RITE (Recognizing Inference in TExt) NTCIR- 9総括と NTCIR- 10へ向けて Yotaro Junta Watanabe1 Mizuno1 1Tohoku University Shuming Shi6 6MicrosoS Research Asia
|
|
|
- こうしろう くまじ
- 4 years ago
- Views:
Transcription
1 RITE (Recognizing Inference in TExt) NTCIR- 9総括と NTCIR- 10へ向けて Yotaro Junta Watanabe1 Mizuno1 1Tohoku University Shuming Shi6 6MicrosoS Research Asia Yusuke Miyao2 Tomohide Shibata3 2NaEonal InsEtute of InformaEcs Hiroshi Kanayama7 3Kyoto University Koichi Takeda7 7IBM Research Cheng- Wei Lee4 Chuan- Jie Lin5 4Academia 5NaEonal Taiwan Sinica Hideki Shima8 Ocean University Teruko Mitamura8 8Carnegie Mellon University 第106回IFAT 第85回DD合同研究発表会
2 RITE RITE (Recognizing Inference in TExt) t 1 t 2 t 1 : t 2 : Simplified, TradiHonal
3 MoHvaHon (InformaHon Access) (QuesHon Answering) (InformaHon Retrieval) (Text SummarizaHon) 106 IFAT 85 DD
4 RITE Binary- Class (BC) 1 <t 1, t 2 > t 1 t 2 (2 ) MulH- Class (MC) 1 <t 1, t 2 > 5 Entrance Exam ( ) BC RITE4QA QA
5 Wikipedia t 1 : 1 t 2 : 1
6 RITE t 1 : t 2 : Does t 1 entail (infer) t 2? Subtask Input Output EvaluaEon BC (t 1, t 2 ) Y (Yes, t 1 t 2 ) N (No) Accuracy MC Entrance Exam (t 1, t 2 ) (t 1, t 2 ) RITE System Yes F (forward; t 1 t 2 ) R (reverse; t 2 t 1 ) B (bidirechonal; t 1 t 2 ) No C (contradichon) I (independence) Y / N Eval (Automatic) Accuracy Accuracy RITE4QA (t 1, t 2 ) Y / N MRR, Top1, Accuracy application-oriented
7 QA TAC RTE (2- way) X TAC RTE (3- way) X X MSR Paraphrase Corpus X CLEF AVE X Kurohashi Lab s X (X) NTCIR- 9 RITE SemEval CLTE (S, T) X X X X X X X X
8 RITE Number of submiced runs Subtask Language Total JA CS CT BC MC Entrance Exam RITE4QA Total
9 (BC) JA Run Accuracy JAIST JAIST JAIST NTTCS LTI LTI LTI NTTCS IBM FX Average Baseline (char overlap) Showing runs above the average. CS Run Accuracy UIOWA- 01 * UIOWA- 03 * UIOWA- 02 * ICRC_HITSZ FudanNLP ICRC_HITSZ FudanNLP WHUTE NTU WHUTE WUST NTU NTU ZSWSL IASLD ICL Average Baseline (char overlap) CT Run Accuracy UIOWA- 01 * UIOWA- 02 * IASLD IASLD III_CYUT_NTHU IASLD NTOUA Average Baseline (char overlap) * UIOWA Systems contain manual intervenhon (not fully automahc).
10 (MC) JA CS CT Run Accuracy IBM KYOTO KYOTO IBM NTTCS NTTCS IBM Average Baseline (char overlap) Run Accuracy UIOWA- 01 * UIOWA- 02 * UIOWA- 03 * ICRC_HITSZ ICRC_HITSZ ZSWSL WHUTE Average Baseline (char overlap) Run Accuracy UIOWA- 01 * UIOWA- 02 * UIOWA- 03 * MCU IMTKU IMTKU Average Baseline (char overlap) * UIOWA Systems contain manual intervenhon (not fully automahc).
11 (EXAM) JA Run Accuracy IBM TU TU IBM LTI KYOTO KYOTO LTI JAIST JAIST TU JAIST LTI KYOTO Average Baseline (char overlap)
12 (RITE4QA) JA CS CT Run Acc MRR LTI JAIST JAIST JAIST LTI JUCS Average Baseline (char overlap) Baseline (all yes) Baseline (random) Baseline (QA system) Oracle Run Acc MRR UIOWA- 01 * IMTKU WHUTE WHUTE IMTKU IMTKU ICL ICRC_HITSZ WHUTE ICRC_HITSZ Average * UIOWA Systems contain manual intervenhon (not fully automahc). Run Acc MRR UIOWA- 01 * IMTKU NTOUA NTOUA IMTKU IMTKU NTOUA ICRC_HITSZ ICRC_HITSZ Average Baseline (char overlap) Baseline (all yes) Baseline (random) Baseline (QA system) Oracle
13 (KYOTO, LTI, NTTCS, SITLP, WHUTE, ZSWSL) Bilingual enrichment (JAIST, JUCS) (UIOWA) Lexical FuncHonal Grammar (FX) (TU) Alexandria Digital Library, Baidupedia, CC-CEDICT,, HowNet, NAIST jdic, REIKAI-SHOGAKU, Wikipedia, WordNet, etc
14 Overlap (character, word, bigram, trigram, head-word, POS, NE, numerical expression) String Similarity (Jaro distance, Jaro Winkler distance, Jaccard Coefficient, Chebyshev Distance, Dice Coefficient, Manhattan Distance, Longest Common Subsequence, Cosine similarity, Levenshtein Edit Distance, BLEU score) Structural matching (predicate-argument matching, subtree matching, Tree Edit Distance) Verbs number mismatch Antonyms Negation / Polarity matching Temporal matching (5% improvement in EXAM [IBM]) Quantification (all, only, most, every ) Quote (something just said might not be true )
15 RITE- 1, etc. Alexandria Digital Library, Baidupedia, CC-CEDICT,, HowNet, NAIST jdic, REIKAI- SHOGAKU, Wikipedia, WordNet, etc AblaHon study 24
16 Recognizing Inference in NTCIR- 10 RITE- 2
17 Recognizing Inference in RITE- 2 BC, MC : RITE- 1 (EXAM) BC Search * t 2, Wikipedia t 2 : t 2 : QA * q t 2 q t 2 q: X X t 2 : RITE4QA: (Simplified, TradiHonal)
18 RITE- 2 Does t 1 entail (infer) t 2? BC (t 1, t 2 ) Y (, t 1 t 2 ) N ( ) MC (t 1, t 2 ) RITE F ( ; t 1 t 2 ) B ( ; t 1 t 2 ) C ( ) I ( ) 評価 大学入試 BC (t 1, t 2 ) System Y / N ( 自動 ) 大学入試検索 (t 2, ) T ( ) / F ( ) 大学入試 QA (q, t2, ) T ( ) / F ( ) 18
19 RITE- 1 vs. RITE- 2 2 (Binary- Class) (MulH- class) (Entrance Exam) RITE- 1 2 (Yes or No) 5 BC (2 ) RITE- 2 2 (Yes or No) 4 BC (2 ) SEARCH QA RITE4QA
20 Recognizing Inference in RITE / /06/30 RITE /07/ /11/ /12/ /03/ /05/ /06/18 21 NTCIR- 10
21 Recognizing Inference in RITE hcp://
22
Microsoft Word - .....J.^...O.|Word.i10...j.doc
P 1. 2. R H C H, etc. R' n R' R C R'' R R H R R' R C C R R C R' R C R' R C C R 1-1 1-2 3. 1-3 1-4 4. 5. 1-5 5. 1-6 6. 10 1-7 7. 1-8 8. 2-1 2-2 2-3 9. 2-4 2-5 2-6 2-7 10. 2-8 10. 2-9 10. 2-10 10. 11. C
橡ボーダーライン.PDF
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 To be or not to be 32 33 34 35 36 37 38 ( ) 39 40 41 42 43 44 45 46 47 48 ( ) 49 50 51 52
¥ì¥·¥Ô¤Î¸À¸ì½èÍý¤Î¸½¾õ
2013 8 18 Table of Contents = + 1. 2. 3. 4. 5. etc. 1. ( + + ( )) 2. :,,,,,, (MUC 1 ) 3. 4. (subj: person, i-obj: org. ) 1 Message Understanding Conference ( ) UGC 2 ( ) : : 2 User-Generated Content [
2 1,384,000 2,000,000 1,296,211 1,793,925 38,000 54,500 27,804 43,187 41,000 60,000 31,776 49,017 8,781 18,663 25,000 35,300 3 4 5 6 1,296,211 1,793,925 27,804 43,187 1,275,648 1,753,306 29,387 43,025
IPSJ-TOD
Vol. 3 No. 2 91 101 (June 2010) 1 1 1 2 1 TSC2 Automatic Evaluation of Text Summaries by Using Paraphrase Kazuho Hirahara, 1 Hidetsugu Nanba, 1 Toshiyuki Takezawa 1 and Manabu Okumura 2 The evaluation
( )
NAIST-IS-MT1051071 2012 3 16 ( ) Pustejovsky 2 2,,,,,,, NAIST-IS- MT1051071, 2012 3 16. i Automatic Acquisition of Qualia Structure of Generative Lexicon in Japanese Using Learning to Rank Takahiro Tsuneyoshi
(NICT) ( ) ( ) (NEC) ( )
(NICT) ( ) () (NEC) ( ) ! Paraphrase (Paraphrasing) l l ! l h"p://paraphrasing.org/bib- cat.html l 12 50 l 640 (2014 6)! l l l l l l ! [ ] 2! [ ] ( )! :............ 1 2 1 = 2 = ! [ ]! [ ]! :............
2014/1 Vol. J97 D No. 1 2 [2] [3] 1 (a) paper (a) (b) (c) 1 Fig. 1 Issues in coordinating translation services. (b) feast feast feast (c) Kran
![2014/1 Vol. J97 D No. 1 2 [2] [3] 1 (a) paper (a) (b) (c) 1 Fig. 1 Issues in coordinating translation services. (b) feast feast feast (c) Kran](/thumbs/92/107842917.jpg "2014/1 Vol. J97 D No. 1 2 [2] [3] 1 (a) paper (a) (b) (c) 1 Fig. 1 Issues in coordinating translation services. (b) feast feast feast (c) Kran")
a) b) c) Improving Quality of Pivot Translation by Context in Service Coordination Yohei MURAKAMI a), Rie TANAKA b),andtoruishida c) Web 1. Web 26.8% 30.9% 21.3% 21% 1 n n(n 1) Department of Social Informatics,
2015taisetumatome.rtf
B B B( ) B3 - B3 1 3g 1/3 B 1. B1() B1() 2. B2() B2() 3. B5() B5() 4. B6() B6()( ) 5. B12() B12() 6. 1q60 160m 50m 50m 20m 8520 80 10 64 5075 30 80 B B 1 30 BB BC EPA . ?? 6 C E C 1 30 1 0.4mg4
スライド 1
22 YES NO ( ) 15 4 3 15 5 : Wikipedia text mining : Wikipedia Data mining DM heuristic, 1: 2: 1: 2: 1: 2: 3: 4: 5: 6: 7: 8: 1: 2: 1: 2: 1: 2: 3: 4: 5: 1: 2: 1: 2: 3: 4: 5: 1: 2: 3: 1: 2: 1: 2: 3:
( : 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...
EP760取扱説明書
D D D # % ' ) * +, B - B / 1 Q&A B 2 B 5 B 6 Q & A 7 8 $ % & ' B B B ( B B B B B B B B B B B ) B B B A # $ A B B * 1 2 # $ % # B B % $ # $ % + B B 1 B 2 B B B B B B B B B B , B B B - 1 3 2 2 B B B B B
kut-paper-template.dvi
14 Application of Automatic Text Summarization for Question Answering System 1030260 2003 2 12 Prassie Posum Prassie Prassie i Abstract Application of Automatic Text Summarization for Question Answering
子ども･子育て支援新制度 全国総合システム（仮称）に関するインターフェース仕様書 市町村・都道府県編（初版）
1...1 1.1... 1 1.1.1... 1 1.2... 3 1.2.1... 3 1.2.2... 4 1.3... 5 1.4... 6 1.4.1... 6 (1) B11:...6 (2) B11:...8 1.4.2... 11 (1) B31:... 11 1.4.3... 12 (1) B21, B41:... 12 2... 14 2.1... 14 2.1.1... 14
/27 (13 8/24) (9/27) (9/27) / / / /16 12
79 7 79 6 14 7/8 710 10 () 9 13 9/17 610 13 9/27 49 7 14 7/8 810 1 15 8/16 11 811 1 13 9/27 (13 8/24) (9/27) (9/27) 49 15 7/12 78 15 7/27 57 1 13 8/24 15 8/16 12 810 10 40 1 Wikipedia 13 8/18, 8/28 79
Title 中国における大学入試改革の動向 : 地方 大学への権限委譲に関する一考察 Author(s) 楠山, 研 Citation 京都大学大学院教育学研究科紀要 (2005), 51: 128-141 Issue Date 2005-03-31 URL http://hdl.handle.net/2433/57556 Right Type Departmental Bulletin Paper
( ) ( ) (action chain) (Langacker 1991) ( 1993: 46) (x y ) x y LCS (2) [x ACT-ON y] CAUSE [BECOME [y BE BROKEN]] (1999: 215) (1) (1) (3) a. * b. * (4)
![( ) ( ) (action chain) (Langacker 1991) ( 1993: 46) (x y ) x y LCS (2) [x ACT-ON y] CAUSE [BECOME [y BE BROKEN]] (1999: 215) (1) (1) (3) a. * b. * (4)](/thumbs/40/20534161.jpg "( ) ( ) (action chain) (Langacker 1991) ( 1993: 46) (x y ) x y LCS (2) [x ACT-ON y] CAUSE [BECOME [y BE BROKEN]] (1999: 215) (1) (1) (3) a. * b. * (4)")
1 1 (lexical conceptual structure, LCS) 2 LCS 3 4 LCS 5 6 2 LCS (1999) LCS 2 (1) [x ACT(-ON y)] CAUSE [BECOME [z BE-AT w]] 1 (1993) ( ) V1 V2 2 (1) y z y z (5.3 ) ( ) ( ) (action chain) (Langacker 1991)
Wiki Wiki Wiki...
21 RDB Wiki 0830016 : : 2010 1 29 1 1 5 1.1........................................... 5 1.2 Wiki...................................... 7 1.2.1 Wiki.................... 7 1.2.2 Wiki.................. 8
N-gram Language Models for Speech Recognition
N-gram Language Models for Speech Recognition Yasutaka SHINDOH ver.2011.01.22 1. 2. 3. 4. N-gram 5. N-gram0 6. N-gram 7. 2-gram vs. 3-gram vs. 4-gram 8. 9. (1) name twitter id @y_shindoh web site http://quruli.ivory.ne.jp/document/
情報の構造とデータ処理
mizutani@ic.daito.ac.jp 2014 SQL information system input process output (information) (symbols) (information structure) (data) 201411 ton/kg m/feet km 2 /m 2 (data structure) (integer) (real) (boolean)
2015 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
H27 28 4 1 11,353 45 14 10 120 27 90 26 78 323 401 27 11,120 D A BC 11,120 H27 33 H26 38 H27 35 40 126,154 129,125 130,000 150,000 5,961 11,996 6,000 15,000 688,684 708,924 700,000 750,000 1300 H28
Drive-by-Download JavaScript
JAIST Reposi https://dspace.j Title Drive-by-Download 攻撃予測のための難読化 JavaScript の検知に関する研究 Author(s) 本田, 仁 Citation Issue Date 2016-03 Type Thesis or Dissertation Text version author URL http://hdl.handle.net/10119/13608
Vol.54 No (July 2013) [9] [10] [11] [12], [13] 1 Fig. 1 Flowchart of the proposed system. c 2013 Information
![Vol.54 No (July 2013) [9] [10] [11] [12], [13] 1 Fig. 1 Flowchart of the proposed system. c 2013 Information](/thumbs/91/104959916.jpg "Vol.54 No (July 2013) [9] [10] [11] [12], [13] 1 Fig. 1 Flowchart of the proposed system. c 2013 Information")
Vol.54 No.7 1937 1950 (July 2013) 1,a) 2012 11 1, 2013 4 5 1 Similar Sounds Sentences Generator Based on Morphological Analysis Manner and Low Class Words Masaaki Kanakubo 1,a) Received: November 1, 2012,
LM4663 2 Watt Stereo Class D Audio Pwr Amp w/Stereo Headphone Amplifier (jp)
2 Watt Stereo Class D Audio Power Amplifier with Stereo Headphone Amplifier Literature Number: JAJS693 Boomer 2006 4 A very minor text edit (typo). (MC) Converted to nat2000 DTD. Few edits on Table 1 and
FX ) 2
(FX) 1 1 2009 12 12 13 2009 1 FX ) 2 1 (FX) 2 1 2 1 2 3 2010 8 FX 1998 1 FX FX 4 1 1 (FX) () () 1998 4 1 100 120 1 100 120 120 100 20 FX 100 100 100 1 100 100 100 1 100 1 100 100 1 100 101 101 100 100
WINET情報
WINETCONTENTS 1 2 3 Q&A Q A 4 Q A 5 Q A 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 No. 10. 1. 11. 2. 12. 3. 4. 13. 5. 14. 6. 7. 15. 8. 9. 16. 33 17. 33. 34. 35. 18. 19. 36.
Corrected Version NICT /11/15, 1 Thursday, May 7,
Corrected Version NICT 26 2008/11/15, 1 1 Word Sketch Engine (Kilgarriff & Tugwell 01; Srdanovic, et al. 08) 2 2 3 3 ( ) I-Language Grammar is Grammar and Usage is Usage (Newmeyer 03) 4 4 (is-a ) ( ) (
IPSJ SIG Technical Report Vol.2009-HCI-134 No /7/17 1. RDB Wiki Wiki RDB SQL Wiki Wiki RDB Wiki RDB Wiki A Wiki System Enhanced by Visibl
1. RDB Wiki 1 1 2 Wiki RDB SQL Wiki Wiki RDB Wiki RDB Wiki A Wiki System Enhanced by Visible RDB Operations Toshiya Okumura, 1 Minoru Terada 1 and Kazutaka Maruyama 2 Although Wiki systems can easily be
Formal Model for Kana-Kanji Conversion (KKC) In Japanese input, users type in phonetic Hiragana, but proper Japanese is written in logographic Kanji K
NLP Programming Tutorial 6 - Kana-Kanji Conversion Graham Neubig Nara Institute of Science and Technology (NAIST) 1 Formal Model for Kana-Kanji Conversion (KKC) In Japanese input, users type in phonetic
A Japanese Word Dependency Corpus ÆüËܸì¤Îñ¸ì·¸¤ê¼õ¤±¥³¡¼¥Ñ¥¹
A Japanese Word Dependency Corpus 2015 3 18 Special thanks to NTT CS, 1 /27 Bunsetsu? What is it? ( ) Cf. CoNLL Multilingual Dependency Parsing [Buchholz+ 2006] (, Penn Treebank [Marcus 93]) 2 /27 1. 2.
IPSJ SIG Technical Report Vol.2010-NL-199 No /11/ treebank ( ) KWIC /MeCab / Morphological and Dependency Structure Annotated Corp
1. 1 1 1 2 treebank ( ) KWIC /MeCab / Morphological and Dependency Structure Annotated Corpus Management Tool: ChaKi Yuji Matsumoto, 1 Masayuki Asahara, 1 Masakazu Iwatate 1 and Toshio Morita 2 This paper
12021108_07.indd
雯 A Study of Japanese Time Adverbs Focusing on Adverbs that Express Immediacy Wen - Shun CAIANG Tamkang University of Taiwan This study focuses on adverbs that express immediacy : sugu, sikyuu, tadachini,
Building a Culture of Self- Access Learning at a Japanese University An Action Research Project Clair Taylor Gerald Talandis Jr. Michael Stout Keiko Omura Problem Action Research English Central Spring,
1 2 3 4 5 1 1 136 2 137 2 1 1 138 2 1 2 139 140 141 142 3 143 3 144 145 4 1 2 146 3 4 147 5 1 2 3 148 1 2 149 3 5 1 2 150 3 151 1 152 2 153 6 1 2 154 3 155 4 1 156 2 3 4 5 157 7 1 2 3 4 158 5 159 6 8 1
Kyoto University 2009 1
K Y O T O U N I V E R S I T Y Kyoto University 2009 1 Kyoto University 2009 2 3 Kyoto University 2009 Kyoto University 2009 4 5 Kyoto University 2009 Kyoto University 2009 6 Kyoto University 2009 7 Kyoto
jnlp98f.dvi
December 9, 1998 RT0288 Human-Computer Interaction 19 pages Research Report A word-based Japanese language model N. Itoh, M. Nishimura, S. Ogino, and K. Yamasaki IBM Research, Tokyo Research Laboratory
15 7 26 1,276 3,800 1 16 15 1 2 3 4 2
1 15 7 26 1,276 3,800 1 16 15 1 2 3 4 2 JA 3 4 2 1 3 2001 1981 6 10% 10 30% 1 2 JA JA 2 4 JA 2 1 2 1 2 1 2 1 2 1 2 7 5 1 1 1 3 1 6 1 1 2 2 1 7 2 3 3 53 1 2000 30 8 250 53 435 20 35 3 1 8 2 4 3 2 2 232
『こみの株式会社』の実践
2003 . JA JA A JA 811 2005/8/11 1003 452 10 960 28 2005/8/11 1003 452 6 120 29 2005/8/11 2003 151 10 420 33 2005/8/11 2003 211 3 180 31 2005/8/11 2003 211 3 150 32 827 400 5 80 221 2005/6/25 900 3 300
EX-word_Library_JA
JA 2 3 4 5 14 7 1 2 6 3 1 2 7 3 8 27 1 2 3 1 2 3 9 1 2 3 1 2 3 10 12 13 14 11 1 12 1 2 13 1 2 3 25 14 1 2 3 25 15 1 2 3 25 16 1 2 3 25 17 1 2 3 25 18 1 2 3 4 25 19 1 2 3 4 25 20 1 2 21 3 4 25 22 1 2 3
324.pdf
50 50 10 30 11 26 12 27 14 16 27 18 20 21 22 22 22 22 23 24 24 1 No.324 JA 2 85 69 20 12 81 18 12 22 93 10 31 3 50 50 30 30 50 22 27 27 10 16 14 52 10 62 15 64 25 24 50 4 25 23 27 5 10 11 25 6 11 49 10
"CAS を利用した Single Sign On 環境の構築"
CAS Single Sign On (Hisashi NAITO) naito@math.nagoya-u.ac.jp Graduate School of Mathematics, Nagoya University naito@math.nagoya-u.ac.jp, Oct. 19, 2005 Tohoku Univ. p. 1/40 Plan of Talk CAS CAS 2 CAS Single
データプロジェクター総合
SYSTEM USE P.4 PORTABLE P.6 COMPACT P.8-9 MOBILE P.9 ENTRY P.9 S Y S T E M U S E FX52 PORTABLE PX41 COMPACT CX8680 INPUT A AUDIO INPUT A/B VIDEO IN INPUT B S VIDEO VIDEO AUDIO MONITOR OUTPUT AUDIO REMOTE
人芯経営論 ･･･リーダーシップ考②
2009/12/15 2009/11/17 2009/11/16 2009/10/19 2009/10/15 2009/10/1 2009/9/17 2009/9/1 2009/8/17 2009/8/17 2009/8/14 2009/8/12 2009/7/28 2009/7/17 2009/7/15 2009/6/24 2009/6/18 2009/6/15 2009/5/20 2009/5/15
大学案内2005-1.inx
4 Kyoto University 2005 Kyoto University 2005 1 2 Kyoto University 2005 Kyoto University 2005 3 4 Kyoto University 2005 Kyoto University 2005 5 6 Kyoto University 2005 Introduction to the Beauties of Kyoto
ohp1.dvi
2008 1 2008.10.10 1 ( 2 ) ( ) ( ) 1 2 1.5 3 2 ( ) 50:50 Ruby ( ) Ruby http://www.ruby-lang.org/ja/ Windows Windows 3 Web Web http://lecture.ecc.u-tokyo.ac.jp/~kuno/is08/ / ( / ) / @@@ ( 3 ) @@@ :!! ( )
CD5003F_cover.indd
CD Player CD5003 1 2 3 OPT_080311F1 4 CD TEXT TEXT STANDBY POWER ON/STANDBY MP3/WMA DISPLAY OFF CD PLAYER CD5003 PHONES LEVEL 5 6 q w ª e ª PHONES LEVEL q w 0 e q w er t y u io STANDBY POWER ON/STANDBY
workshop_func_exp_ pptx
Introduction: What is Factuality? (Factuality) [ + 10] [ + 11] 2011/10/28 2 - - 2 Introduction: Motivation 2011/10/28 2 - - 3 Introduction: Motivation 2011/10/28 2 - - 4 Contents Introduction What is Factuality?
Ver.1.0.1-1512 1. 03 2. 04 3. 05 05 4. 06 07 5. 08 6. 09 10 11 12 14 7. 19 2 1. Plus / 3 2. 1 4 3. Plus 5 4. FX 6 4. 7 5. 1 200 3 8 6. 38 25 16 9 6. 10 6. 11 6. 38 / 12 6. 13 6. 25 14 6. 0 359 15 6. 3
橡matufw
3 10 25 3 18 42 1 2 6 2001 8 22 3 03 36 3 4 A 2002 2001 1 1 2014 28 26 5 9 1990 2000 2000 12 2000 12 12 12 1999 88 5 2014 60 57 1996 30 25 205 0 4 120 1,5 A 1995 3 1990 30 6 2000 2004 2000 6 7 2001 5 2002
O
11 2 1 2 1 1 2 1 80 2 160 3 4 17 257 1 2 1 2 3 3 1 2 138 1 1 170 O 3 5 1 5 6 139 1 A 5 2.5 A 1 A 1 1 3 20 5 A 81 87 67 A 140 11 12 2 1 1 1 12 22 1 10 1 13 A 2 3 2 6 1 B 2 B B B 1 2 B 100 B 10 B 3 3 B 1
BLEU Kishore Papineni, Salim Roukos, Todd Ward and Wei-Jing Zhu. (2002) BLEU: a method for Automatic Evaluation of Machine Translation. ACL. MT ( ) MT
4. BLEU @NICT mutiyama@nict.go.jp 1 BLEU Kishore Papineni, Salim Roukos, Todd Ward and Wei-Jing Zhu. (2002) BLEU: a method for Automatic Evaluation of Machine Translation. ACL. MT ( ) MT ( ) BLEU 2 BLEU
/™Z‚å‰IŠv‚æ36“ƒ /fi¡„´“NŠm†€
do/does/did A Study of Teaching the Auxiliary Verbs do /does /did to Beginning Learners of EFL Yasuhiro Fujiwara do/does/did Abstract Mastery of the auxiliary verbs do/does/did, conventionally termed as
WIDE 1
WIDE 1 2 Web Web Web Web Web Web Web Web Web Web? Web Web Things to cover Web Web Web Web Caching Proxy 3 Things NOT covered / How to execute Perl Scripts as CGI binaries on Windows NT How to avoid access
Sloman (1998) Category inference is not a tree
Web BBS Journal Club 2006/02/08 rep: Cognitive Psychology, 1998, Vol.35, No.1, pp.1-33. Category inference is not a tree: The myth of inheritance hierarchies Steven A. Sloman 1 Yes/No - A car headlight
+1 3 JKL F7 F6 +1 3 JKL SIMUL VIEW INST 9-16 DRUM 3 / 11 TRIG LIST 4 / 12 SAMPLE 5 / 13 OTHERS 6 / 14 7 / 15 PERFORM 1 / 9 VOICE 2 / 10 STEREO 8 / 16 OTHERS 6 / 14 DISK F1 DISK F1 SHIFT F5 DISK F1
2
NTT 2012 NTT Corporation. All rights reserved. 2 3 4 5 Noisy Channel f : (source), e : (target) ê = argmax e p(e f) = argmax e p(f e)p(e) 6 p( f e) (Brown+ 1990) f1 f2 f3 f4 f5 f6 f7 He is a high school
駒田朋子.indd
2 2 44 6 6 6 6 2006 p. 5 2009 p. 6 49 12 2006 p. 6 2009 p. 9 2009 p. 6 2006 pp. 12 20 2005 2005 2 3 2005 An Integrated Approach to Intermediate Japanese 13 12 10 2005 8 p. 23 2005 2 50 p. 157 2 3 1 2010
JA2008
A1 1 10 vs 3 2 1 3 2 0 3 2 10 2 0 0 2 1 0 3 A2 3 11 vs 0 4 4 0 0 0 0 0 3 6 0 1 4 x 11 A3 5 4 vs 5 6 5 1 0 0 3 0 4 6 0 0 1 0 4 5 A4 7 11 vs 2 8 8 2 0 0 0 0 2 7 2 7 0 2 x 11 A5 9 5 vs 3 10 9 4 0 1 0 0 5
2009 1. 2. 3. 4. 5. 2 2009 CONTENTS 4 6 8 TOPIC 01 10 TOPIC 02 11 TOPIC 03 12 TOPIC 04 14 TOPIC 05 15 TOPIC 06 15 TOPIC 07 16 18 18 19 20 21 22 22 22 23 24 25 26 27 27 27 28 29 30 TOPIC 08 16 TOPIC 09
2016年2月27日11s感性工学会パンフレット
TIMETABLE 9 10 11 12 13 14 15 16 17 18 19 20 9 1 4 7 8 13:00-13:20 13:20-14:20 5 11 2 3 5 6 8 1 1 2 TIMETABLE 9 10 11 12 13 14 15 16 17 18 19 20 3 6-1 6-2 9 11 2 12 10 4 10-1 13 4 3 10-2 7 10:00-12:00
untitled
B 60 8 2 21 3 B - - 1 A. B. A B A A A B 2 A A 1830 A 10 - - 2 11 12 13 20 A 21 A B A 7 10 1830 1830 B - - 3 3 15 15 2 15 15 2 TO 15 TO 15 TO - - 4 1491 93 1493 17 2 = - - 5 , ZPANGRI P - - 6 1 8 1 15 15
1. 2. 3. 5. 256K DRAM LSI DRAM DRAM 80 DRAM RIE CVD 16K 64K 256K 1M DRAM DRAM No.1 DRAM NEC DRAM KrF CMP AMAT Cu Low-k 1M 4M 16M 64M 16k 64k 4M 16M 2000 2000 90 1990 28 R&D 1988 82 1987 16
3 Venue Venue Venue Venue Venue Venue SNS [2] Venue Venue [3] Venue Venue Venue [4] / Venue [5] Venue Venue Foursquare Venue Foursquare
![3 Venue Venue Venue Venue Venue Venue SNS [2] Venue Venue [3] Venue Venue Venue [4] / Venue [5] Venue Venue Foursquare Venue Foursquare](/thumbs/91/106692425.jpg "3 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)
skeiji.final.dvi
HTML HTML 1) HTML HTML 2) df idf 3) 4) : World Wide Web Automatic acquisition of hyponymy relations from HTML documents This paper describes an automatic acquisition method for hyponymy relations. Hyponymy
2 6
2 4 6 7 2 6 2 6 3 4 - c 5 G G G G G G d 6 c c 7 c 8 f d f d f d d f e f 5 b b d 5 c d d 9 d e d 0 0 5 c e cce 0 5 0 6 6 2 e 3 5 - e e e d b 4 bc d d d d dd ccdc c 5 d b c c e d 7 b f 6 6 s s s s s s s
Plastic Package (Note 12) Note 1: ( ) Top View Order Number T or TF See NS Package Number TA11B for Staggered Lead Non-Isolated Package or TF11B for S
Overture 68W ( ) 0.1 (THD N) 20Hz 20kHz 4 68W 8 38W SPiKe (Self Peak Instantaneous Temperature ( Ke)) SOA (Safe Operating Area) SPiKe 2.0 V ( ) 92dB (min) SN 0.03 THD N IMD (SMTPE) 0.004 V CC 28V 4 68W