(‘Û‰ï‹cj

 

A reference system for world wide web: Autoref

‹¤’˜@•½¬8”N3ŒŽ@IPSJ Proceedings of multimedia Japan 96 , pp.388-391

ƒEƒFƒuƒuƒ‰ƒEƒU‚ÉŽè‚ð‰Á‚¦‚È‚¢ðŒ‚ŁCƒEƒFƒuî•ñ‚Ì‚½‚ß‚ÌŽ«‘ƒVƒXƒeƒ€‚ð‘g‚Ý—§‚Ä‚é•û–@‚ðŽ¦‚µ‚½D“Á’¥‚́Cƒlƒbƒgƒ[ƒNã‚É“ÁŽê‚ȃT[ƒo‚ðÝ’肵CƒEƒFƒuƒuƒ‰ƒEƒU‚Æ“Æ—§‚ȃvƒƒOƒ‰ƒ€‚ŃEƒFƒuƒuƒ‰ƒEƒU‚É‹@”\‚ð•t‚¯‰Á‚¦‚邱‚Æ‚ðŽÀŒ»‚µ‚½‚±‚Æ‚Å‚ ‚éDì¬‚µ‚½–|–óƒVƒXƒeƒ€‚ÆŒø‰Ê‚ð”팱ŽÒ‚ð—p‚¢‚Ä”äŠr‚µ‚½D”~‘º‚́CƒVƒXƒeƒ€‚ÌŒ´Œ^‚Æ‚È‚éƒVƒXƒeƒ€‚ðì¬‚µC˜_•¶‚Ì‹Lq‚ð‚µ‚½DˆÉ“¡‚́CƒVƒXƒeƒ€‚Ì•]‰¿‚ðA”팱ŽÒ‚ðŽg‚Á‚Ä‘ª’肵‚½D

’˜ŽÒF”~‘º‹±ŽiCˆÉ“¡Cˆê

 

Knowledge discovery by logical resolution with usefulness measure

‹¤’˜@•½¬10”N11ŒŽ@ACM/IPSJ Proceedings of foundations of data organization, pp.89-96

˜_—„˜_ƒVƒXƒeƒ€‚ªo—Í‚·‚é˜_—Ž®‚ɑ΂µ‚āCî•ñ—˜_‚ÉŠî‚¢‚½ƒqƒ…[ƒŠƒXƒeƒBƒNƒX‚ð‚·‚é‚±‚ƂŁClŠÔ‚É‚Æ‚Á‚Ä—L—p‚ƍl‚¦‚ç‚ê‚é˜_—Ž®‚ð‘I•Ê‚·‚邱‚Æ‚ð’ñˆÄ‚µC‚»‚Ì•]‰¿‚ðs‚Á‚½D

’˜ŽÒFŽR–{ ‰pŽqC”~‘º‹±Ži

 

Dynamic programming: a method for taking advantage of technical terminology@in Japanese documents

‹¤’˜@•½¬12”N10ŒŽ@Proceedings of the 5th international workshop on information retrieval with Asian language, pp.125 -132

“ú–{Œê‚Ì‹Zp—pŒê‚Ì—p–@‚𕪐͂µCDPƒ}ƒbƒ`ƒ“ƒO‚É‚æ‚錟õ‚ðs‚¤‚±‚Æ‚ÅŒŸõ¸“x‚ªã‚ª‚邱‚Æ‚ª‚ ‚邱‚Æ‚ðŽ¦‚µ‚½D‚»‚µ‚āC“ú–{Œê‚Ì‹Zp—pŒê‚̍\‘¢‚ªDPƒ}ƒbƒ`ƒ“ƒO‚É“K‚µ‚Ä‚¢‚邱‚Æ‚ðŽ¦‚µ‚½D”~‘º‚́Cƒ_ƒCƒiƒ~ƒbƒNƒvƒƒOƒ‰ƒ~ƒ“ƒO‚ŏî•ñŒŸõ‚ðŽÀs‚·‚éƒvƒƒgƒ^ƒCƒvƒVƒXƒeƒ€‚ðÅ‰‚ɍ쐬‚µ‚½D

’˜ŽÒFŽR–{‰pŽqCŽR–{Š²—YC”~‘º‹±ŽiCKenneth W. Church

 

Using variable length for retrieving technical abstracts in Japanese

‹¤’˜@•½¬12”N10ŒŽ@Proceedings of the 5th international workshop on information retrieval with Asian language, pp.213 -214

î•ñŒŸõ‚É‚¨‚¢‚āC’·‚¢•¶Žš—ñ‚ðî•ñŒŸõ‚ÉŽg‚¤‚±‚Ƃ͍s‚í‚ê‚È‚¢D‚»‚ê‚́CƒVƒXƒeƒ€‚Ì“®ì‘¬“x‚ð’ቺ‚³‚¹‚é‚È‚Ç‚Ì–â‘肪‚ ‚邽‚ß‚Å‚ ‚éD‚µ‚©‚µC’·‚¢•¶Žš—ñ‚ðŽg‚¤‚±‚Æ‚ªŒø‰Ê‚ª‚ ‚é‚©‚Ç‚¤‚©‚Í’m‚ç‚ê‚Ä‚¢‚È‚©‚Á‚½D‚»‚±‚ŁCî•ñŒŸõ‚ÉŽg—p‚·‚镶Žš—ñ‚Ì’PˆÊ‚Ì’·‚³‚ð•Ï‰»‚³‚¹‚āC’·‚¢•¶Žš—ñ‚܂ňµ‚¤‚±‚Æ‚ª¸“x‚ÌŒüã‚ÉŠñ—^‚·‚邱‚Æ‚ðŽ¦‚µ‚½D

’˜ŽÒFFeng LinC ”~‘º‹±ŽiC ŽR–{Š²—YC Kenneth W. Church

 

Empirical Term Weighting and Expansion Frequency

‹¤’˜@•½¬12”N10ŒŽ@ACL Proceeding of the 2000 joint SIGDAT conference on empirical methods in natural language processing and very large corpora, pp.117-123

î•ñŒŸõ‚É‚¨‚¢‚āC—pŒê‚̏d‚Ý•t‚¯‚ÍŒŸõ¸“x‚ð¶‰E‚·‚éd—v‚È–â‘è‚Å‚ ‚邪C“Œv“I‚È—˜_‚Æ“Œv’l‚̃Xƒ€-ƒWƒ“ƒO‚ŏd‚Ý‚ðŒˆ‚ß‚é‚Æ‚¢‚¤•û–@‚ð’ñˆÄ‚µ‚½D‚±‚Ì•û–@‚ŁCŒoŒ±“I‚ɍs‚í‚ê‚Ä‚¢‚éd‚Ý•t‚¯‚Ì•ûŽ®‚Ɛ®‡«‚Ì‚ ‚錋‰Ê‚ª“¾‚ç‚ê‚é‚΂©‚è‚Å‚È‚­CExpansion frequency‚Æ‚¢‚¤V‚µ‚¢ŠT”O‚Ì“Œv’l‚ɂ‚¢‚Ä‚àC“KØ‚ȏd‚Ý‚ª’è‚܂邱‚Æ‚ðŽ¦‚µ‚½D‚³‚ç‚ɁCExpansion frequency‚Æ“Œv“I‚ȏd‚Ý•t‚¯‚ð‘g‚ݍ‡‚킹‚邱‚ƂŁCŒ¾Œê’mŽ¯‚ð‘å—Ê‚ÉŽg‚Á‚½î•ñŒŸõƒVƒXƒeƒ€‚Æ“¯“™‚ÌŒŸõ«”\‚ª“¾‚ç‚ê‚邱‚Æ‚ðŽ¦‚¹‚½D

’˜ŽÒF”~‘º‹±ŽiCKenneth W. Church

 

Empirical Term Weighting

‹¤’˜@•½¬13”N10ŒŽ@‚Qnd NTCIR Workshop Meeting 2001, pp.216-221

Kyoji Umemura, Yoshiyuki Takeda, Michiko Tanaka,Lin Feng, Eiko Yamamoto

 

Selecting indexing strings using adaptation

‹¤’˜@•½¬14”N8ŒŽ@The 25th international ACM SIGIR conference on research and development in information retrieval, pp.42 -43, ACM SIGIR 2002

î•ñŒŸõ‚É‚¨‚¢‚āCŒŸõ—v‹‚Ì‚È‚©‚©‚猟õ‚ÉŒø‰Ê‚Ì‚ ‚é•”•ª‚¾‚¯‚ðŽæ‚èo‚·‚±‚Ƃ͏d—v‚È–â‘è‚Å‚ ‚邪CŒŸõ‚ÉŒø‰Ê‚ª‚ ‚é’PŒê‚̓Rƒ“ƒsƒ…[ƒ^‚É“o˜^‚³‚ê‚Ä‚¢‚È‚¢Œê‚Å‚ ‚邱‚Æ‚ª‘½‚¢‚̂ŁC‚±‚ÌŽæ‚èo‚µ‘€ì‚͓‚¢D‚±‚̘_•¶‚Å‚Í”½•œ“x‚Æ‚¢‚¤“Œv—Ê‚É‚æ‚Á‚āCŒ¾Œê“Æ—§‚ɏî•ñŒŸõ‚ÉŒø‰Ê‚ª‚ ‚é’PŒê‚ª‘I•Ê‚Å‚«‚邱‚Æ‚ðŽ¦‚µCƒRƒ“ƒsƒ…[ƒ^‚É–¢’m‚Ì’PŒê‚Å‚ ‚Á‚Ä‚àCŒŸõ‚ÉŒø‰Ê‚ª‚ ‚è‚»‚¤‚È•¶Žš—ñ‚ªŽæ‚èo‚¹‚邱‚Æ‚ðŽ¦‚µ‚½D‚»‚µ‚āC‚»‚Ì•¶Žš—ñ‚¾‚¯‚ð‘I‚Ô‚±‚Æ‚É‚æ‚Á‚āCî•ñŒŸõ‚̐¸“x‚ªŒüã‚·‚邱‚Æ‚ðŽ¦‚µ‚½D

’˜ŽÒF•“c‘PsC”~‘º‹±Ži

 

Deciding Indexing Strings with Statistical Analysis

‹¤’˜@•½¬12”N8ŒŽ@NTICIR Workshop 3  Meeting CLIR, Proceeding, pp.79 -85, NTICIR Workshop 2002

’˜ŽÒF•“c‘PsC”~‘º‹±ŽiCŽR–{‰pŽq

 

Selecting the most highly correlated pairs within a large vocabulary@

’P’˜@•½¬14”N8ŒŽ@Proceedings of the workshop on SEMANET: building and using semantic networks, pp.94-100, SEMANET 2002

‘å‹K–Í‚ÈŒêœb‚Ì‘g‚Ì‚È‚©‚©‚çCoŒ»ƒpƒ^-ƒ“‚Ì‘ŠŠÖ‚ª‚‚¢‘g‚ð˜R‚ê‚È‚­“Á’è‚·‚éƒAƒ‹ƒSƒŠƒYƒ€‚ðŽ¦‚µ‚½D’ʏí‚Ì•û–@‚ł́C10”N•ª‚̐V•·‹LŽ–‚ð‘ΏۂɁC‚·‚ׂĂ̒PŒê‚̏oŒ»‚ÉŠÖ‚·‚é‘ŠŠÖŒW”‚ð‹‚ß‚é‚±‚Ƃ͓‚¢‚ªC‚»‚ê‚ð’ʏí‚̏¬Œ^‚̃Rƒ“ƒsƒ…[ƒ^‚ÅŽÀs‚Å‚«‚é•û–@‚ɂ‚¢‚ďq‚ׂ½D‚±‚̃Aƒ‹ƒSƒŠƒYƒ€‚ÌŽÀs‘¬“x‚́C‘ΏۂƂ·‚éŒêœb‚̗ʂɈˑ¶‚¹‚¸Cƒf[ƒ^—Ê‚¾‚¯‚Ɉˑ¶‚·‚éD‚»‚µ‚āCƒf[ƒ^—Ê‚ðN‚Æ‚·‚é‚ƁC‚»‚Ì•½‹Ï‚ÌŒvŽZ—Ê‚ÍN log(N)‚É”ä—á‚·‚é‚à‚Ì‚Æ‚È‚èC‘å‹K–͂ȃf[ƒ^‚É‚à“K—p‚Å‚«‚é‚à‚Ì‚Æ‚È‚Á‚Ä‚¢‚éD
’˜ŽÒF”~‘º‹±Ži

 

Very low dimensional latent semantic indexing for local query regions

‹¤’˜@•½¬15”N7ŒŽ  Sixth  International Workshop on Information Retrieval with Asian Languages, IRAL-2003@Proceedings of the  6th international workshop on information retrieval with Asian language@ (pp.84 -91), IRAL 2003, JAPAN(Hokakido)

î•ñŒŸõ‚Å‚ÍŽ¿–âŠg’£‚Æ‚¢‚¤•û–@‚ª‚ ‚èCŒŸõŒ‹‰Ê‚ðŽ¿–â•¶‚ɒljÁ‚·‚é‚Æ‚¢‚¤•û–@‚ŁCŒŸõ‚̐¸“x‚ð‚ ‚°‚é‚Æ‚¢‚¤Žè–@‚ª‚ ‚éD‚±‚ÌŽè–@‚É‚¨‚¢‚ẮCŽ¿–âŠg’£‚̃hƒLƒ…ƒƒ“ƒg‚É—ÞŽ—‚Ì‚à‚Ì‚ª‘½‚­‘¶Ý‚·‚é‚ƁCŒŸõŒ‹‰Ê‚ª•Î‚Á‚Ä‚µ‚Ü‚¤‚Æ‚¢‚¤–â‘肪‚ ‚éD‚±‚̘_•¶‚ł́CŽ¿–âŠg’£‚̃hƒLƒ…ƒƒ“ƒg‚̎听•ª•ªÍ‚ðs‚Á‚āC•Î‚è‚ð–hŽ~‚Å‚«‚éŽè–@‚ð’ñˆÄ‚µ‚Ä‚¢‚éD‚»‚µ‚āC’ñˆÄŽè–@‚ƈê”Ê‚ÌŽ¿–âŠg’£‚Æ”äŠr‚µ‚½D”~‘º‚Í‘å‹K–͂ȃR[ƒpƒX‚ɑ΂µ‚Ď听•ª•ªÍ‚ð—˜—p‚µ‚½î•ñŒŸõŒŸõ‚ÌŽè–@‚𕡐”Ž¦‚µCXu‚Í‚»‚ê‚ð‡”Ô‚ÉŽÀŒ»‚µCŒø‰Ê‚Ì‚ ‚éŽè–@‚ð“Á’肵‚½D

’˜ŽÒFXu YinghuiC”~‘º‹±Ži

 

Dynamic programming matching for large scale information retrieval

‹¤’˜@•½¬15”N7ŒŽ@Proceedings of the  6th international workshop on information retrieval with Asian language , pp.100-107, IRAL 2003, JAPAN(Hokakido)

‘å‹K–Í‚È•¶‘‚ð‘ΏۂÉDPƒ}ƒbƒ`ƒ“ƒO‚ŏî•ñŒŸõ‚ðs‚¤ƒAƒ‹ƒSƒŠƒYƒ€‚ðŽÀŒ»‚µCŒø‰Ê‚𑪒肵‚½D’ʏí‚ÌDPƒ}ƒbƒ`ƒ“ƒO‚ðî•ñŒŸõ‚ɉž—p‚·‚é‚ɂ́Cî•ñŒŸõ‚̐¸“x‚Ì–â‘è‚ƁCî•ñŒŸõ‚Ì‘¬“x‚Ì–â‘è‚Ì“ñ‚‚ª‚ ‚邪C‘OŽÒ‚ɂ‚¢‚ẮC‚·‚łɐæs‚·‚錤‹†‚ª‚ ‚Á‚½‚ªC‚±‚̘_•¶‚ł́CŒvŽZ‘¬“x‚Ì–â‘è‚ð‰ðŒˆ‚Å‚«‚邱‚Æ‚ðŽ¦‚µ‚½DŽÀÛ‚ɁC”•SƒƒKƒoƒCƒg‚̏î•ñ‚ðDPƒ}ƒbƒ`ƒ“ƒO‚ÅŒŸõ‚µ‚Ä‚àC10•b’ö“x‚ÅŒ‹‰Ê‚𓾂邱‚Æ‚ª‚Å‚«C‚±‚ê‚Ü‚Å‚Ì•û–@‚æ‚è‚à‚QŒ…’ö“x‚‘¬‰»‚Å‚«‚½D

’˜ŽÒFŽR–{‰pŽqCŠÝ“c³”ŽC ••À‰À‘¥C•“c‘PsC”~‘º‹±Ži

 

Japanese Multiword Extraction using SVM and Adaptation@@@

‹¤’˜@•½¬16”N7ŒŽ@LREC-2004(Lisbon, Poltugal)  Workshop on Methodologies and Evaluation of Multiword Units in Real-world ApplicationsCpp.1-4

’˜ŽÒFT. OgataCK. TeraoCK. Umemura

”½•œ“x‚Æ‚¢‚¤“Á’¥—Ê‚ð—p‚¢‚é‚ƁCƒL[ƒ[ƒh‚ƈӖ¡‚Ì‚È‚¢•¶Žš—ñ‚ª•ª—£‚Å‚«‚邱‚Ƃ𓝌v—ʂ̃vƒƒbƒg‚ÅŽ¦‚µCSupport Vector Machine‚Ì“ü—Í‚Æ‚µ‚Ä”½•œ“x‚ð—p‚¢‚邱‚Æ‚ÅŽ«‘‚ð—p‚¢‚È‚¢‚ŃL[ƒ[ƒh‚𒊏o‚·‚é•û–@‚ð•ñ‚µ‚½B

 

Related Word-pairs Extraction without Dictionaries    

‹¤’˜@•½¬16”N7ŒŽLREC-2004(Lisbon, Poltugal)Cpp.1309-1312

’˜ŽÒFEiko Yamamoto, Kyoji Umemura

‘OŒã‚É“¯‚¶‚悤‚È•¶Žš—ñ‚ª˜A‘±‚·‚é‚Æ‚¢‚¤ƒqƒ…[ƒŠƒXƒeƒBƒbƒNƒX‚ð‚‘¬‚ÉŽÀ‘•‚µC‚»‚ê‚É‚à‚Ƃ¢‚āC“¯‚¶‚悤‚ÉŽg‚í‚ê‚éŒêiŒê‹åj‚ðŽ«‘‚ð—p‚¢‚È‚¢‚Å“Á’è‚·‚é•û–@‚ð•ñ‚µ‚½B

 

A Unified Model Literal Mining and Link Analysis for Ranking Web Resources

‹¤’˜@@•½¬16”N8ŒŽ@@SIGIR 2004CEnglandCpp.546-547

’˜ŽÒFYinghui XuCKyoji Umemura

Webƒf[ƒ^‚ð‘ΏۂƂµ‚½î•ñŒŸõ‚É‚¨‚¢‚āCƒŠƒ“ƒN‚̉ðÍ‚ðs‚Á‚ÄŒŸõ‚̏•‚¯‚É‚·‚邱‚Æ‚ªs‚í‚ê‚Ä‚¢‚邪CƒŠƒ“ƒN‚ɂ‚¢‚āCî•ñ‚ð‹­

‰»‚·‚邽‚߂̃Šƒ“ƒN‚ƁC“ǂݐi‚߂邽‚߂̃Šƒ“ƒN‚𕶎šî•ñ‚̃}ƒbƒ`ƒ“ƒO“x‡‚¢‚É‚æ‚Á‚Đ„’肵C•Ê‚̃Šƒ“ƒN‰ðÍ‚ðs‚¤‚±‚Æ‚É‚æ‚Á‚āC

‹æ•Ê‚µ‚È‚¢‰ðÍ‚æ‚è‚àŒø‰Ê‚ª‚ ‚邱‚Æ‚ð•ñ‚µ‚½B

 

Web Searching Using Term  Entropy on Virtual Document and Query Independent Importance in  NTCIR-4 Web Task@@@

‹¤’˜@•½¬16”N9ŒŽ@@

NTCIR@2004 Workshop 4 MeetingCChinaCVol.1Cpp.1-8

’˜ŽÒFYinghui Xu, Kyoji Umemura

Webƒf[ƒ^‚ð‘ΏۂƂµ‚½î•ñŒŸõ‚É‚¨‚¢‚āCWebƒf[ƒ^‚ÍŒŸõ‚Ì’PˆÊ‚Æ‚µ‚Ă̓mƒCƒY‚Æ‚È‚éƒtƒB[ƒ‹ƒh‚ª‘½‚¢‚±‚Æ‚ðà–¾‚µCƒy[ƒW‚²‚Ƃɉ¼‘z•¶‘‚ðƒŠƒ“ƒNî•ñ‚ð‚à‚Ƃɍ쐬‚·‚µC‚»‚±‚ɑ΂µ‚ďî•ñŒŸõ‚ðs‚¤‚±‚Æ‚ÅŒø‰Ê‚ª‚ ‚邱‚Æ‚ð•ñ‚µ‚½B

 

Literal-Matching-Biased Link Analysis

‹¤’˜@•½¬16”N10ŒŽ@

AIRS, Asia Information Retrieval Symposium, October 18-20, 2004, Beijing, China, Proceeding, p91-97

’˜ŽÒFYinghui Xu, Kyoji Umemura

 

Query Expansion with the Minimum User Feedback by Transductive Learning

‹¤’˜@•½¬17”N10ŒŽ@HLT/EMNLP 2005CCanada @Human Language Technology Conference and Conference on Empirical Methods in Natural Language

Processing, pp.963-970

’˜ŽÒFMasayuki Okabe, Kyoji Umemura, Seiji Yamada

 

Substring statistics

‹¤’˜F10th Internal Conferece, Computational Linguistics and Intelligent Text Processing

53-71, March 2009, USA

’˜ŽÒFKyoji Umemura, Kenneth Church

 

Analysis of Anomalies on a Virtualized Network Testbed

‹¤’˜F•½¬22”N6ŒŽ29“ú-7ŒŽ1“ú, Bradford, West Yorkshire, UK

The 10th IEEE International Conference on Computer and Information Technology (CIT 2010)

IEEE Computer Society pp.297 - 304

’˜ŽÒFChunghan Lee, Hirotake Abe, Toshio Hirotsu, and Kyoji Umemura

 

A Light-weight Autonomous Power Saving Method for Wireless Sensor Networks

‹¤’˜FThe sixth International Conference on Autonomic and Autonomous Systems ICAS 2010, March 7-13, 2010 – Cancun, Mexico  http://www.iaria.org/conferences2010/ProgramICAS10.html

’˜ŽÒFToshio Hirotsu, Shinnosuke Nishitani, Hirotake Abe, Kyoji Umemura, Kensuke Fukuda

Satoshi Kurihara, Toshiharu Sugawara

 

A Light-weight Autonomous Power Saving Method for Wireless Sensor Networks

Toshio Hirotsu, Shinnosuke Nishitani, Hirotake Abe, Kyoji Umemura, Kensuke Fukuda

Satoshi Kurihara, Toshiharu Sugawara

ICSA 2010 APPLIED STATISTICS SYMPOSIUM
June 20-23, 2010, Downtown Indianapolis, IN , USA

 

Estimating Traffic anomaly Anomalies for Throughput Prediction on Network Virtualization

‹¤’˜FHSNCE2011 (collocated with IEEE/IPSJ SAINT2011)Ap.267-273, Munich, GERMANY, July 18-21

’˜ŽÒFChunghan Lee, Hirotake Abe, Toshio Hirotsu, and Kyoji Umemura

 

Predicting Network Throughput for Grid Applications on Network Virtualization Areas •\²

‹¤’˜FAssociation for Computing Machinery, Network-aware Data Management(NDMf11), pp.11 – 20, Seattle, Washington, USA, Nov 14, 2011

’˜ŽÒFChunghan Lee, Hirotake Abe, Toshio Hirotsu and Kyoji Umemura

 

A Statistical Approach for Selecting Throughput Prediction Parameters on the Internet@

‹¤’˜FThe 6th International Conference on Ubiquitous Information Technologies & Applications (CUTE 2011), pp.37-40, Seoul, KOREA, Dec. 15-17, 2011

’˜ŽÒFChunghan Lee, Hirotake Abe, Toshio Hirotsu and Kyojji Umemura

 

 

 

(‘“àŒû“ª”­•\)@2005”N“x‚æ‚è

 

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’˜ŽÒF¬—ÑŒ[ˆê˜YC‹à’J“ÖŽjC”~‘º‹±Ži

 

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‹¤’˜  “ú–{Šwp‰ïî•ñˆ—Šw‰ï‘ÛŠwp˜A‡C •½¬17”N3ŒŽ  pp.129-136C2005 “Œ‹ž

’˜ŽÒF‰ª•”³KC”~‘º‹±Ži@

 

Transductive ŠwK‚É‚æ‚éÅ¬•¶‘”»’è‚©‚ç‚̃NƒGƒŠŠg’£iQuery Expansion with the Minimum Judgmentj

‹¤’˜  •½¬17”N3ŒŽ  lH’m”\Šw‰ï‘S‘‘å‰ïi19‰ñj˜_•¶W, pp.1-4, JSAI 2005

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‹¤’˜@•½¬17”N5ŒŽ  î•ñˆ—Šw‰ïŒ¤‹†•ñ, Vol.2005, No.48, pp.99-104,  2005 5ŒŽ ‰«“ê

’˜ŽÒF¬’ˉë—m,@‰ª•”³K,@”~‘º‹±Ži

 

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’˜ŽÒF’·’¬Œ’‘¾, •“c‘Ps, ”~‘º‹±Ži

 

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’˜ŽÒFŽ½”¨q‘¾C”~‘º‹±Ži

 

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’˜ŽÒFŽá—Ñ—TŽkC”~‘º‹±Ži

 

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’˜ŽÒF‚£‹Å‰›, ”~‘º‹±Ži

 

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‹¤’˜@•½¬19”N7ŒŽ,î•ñˆ—Šw‰ïŒ¤‹†•ñA“¿“‡@pp.121-126

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‹¤’˜@•½¬19”N7ŒŽ,î•ñˆ—Šw‰ïŒ¤‹†•ñA“¿“‡@pp.145-149

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’˜ŽÒFácŠÔ@‰ëC”~‘º@‹±Ži

 

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’˜ŽÒFÜŒ´KŽ¡C“¡Œ´‘å•ãC”~‘º‹±Ži

 

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’˜ŽÒFˆ¢•”—mäC”~‘º‹±Ži

 

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’˜ŽÒF‹e’r@½Cˆ¢•”—mäC”~‘º‹±Ži

 

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’˜ŽÒF‰–“üŠ°”VC‰ª•”³KCˆ¢•”—mäC”~‘º‹±Ži

 

2Œê‚Ì‹¤’ÊŽü•Ó•¶Žš—ñ‚Ì’·‚³‚É’…–Ú‚µ‚½Œê•¶–¬—ÞŽ—”»’è

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’˜ŽÒFÜŒ´KŽ¡C”~‘º‹±Ži

 

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’˜ŽÒF“¡Œ´‘å•ãC‹e’r@½Cˆ¢•”—mäC‰ª•”³KC”~‘º‹±Ži

 

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’˜ŽÒF‰äÈ—TŽ÷Cˆ¢•”—mäC‰ª•”³KC”~‘º‹±Ži

 

‰¼‘zƒ†ƒrƒLƒ^ƒXƒZƒ“ƒT‚É‚¨‚¯‚鑪’è’l•âŠ®ƒVƒXƒeƒ€‚̃vƒƒgƒ^ƒCƒv\’z

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’˜ŽÒF‘å–x’B–çC‹e’r@½CâV“¡‹`•¶C‰äÈ—TŽ÷Cˆ¢•”—mäC‰ª•”³KC”~‘º‹±Ži

 

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’˜ŽÒFâV“¡‹`•¶Cˆ¢•” —mäC”~‘º ‹±Ži

 

‰¼‘zƒ†ƒrƒLƒ^ƒXƒZƒ“ƒT‚É‚¨‚¯‚鑪’è’l•âŠ®ƒVƒXƒeƒ€‚̃vƒƒgƒ^ƒCƒv\’z

‹¤’˜Fî•ñˆ—Šw‰ï71‰ñ‘S‘‘å‰ï3ZD-1iŽ ‰êŒ§‘’ÃŽsF2009”N3ŒŽ11“ú      000j pp.2-459-460

’˜ŽÒF‘å–x’B–çC‹e’r@½CâV“¡‹`•¶C‰äÈ—TŽ÷Cˆ¢•”—mäC‰ª•”³KC”~‘º‹±Ži

 

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‹¤’˜Fî•ñˆ—Šw‰ï71‰ñ‘S‘‘å‰ï3ZD-2iŽ ‰êŒ§‘’ÃŽsF2009”N3ŒŽ11“új pp.2-461-462

’˜ŽÒF‰äÈ —TŽ÷Cˆ¢•” —mäC‰ª•” ³KC”~‘º ‹±Ži

 

Compression-based Dissimilarity Measure (CDM)‚ð—p‚¢‚½lŠ´ƒZƒ“ƒTî•ñ‚Ì—ÞŽ—”»’è

‹¤’˜Fî•ñˆ—Šw‰ï71‰ñ‘S‘‘å‰ï3ZD-3iŽ ‰êŒ§‘’ÃŽsF2009”N3ŒŽ11“új@pp.2-463-464

’˜ŽÒF‹e’n ½Cˆ¢•” —mäC‰ª•” ³KC”~‘º ‹±Ži

 

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’˜ŽÒF“¡Œ´ ‘å•ãC‹e’n ½Cˆ¢•” —mäC‰ª•” ³KC”~‘º ‹±Ži

 

SYNƒpƒPƒbƒg‚̌ĉž‚É’…–Ú‚µ‚½P2Pƒgƒ‰ƒtƒBƒbƒN‚Ì•\Ž¦

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’˜ŽÒFŽO‰Y–¾“úA”~‘º‹±ŽiAˆ¢•”—mäA‰ª•”³K

 

ˆ³k‚ÉŠî‚­ŽÚ“xiCDMj‚ð—p‚¢‚½lŠ´ƒZƒ“ƒTî•ñ‚Ì—ÞŽ—”»’è

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’˜ŽÒF‹e’n ½Cˆ¢•” —mäC‰ª•” ³KC”~‘º ‹±Ži

 

ƒCƒ“ƒ^[ƒ†ƒrƒLƒ^ƒXƒlƒbƒgƒ[ƒNî•ñŠî”Õ‚Ì‚½‚߂̐lŠÔs“®ƒ}ƒCƒjƒ“ƒO

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’˜ŽÒFŒIŒ´@‘EÀ”ö³siã‘åjE•Ÿ“cŒ’‰îiNIIjEœA’ÓoŽu•v i–L‹´‹Z‰È‘åjE

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‘ÌŒ±î•ñ‚ÉŠÖ‚·‚錟õƒpƒ‰ƒ_ƒCƒ€‚ÌŽÀØŒ¤‹†

An Empirical Paradigm for Experimental Information Retrieval, in English

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’˜ŽÒFŒF’J–€”üŽqA”~‘º‹±Ži

 

Œê‚Ì•¶–¬‚̈ê’v”»’è‚É‚¨‚¯‚镶–¬‚̏oŒ»•p“x‚ÆŽí—ސ”‚Ì”äŠr

‹¤’˜Fî•ñˆ—Šw‰ïŒ¤‹†•ñA‹ž“s‘åŠw@2009”N9ŒŽAvol.2009.NL-193 No.8, pp.1-6

’˜ŽÒF‘ŽR“ÄŽuC”~‘º ‹±ŽiCˆ¢•” —mäC‰ª•” ³K

 

Evaluation of Network Throughput Predictability for Bulk Transfer

‹¤’˜F‘æ2‰ñGCOEŠw¶ŽåÃƒVƒ“ƒ|ƒWƒEƒ€@i–L‹´‹Zp‰ÈŠw‘åŠw@2009”N9ŒŽ4“új

’˜ŽÒFC.H.Lee, H. Abe, T. Hirotsu and K. Umemura

 

‰æ–ʃCƒ[ƒW‚©‚çŽæ‚èo‚µ‚½ƒeƒLƒXƒg‚ɑ΂·‚éî•ñŒŸõ‚̉ۑè

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’˜ŽÒFŒF’J–€”üŽqAˆ¢•” —mäC‰ª•” ³KC”~‘º ‹±Ži

 

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’˜ŽÒF”öã@“OA‰ª•”³sA”~‘º‹±ŽiAˆ¢•”—mä

 

‘o•ûŒü’ʐM‚É’…–Ú‚µ‚½ˆÃ†‰»P2Pƒgƒ‰ƒqƒbƒN‚̉ðÍŽè–@‚ÌŒŸ“¢

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’˜ŽÒF—é–؏«ŽjA”~‘º‹±ŽiAˆ¢•”—mäA‰ª•”³s

 

‰¼‘zƒ†ƒrƒLƒ^ƒXƒZƒ“ƒT‚ÌŽÀŒ»‚ÉŒü‚¯‚½‘½ƒ`ƒƒƒ“ƒlƒ‹ƒf[ƒ^Žû˜^ŠÂ‹«‚̐݌v‚ÆŽÀ‘•

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î•ñ—ʂ̍ő剻‚ÉŠî‚­ŽwŒü«ƒZƒ“ƒT‚Ì•ûŒü§Œä

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’˜ŽÒF‰äÈ—TŽ÷Aˆ¢•” —mäC‰ª•” ³KC”~‘º ‹±Ži

 

Compression-based Dissimilarity Measure (CDM)‚ð—p‚¢‚½lŠ´ƒZƒ“ƒTî•ñ‚Ì—ÞŽ—”»’è

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’˜ŽÒF‹e’n ½Cˆ¢•” —mäC‰ª•” ³KC”~‘º ‹±Ži

 

î•ñ—ʂ̍ő剻‚ÉŠî‚­ŽwŒü«ƒZƒ“ƒT‚Ì•ûŒü§Œä

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’˜ŽÒF‰äÈ—TŽ÷Aˆ¢•” —mäC‰ª•” ³KC”~‘º ‹±Ži

 

—אڒPŒê‚Å•\Œ»‚µ‚½•¶–¬‚É‚¨‚¯‚鍂•p“x•¶–¬‚ÌŒXŒü•ªÍ

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’˜ŽÒF”öã@“OA‰ª•”³sA”~‘º‹±ŽiAˆ¢•”—mä

 

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’˜ŽÒFŒF’J–€”üŽqA™‰Y—ɈêA‰ª•”³sA”~‘º‹±Ži

 

Characteristics of Internet Traffic Anomalies over a Virtualized Network Testbed

‹¤’˜FThe 7th Korea-Japan e-Science Symposium, Hongcheon, Korea July 2010

’˜ŽÒFChunghan Lee, Hirotake Abe, Toshio Hirotsu and Kyojji Umemura

 

ƒCƒ“ƒ^[ƒlƒbƒgã‚Å—\‘ª‰Â”\«‚ð‚‚ß‚é‚½‚߂̃Xƒ‹[ƒvƒbƒg‚Ì•]‰¿

Throughput Evaluation for Improving Predictability over the Internet

‹¤’˜FADST2010, –L‹´‹Zp‰ÈŠw‘åŠwƒOƒ[ƒoƒ‹COE, ‘æ3‰ñƒZƒ“ƒVƒ“ƒOƒA[ƒLƒeƒNƒgEƒVƒ“ƒ|ƒWƒEƒ€AB-16, p67i–¼ŒÃ‰®‘ÛƒZƒ“ƒ^[F2010”N10ŒŽ21“új

’˜ŽÒFChunghan Lee, Hirotake Abe, Toshio Hirotsu and Kyojji Umemura

 

A PCA Analysis for Traffic Anomaly Estimation

‹¤’˜FƒCƒ“ƒ^[ƒlƒbƒgƒRƒ“ƒtƒ@ƒŒƒ“ƒX2010A“ú–{ƒ\ƒtƒgƒEƒGƒAŠw‰ïi“Œ‹ž‘åŠw–퐶u“°@2010”N10ŒŽ25“ú-26“új, N0.66, p93-98

’˜ŽÒFChunghan Lee, Hirotake Abe, Toshio Hirotsu and Kyojji Umemura

 

Traffic Anomaly Analysis and Throughput Evaluation

‹¤’˜FInternal Symposium on Electronics-Inspired Interdisciplinary Research(EIIRIS), p92, Aichi, Japan, Nov. 2010

’˜ŽÒFChunghan Lee, Hirotake Abe, Toshio Hirotsu and Kyojji Umemura

 

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p.257-260@ˆ¤’m@–¼ŒÃ‰®

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Comparing Variety with Frequency on Judging the Correspondence of the Surrounding Contexts of Words and Evaluation Approach @§—ãÜ

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MapReduce‚ð—p‚¢‚½•ª•z—ÞŽ—“xŒvŽZ‚É‚æ‚éŠÖ˜AŒë”»’è

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’˜ŽÒFŒF’J–€”üŽqA™‰Y—ɈêA‰ª•”³KA”~‘º‹±Ži

 

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Internet Traffic Characteristics of Virtual Machine on Amazon EC2

‹¤’˜FIPSJ Technical report (SIGOS 117), 2011-OS-117, pp.1-7, Okinawa, Japan, April 2011

’˜ŽÒFChunghan Lee, Hirotake Abe, Toshio Hirotsu and Kyojji Umemura

 

Network Throughput Prediction using Support Vector Regression

‹¤’˜FApplication and Deepening of Intelligent Sensing Technology (ADIST 2011), TUT Campus, pp.40, Japan,October 14, 2011

’˜ŽÒFChunghan Lee, Hirotake Abe, Toshio Hirotsu and Kyojji Umemura

 

Recent Empirical Evaluation of Aggregate THrouput using Parallel Transfers on the Internet

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’˜ŽÒFChunghan Lee, Hirotake Abe, Toshio Hirotsu and Kyojji Umemura

 

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’˜ŽÒF™‰Y—ɈêA‰ª•”³KA”~‘º‹±Ži

 

Appropriate Parameter Selection for Predicting Network Throughput on the Internet

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’˜ŽÒFChunghan Lee, Hirotake Abe, Toshio Hirotsu and Kyojji Umemura

 

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’˜ŽÒFŠFì@•àA‰ª•”³KA”~‘º‹±Ži

 

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