Co-Occurrence Graph
1 2 1 Bow-tie SCC Inter Keyword Navigation based on Degree-constrained Co-Occurrence Graph Satoshi Shimada, 1 Tomohiro Fukuhara 2 and Tetsuji Satoh 1 We had proposed a navigation method that generates
More information,,, Twitter,,, ( ), 2. [1],,, ( ),,.,, Sungho Jeon [2], Twitter 4 URL, SVM,, , , URL F., SVM,, 4 SVM, F,.,,,,, [3], 1 [2] Step Entered
DEIM Forum 2016 C5-1 182-8585 1-5-1 E-mail: saitoh-ryoh@uec.ac.jp, terada.minoru@uec.ac.jp Twitter,, Twitter,,, Bag of Words, Latent Semantic Indexing,.,,,, Twitter,, Twitter,, 1. SNS, SNS Twitter 1,,,
More informationSICE東北支部研究集会資料(2017年)
307 (2017.2.27) 307-8 Deep Convolutional Neural Network X Detecting Masses in Mammograms Based on Transfer Learning of A Deep Convolutional Neural Network Shintaro Suzuki, Xiaoyong Zhang, Noriyasu Homma,
More information1 Web DTN DTN 2. 2 DTN DTN Epidemic [5] Spray and Wait [6] DTN Android Twitter [7] 2 2 DTN 10km 50m % %Epidemic 99% 13.4% 10km DTN [8] 2
DEIM Forum 2014 E7-1 Web DTN 112 8610 2-1-1 UCLA Computer Science Department 3803 Boelter Hall, Los Angeles, CA 90095-1596, USA E-mail: yuka@ogl.is.ocha.ac.jp, mineo@cs.ucla.edu, oguchi@computer.org Web
More informationVol. 46 No. SIG 13(TOD 27) ) ),4) 4) 1 2 5) 2 Cutting Scatter/Gather 6),7) Fractionation 6) Leuski 8)
Vol. 46 No. SIG 13(TOD 27) Sep. 2005 94 95 IREX A Label-based Navigation Method Using Informatively Named Entities Hiroyuki Toda, Hidekazu Nakawatase and Ryoji Kataoka Due to the growth of the Internet,
More information189 2015 1 80
189 2015 1 A Design and Implementation of the Digital Annotation Basis on an Image Resource for a Touch Operation TSUDA Mitsuhiro 79 189 2015 1 80 81 189 2015 1 82 83 189 2015 1 84 85 189 2015 1 86 87
More information2014 2
2014 2 Web Web 1 1 1 1.1................................... 1 1.2.................................... 1 1.3.............................. 1 1.4.................................... 2 1.5...................................
More information1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15. 1. 2. 3. 16 17 18 ( ) ( 19 ( ) CG PC 20 ) I want some rice. I want some lice. 21 22 23 24 2001 9 18 3 2000 4 21 3,. 13,. Science/Technology, Design, Experiments,
More informationSERPWatcher SERPWatcher SERP Watcher SERP Watcher,
SERPWatcher 112-8610 2-1-1 112-8610 2-1-1 229-8558 5-10-1 E-mail: nakabe@db.is.ocha.ac.jp, chiemi@is.ocha.ac.jp SERPWatcher SERP Watcher SERP Watcher, SERP Analysis of transition of ranking in SERP Watcher
More informationHASC2012corpus HASC Challenge 2010,2011 HASC2011corpus( 116, 4898), HASC2012corpus( 136, 7668) HASC2012corpus HASC2012corpus
HASC2012corpus 1 1 1 1 1 1 2 2 3 4 5 6 7 HASC Challenge 2010,2011 HASC2011corpus( 116, 4898), HASC2012corpus( 136, 7668) HASC2012corpus HASC2012corpus: Human Activity Corpus and Its Application Nobuo KAWAGUCHI,
More information14 2 5
14 2 5 i ii Surface Reconstruction from Point Cloud of Human Body in Arbitrary Postures Isao MORO Abstract We propose a method for surface reconstruction from point cloud of human body in arbitrary postures.
More informationGUI(Graphical User Interface) GUI CLI(Command Line Interface) GUI
24 GUI(Graphical User Interface) GUI CLI(Command Line Interface) GUI 1 1 1.1 GUI................................... 1 1.2 GUI.................... 1 1.2.1.......................... 1 1.2.2...........................
More information