Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Fast Succinct Trie
Search
Shunsuke Kanda
August 06, 2019
Research
2
750
Fast Succinct Trie
第七回StringBeginnersでの発表資料です。
Shunsuke Kanda
August 06, 2019
Tweet
Share
More Decks by Shunsuke Kanda
See All by Shunsuke Kanda
Leveraging LLMs for Unsupervised Dense Retriever Ranking (SIGIR 2024)
kampersanda
3
420
Lucene/Elasticsearch の Character Filter でユニコード正規化するとトークンのオフセットがズレるバグへの Workaround - Search Engineering Tech Talk 2024 Spring
kampersanda
0
1.5k
Binary and Scalar Embedding Quantization for Significantly Faster & Cheaper Retrieval
kampersanda
3
460
トライとダブル配列の基礎
kampersanda
2
1.7k
Binary search with modern processors
kampersanda
34
14k
AIP Open Seminar #6
kampersanda
0
270
ICDM2020
kampersanda
0
240
SIGSPATIAL20
kampersanda
0
230
EliasFano
kampersanda
1
270
Other Decks in Research
See All in Research
Language Models Are Implicitly Continuous
eumesy
PRO
0
370
ForestCast: Forecasting Deforestation Risk at Scale with Deep Learning
satai
2
250
自動運転におけるデータ駆動型AIに対する安全性の考え方 / Safety Engineering for Data-Driven AI in Autonomous Driving Systems
ishikawafyu
0
120
AIスーパーコンピュータにおけるLLM学習処理性能の計測と可観測性 / AI Supercomputer LLM Benchmarking and Observability
yuukit
1
500
[Devfest Incheon 2025] 모두를 위한 친절한 언어모델(LLM) 학습 가이드
beomi
2
1.4k
Akamaiのキャッシュ効率を支えるAdaptSizeについての論文を読んでみた
bootjp
1
400
大規模言語モデルにおけるData-Centric AIと合成データの活用 / Data-Centric AI and Synthetic Data in Large Language Models
tsurubee
1
470
Open Gateway 5GC利用への期待と不安
stellarcraft
2
170
J-RAGBench: 日本語RAGにおける Generator評価ベンチマークの構築
koki_itai
0
1.2k
Community Driveプロジェクト(CDPJ)の中間報告
smartfukushilab1
0
130
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing
satai
3
360
空間音響処理における物理法則に基づく機械学習
skoyamalab
0
170
Featured
See All Featured
[RailsConf 2023] Rails as a piece of cake
palkan
58
6.2k
Hiding What from Whom? A Critical Review of the History of Programming languages for Music
tomoyanonymous
1
360
Digital Ethics as a Driver of Design Innovation
axbom
PRO
0
140
The Art of Programming - Codeland 2020
erikaheidi
57
14k
How to Create Impact in a Changing Tech Landscape [PerfNow 2023]
tammyeverts
55
3.2k
Why Mistakes Are the Best Teachers: Turning Failure into a Pathway for Growth
auna
0
43
Technical Leadership for Architectural Decision Making
baasie
0
220
Design and Strategy: How to Deal with People Who Don’t "Get" Design
morganepeng
133
19k
Winning Ecommerce Organic Search in an AI Era - #searchnstuff2025
aleyda
0
1.8k
The Pragmatic Product Professional
lauravandoore
37
7.1k
Ruling the World: When Life Gets Gamed
codingconduct
0
120
Building AI with AI
inesmontani
PRO
1
630
Transcript
'BTU4VDDJODU5SJF @kampersanda 7th StringBeginners հจɿ ;IBOH -JN -FJT "OEFSTFO ,BNJOTLZ
,FFUPOBOE1BWMP 4V3'1SBDUJDBM3BOHF2VFSZ'JMUFSJOHXJUI'BTU4VDDJODU5SJF *O4*(.0% QQ
'BTU4VDDJODU5SJF '45 w ͷ4*(.0%ͰఏҊ͞Εͨ؆ܿ5SJFදݱ ;IBOHFUBM4V3'1SBDUJDBMSBOHFRVFSZpMUFSJOHXJUI GBTUTVDDJODUUSJFT4*(.0% 4VDDJODU3BOHF'JMUFS
4V3' ͷͨΊʹఏҊ͞Εͨ Ұൠతͳ༻్ʹ͑Δ w ࠓճͷൃද4V3'Ͱͳ͘'45ʹযΛͯͨͷͰ͢ w ͪͳΈʹ ච಄ஶऀ͞ΜʹΑΔΘ͔Γ͍͢εϥΠυ͕͏͢Ͱʹ͋Γ·͢ ‣ IUUQXXXDTDNVFEVdIVBODIFTMJEFT'45QEG ࠓճͷ୯७ʹͦΕΛͳͧͬͨͷͰͳ͍Ͱ͢ 2
5SJFࣙॻ w 5SJFͱҰݴͰݴͬͯɺٻΊΒΕΔૢ࡞͍Ζ͍Ζ w ࠓճ؆୯ʹҎԼͷΑ͏ͳૢ࡞͕Ͱ͖ΕΑ͠ͱ͠·͢ .FNCFS 4 ɿจࣈྻ4͕Ωʔͱؚͯ͠·Ε͍ͯΔ͔ʁ
1SFpY 4 ɿจࣈྻ4ͷ಄ࣙͱ࠷Ұக͢ΔΩʔʁ 3 .FNCFS Θͨ͠ :FT .FNCFS Θͨ͘͠ /P 1SFpY Θͨ͘͠ Θͨ ͨ Θ ʹ ͠ Έ ͨ Θ ͠
ͦͦ؆ܿ5SJFͬͯԿʁ 'BTU4VDDJODU5SJF '45 ͱʁ 5SJFࣙॻͱͯ͠ͷ'45ͷੑೳʁ
ͦͦ؆ܿ5SJFͬͯԿʁ 'BTU4VDDJODU5SJF '45 ͱʁ 5SJFࣙॻͱͯ͠ͷ'45ͷੑೳʁ
؆ܿ5SJFͱʁ w ใཧతԼݶʹ͍ۙϝϞϦྔͰ5SJFΛදݱ͢Δσʔλߏ OMHМ 0 O Ϗοτ ‣ OઅɺМΞϧϑΝϕοταΠζ
w ʮॱংͷ؆ܿදݱʯ ʮϥϕϧͷྻʯͰΑ͘දݱ͞ΕΔ w ̏ͭͷදతͳॱংͷ؆ܿσʔλߏ #1 #BMBODFE1BSFOUIFTFT %'6%4 %FQUI'JSTU6OBSZ%FHSFF4FRVFODF -06%4 -FWFM0SEFSFE6OBSZ%FHSFF4FRVFODF w ͪͳΈʹɺ 9#8N#POTBJͳͲ؆ܿ5SJFͰ͕͢ࠓճѻΘͳ͍Ͱ͢ 6 O P O CJUT OMPHМCJUT
#1 #BMBODFE1BSFOUIFTFT w ֤અΛ։ׅހ(ͱดׅހ)ͷϖΞͰදݱ ਂ͞༏ઌॱͰΛࠪ ߦ͖ͷ๚Ͱ(Λஔ͖ɺؼΓͷ๚Ͱ)Λஔ͘ 7
'JSTU$IJME QPT QPT /FYU4JCMJOH QPT 'JOE$MPTF QPT ( ( ( ) ( ( ) ( ) ) ) ( ( ( ) ) ) ) 'JOE$MPTFɿରԠ͢ΔดׅހͷҐஔ
%'6%4 %FQUI'JSTU6OBSZ%FHSFF4FRVFODF w #1ΑΓଟػೳͳׅހྻදݱ ਂ͞༏ઌॱͰΛࠪ ֤અʹ͍ͭͯɺͦͷࢠͱಉ͡ͷ(ͱ̍ݸͷ)Λஔ͘ ࠷ޙʹઌ಄ʹ(Λஔ͘
8 ( ( ( ) ( ( ) ) ( ( ) ) ) ( ) ( ) ) $IJME QPT J 'JOE$MPTF 4FMFDU) 3BOL) QPT J 3BOLb QPT ɿQPT·Ͱͷbͷ 4FMFDUb L ɿL൪ͷb͕ݱΕΔҐஔ 'JOE$MPTF
-06%4 -FWFM0SEFSFE6OBSZ%FHSFF4FRVFODF w ͜ͷੈͰͬͱγϯϓϧͳදݱʢྑ͍ҙຯͰʣ ෯༏ઌॱʹΛࠪ ֤અʹ͍ͭͯɺͦͷࢠͱಉ͡ͷ1ͱ̍ݸͷ0Λஔ͘ ࠷ޙʹઌ಄ʹ10Λஔ͘
9 1 0 1 1 0 1 1 0 1 0 0 1 1 0 1 0 0 0 0 'JSTU$IJME QPT 4FMFDU0 3BOL1 1PT /FYU4JCMJOH QPT QPT 3BOLb QPT ɿQPT·Ͱͷbͷ 4FMFDUb L ɿL൪ͷb͕ݱΕΔҐஔ 'JSTU$IJME
؆ܿ5SJFͷϨϏϡʔ 10 ػೳੑ ݕࡧ ࣮ #1 ̋ ˚ %'6%4
˕ ̋ -06%4 ˚ ˕ қ w Ұൠతʹɺࣙॻͱͯ͠ͷ5SJF಄ࣙݕࡧ͕Ͱ͖Εे w #1ͱ%'6%4Ϧον͗͢ΔͷͰ-06%4͕࠾༻͞ΕΔέʔε͕ଟ͍ 59ɺ69ɺ."3*4"ɺ'45ɺͳͲ w ͦͷลΓͷൺֱ࣮ݧ "SSPZVFMPFUBM4VDDJODUUSFFTJOQSBDUJDF"-&/&9 ాΒॱংͷ؆ܿදݱΛ༻͍ͨτϥΠࣙॻͷධՁॲશࠃ ࠓͱͳͬͯ ͦ͜·Ͱ͡Όͳ͍
ͦͦ؆ܿ5SJFͬͯԿʁ 'BTU4VDDJODU5SJF '45 ͱʁ 5SJFࣙॻͱͯ͠ͷ'45ͷੑೳʁ
ઃܭͷϞνϕʔγϣϯ w ࠜͷۙͷઅͱ༿ͷۙͷઅͰੑׂ࣭͕ҧ͏ 12 w ͪͳΈʹɺͦͷΑ͏ͳϞνϕʔγϣϯ౷తʹ͋Γ·͢ "35ɿઅͷ࣍ʹΑΓదͳσʔλߏΛબ #VSTU5SJF)"5ɿࠜۙͷઅΛ୯७ͳྻͰදݱ
."3*4"ɿࠜͷۙͷ3BOL4FMFDUͷԋࢉ݁ՌΛΩϟογϡ ૄ සൟʹΞΫηε͞ΕΔ େଟͷઅ͕ଐ͢Δ ͕େࣄʂ ϝϞϦޮ͕େࣄʂ ͨ Θ ʹ ͠ Έ ͨ Θ ͠ ີ
-06%4%4ɿೋछྨͷ-06%4Ͱදݱ 13 ਤจΑΓҾ༻ w ࠜۙߴͳ-06%4%FOTF w ༿ۙϝϞϦޮͷྑ͍-06%44QBSTF
-06%4%FOTF 14 - )$ ͨ Θ ʹ ͠ Έ ͨ
Θ ͠ - )$ ͨ Θ Θ ͨ ʹ - )$ ͠ ͠ Έ ˞ଟগɺ؆ུԽͯ͠·͢ w -ɿͦͷࢬϥϕϧΛ࣋ͭࢠ͕ଘࡏ͢Δ͔ʁ w )$ɿͦͷࢠ෦અ͔ʁ МޒेԻ w ֤෦અΛ͞Мͷ ϏοτϚοϓͰදݱ
-06%4%FOTF 15 - )$ ͨ Θ ʹ ͠ Έ ͨ
Θ ͠ - )$ ͨ Θ Θ ͨ ʹ - )$ ͠ ͠ Έ ॳظঢ়ଶɿQPT ʮΘͨ͠ʯͰݕࡧ ߋ৽ɿQPTQPT จࣈ ֬ೝɿ-<QPT>ͳΒࢠ͕ଘࡏ͠ɺ)$<QPT>ͳΒͦͷࢠ෦અ ભҠɿ$IJME1PT QPT Мº3BOL )$ QPT QPT М ˞ଟগɺ؆ུԽͯ͠·͢
-06%4%FOTF 16 ͨ Θ ʹ ͠ Έ ͨ Θ ͠
ͨ Θ Θ ͨ ʹ ͠ ͠ Έ QPT $IJME1PT ʮΘͨ͠ʯͰݕࡧ М ˞ଟগɺ؆ུԽͯ͠·͢ - )$ - )$ - )$ QPT ߋ৽ɿQPTQPT จࣈ ֬ೝɿ-<QPT>ͳΒࢠ͕ଘࡏ͠ɺ)$<QPT>ͳΒͦͷࢠ෦અ ભҠɿ$IJME1PT QPT Мº3BOL )$ QPT 3BOL )$ QPT
-06%4%FOTF 17 ͨ Θ ʹ ͠ Έ ͨ Θ ͠
ͨ Θ Θ ͨ ʹ ͠ ͠ Έ QPT $IJME1PT ʮΘͨ͠ʯͰݕࡧ М ˞ଟগɺ؆ུԽͯ͠·͢ - )$ - )$ - )$ QPT ߋ৽ɿQPTQPT จࣈ ֬ೝɿ-<QPT>ͳΒࢠ͕ଘࡏ͠ɺ)$<QPT>ͳΒͦͷࢠ෦અ ભҠɿ$IJME1PT QPT Мº3BOL )$ QPT 3BOL )$ QPT
-06%4%FOTF 18 ͨ Θ ʹ ͠ Έ ͨ Θ ͠
ͨ Θ Θ ͨ ʹ ͠ ͠ Έ QPT )$<QPT>ͳͷͰ༿ ʮΘͨ͠ʯͰݕࡧ М ˞ଟগɺ؆ུԽͯ͠·͢ - )$ - )$ - )$ QPT ߋ৽ɿQPTQPT จࣈ ֬ೝɿ-<QPT>ͳΒࢠ͕ଘࡏ͠ɺ)$<QPT>ͳΒͦͷࢠ෦અ ભҠɿ$IJME1PT QPT Мº3BOL )$ QPT
-06%44QBSTF 19 ͨ Θ
ʹ ͠ Έ ͨ Θ ͠ - ͨ Θ Θ ͨ ʹ ͠ ͠ Έ )$ 4 ˞ଟগɺ؆ུԽͯ͠·͢ w ݪཧతʹී௨ͷ-06%4ͱҰॹ w-ɿϥϕϧͷྻ w)$ɿͦͷઅ෦અ͔ʁ w4ɿͦͷઅஉ͔ʁʢݪཧతʹී௨ͷ-06%4ʣ
-06%44QBSTF 20 ʮΘͨ͠ʯͰݕࡧ
- ͨ Θ Θ ͨ ʹ ͠ ͠ Έ )$ 4 ୳ࡧɿQPT -<QPT>จࣈ ͳQPT ֬ೝɿ)$<QPT>ͳΒͦͷࢠ෦અ ભҠɿ$IJME1PT QPT 4FMFDU 4 3BOL )$ QPT ˞ଟগɺ؆ུԽͯ͠·͢ ॳظঢ়ଶɿQPT QPT ͨ Θ ʹ ͠ Έ ͨ Θ ͠
-06%44QBSTF 21 ʮΘͨ͠ʯͰݕࡧ
- ͨ Θ Θ ͨ ʹ ͠ ͠ Έ )$ 4 ˞ଟগɺ؆ུԽͯ͠·͢ QPT $IJME1PT QPT ୳ࡧɿQPT -<QPT>จࣈ ͳQPT ֬ೝɿ)$<QPT>ͳΒͦͷࢠ෦અ ભҠɿ$IJME1PT QPT 4FMFDU 4 3BOL )$ QPT ͨ Θ ʹ ͠ Έ ͨ Θ ͠ 3BOL )$ QPT 4FMFDU 4
ͨ Θ ʹ ͠
Έ ͨ Θ ͠ -06%44QBSTF 22 ʮΘͨ͠ʯͰݕࡧ - ͨ Θ Θ ͨ ʹ ͠ ͠ Έ )$ 4 ˞ଟগɺ؆ུԽͯ͠·͢ QPT $IJME1PT ୳ࡧɿQPT -<QPT>จࣈ ͳQPT ֬ೝɿ)$<QPT>ͳΒͦͷࢠ෦અ ભҠɿ$IJME1PT QPT 4FMFDU 4 3BOL )$ QPT 3BOL )$ QPT 4FMFDU 4
-06%44QBSTF 23 ʮΘͨ͠ʯͰݕࡧ
- ͨ Θ Θ ͨ ʹ ͠ ͠ Έ )$ 4 ˞ଟগɺ؆ུԽͯ͠·͢ QPT )$<QPT>ͳͷͰ༿ ୳ࡧɿQPT -<QPT>จࣈ ͳQPT ֬ೝɿ)$<QPT>ͳΒͦͷࢠ෦અ ભҠɿ$IJME1PT QPT 4FMFDU 4 3BOL )$ QPT ͨ Θ ʹ ͠ Έ ͨ Θ ͠
'45ͷͦͷଞͷ w -06%4%FOTF4QBSTFͦΕͧΕʹదͳ3BOLࣙॻͷઃܭ w 4*.%ʹΑΔϥϕϧ୳ࡧͷߴԽ w ϓϦϑΣον໋ྩͷ׆༻ 24 ਤจΑΓҾ༻
ͦͦ؆ܿ5SJFͬͯԿʁ 'BTU4VDDJODU5SJF '45 ͱʁ 5SJFࣙॻͱͯ͠ͷ'45ͷੑೳʁ
'45ͷԠ༻ɿ3BOHF2VFSZ'JMUFSJOH w '453BOHF2VFSZ'JMUFSJOHͷҝͷσʔλߏͱͯ͠ఏҊ͞Εͨ 26 * $ % . & .
- ɿ*$"-1͔Β*$%.ͷؒʹؚ·ΕΔσʔλ͋Δʁ ղɿ:&4ʢ*$%&ͱ*$%.ʣ ɿ*$"-1͔Β*$%.ͷؒʹؚ·ΕΔσʔλʁ ղɿͭʢ*$%&ͱ*$%.ʣ w 4V3' 4VDDJODU3BOHF'JMUFS Ͱ'45ͷར༻ʹՃ͑ɺϢχʔΫͳ ඌࣙΛΓޡݕग़Λڐ͢͜ͱͰɺ#MPPN'JMUFSʹඖఢ͢ΔϝϞϦ༻ྔ Ͱ3BOHF2VFSZ'JMUFSJOHΛ࣮ݱ͢Δ
'45ͷੑೳʢจΑΓҾ༻ʣ w طଘͷ؆ܿ5SJFࣙॻͱൺͯ 27 ϏοτΛόΠτจࣈྻͱͯ͠ ϗετ໊Λͻͬ͘Γฦͯ͠ FH DPNHPPMHF!LBOEB UYUSJFγϯϓϧͳ-06%4 1%5ܦ࿏ղ
%'6%4
'45ͷੑೳʢจΑΓҾ༻ʣ w CJUJOUͰ-06%4%FOTFͷߩݙ͕େ͖͍ Ұ༷Ͱੜ͞Εͨσʔλ ͳͷͰ֤અͷࢠͷ͕ͱͯେ͖͍ 28 CBTFMJOF-06%44QBSTFͷΈ w
5SJFࣙॻͱͯͪ͠ΐͬͱಛघͳσʔληοτʁ w ࣗવݴޠͳͲσʔληοτͰͷੑೳͲ͏ͳͷʁ
5SJFࣙॻɺ࣮͠·ͨ͠ 29 w IUUQTHJUIVCDPNLBNQFSTBOEBGBTU@TVDDJODU@USJF
.FNPSZ6TBHF .J# '45 %"354$ 9$%"5
59 ."3*4" 1%5 4FBSDI5JNF NJDSPTFDRVFSZ '45 %"354$ 9$%"5 59 ."3*4" 1%5 .FNPSZ6TBHF .J# '45 %"354$ 9$%"5 59 ."3*4" 1%5 4FBSDI5JNF NJDSPTFDRVFSZ '45 %"354$ 9$%"5 59 ."3*4" 1%5 30 ࣮ݧʢຊޠʣ ϝϞϦ ݕࡧ *1"ࣙॻ .TUSJOHT BWFMFOHUI 8JLJλΠτϧ .TUSJOHT BWFMFOHUI
31 ࣮ݧʢ"TLJUJT`TEBUBTFUʣ .FNPSZ6TBHF .J# '45
%"354$ 9$%"5 59 ."3*4" 1%5 4FBSDI5JNF NJDSPTFDRVFSZ '45 %"354$ 9$%"5 59 ."3*4" 1%5 ϝϞϦ ݕࡧ %JTUJODU .TUSJOHT BWFMFOHUI 6SM .TUSJOHT BWFMFOHUI .FNPSZ6TBHF .J# '45 %"354$ 9$%"5 59 ."3*4" 1%5 4FBSDI5JNF NJDSPTFDRVFSZ '45 %"354$ 9$%"5 59 ."3*4" 1%5
·ͱΊ w '45γϯϓϧͳ-06%4ͳվྑ w σʔλ͔ΒΔΑ͏ͳઅͷࢠͷ͕ͱͯଟ͍5SJFʹ ରͯ͠ɺ-06%4%FOTFͷߩݙ͕ͱͯେ͖͍ 3BOHFRVFSZpMUFSJOHͷͨΊͷσʔλߏͱͯ͠Α͍ w ҰํͰɺࣗવݴޠσʔλͳͲͰطଘͷ5SJFࣙॻͷํ͕ޮ͕
ྑͦ͞͏ ͔͠͠ͳ͕Βɺ-06%4%FOTFͱଞͷ5SJFࣙॻʢྫ͑ 1%5ͱ͔ʣΛΈ߹ΘͤΔͳͲͷํࡦߟ͑ΒΕͦ͏ 32