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γζϧϫʔυ͔Β૝‫͞ى‬ΕΔྉཧͷࡶֶΛ࿩͢ର࿩γεςϜ৽໊ ࿨໵†

ౢా ࿨޹†† ‫۝‬भ޻‫ۀ‬େֶେֶӃ ৘ใ޻ֶ෎ ઌ୺৘ใ޻ֶઐ߈ ˟ 820-8052 ෱Ԭ‫ݝ‬൧௩ࢢ઒௡ 680-4
E-mail: †{k_niina,shimada}@pluto.ai.kyutech.ac.jp͋Β·͠ ΧʔφϏͷ༷ʑͳ‫ػ‬ೳͷ 1 ͭʹҿ৯ళ‫͕͋ࡧݕ‬Δɽ‫ࡏݱ‬ͷҿ৯ళ‫ࡧݕ‬͸ɼϢʔβ͕۩ମతͳྉཧ໊Λ༩͑Δ͜ͱΛલఏͱ͍ͯ͠Δɽ͔͠͠ɼϢʔβ͸ʮ͋ͬ͞Γͨ͠΋ͷ͕৯΂͍ͨʯͷΑ͏ͳந৅తͳ৘ใͷΈͷཁ‫ٻ‬Λසൟʹߦ͏Մೳੑ͕͋Γɼ‫ࡏݱ‬ͷΧʔφϏͰ͸͜ͷཁ‫ʹٻ‬ରԠͰ͖ͳ͍ɽຊ‫Ͱڀݚ‬͸ɼ͜ͷ໰୊ͷղܾࡦͱͯ͠ɼ৯΂෺ͷඒຯ͠͞ͳͲΛද͢ʮγζϧϫʔυʯʹண໨͠ɼγζϧϫʔυ͔Β૝‫͞ى‬ΕΔྉཧ໊ͷ֫ಘΛߦ͏ɽ·ͨɼۙ೥ΧʔφϏͷΑ͏ͳλεΫࢦ޲‫ࡶͱܕ‬ஊର࿩γεςϜͷΑ͏ͳඇλεΫࢦ޲‫ܕ‬Λ૊Έ߹Θͤͯɼຬ଍౓ͷ޲্ΛਤΔಈ
͖͕͋Δɽ͔͠͠ɼඇλεΫࢦ޲‫ؔ͢ʹܕ‬Δ‫Ͱڀݚ‬੒ՌΛ͍͋͛ͯΔख๏Ͱ͸ɼ൚༻తͳจΛੜ੒͠΍͍ͨ͢ΊɼϢʔβ͕ର࿩ʹ๞͖Δ‫ݥة‬ੑ͕͋Δɽຊ‫Ͱڀݚ‬͸ɼϢʔβΛָ͠·ͤΔཁૉͱͯ͠ࡶֶʹ஫໨͠ɼWeb ϖʔδ͔ΒࡶֶΛ‫ؚ‬Ήจͷநग़Λߦ͏ɽ͞ΒʹɼఏҊ͢Δ 2 ͭͷख๏Λ૊Έ߹Θͤͨࡶஊର࿩γεςϜͷߏஙΛߦ͏ɽΩʔϫʔυ γζϧϫʔυɼࡶֶɼࡶஊɼର࿩γεςϜA Dialogue System with Miscellaneous Knowledge from Sizzle Words
Kazuya NIINA† and Kazutaka SHIMADA†† Graduate School of Computer Science and System Engineering, Kyushu Institute of Technology
680-4, Kawazu, Iizuka, Fukuoka, 820-8502 Japan
E-mail: †{k_niina,shimada}@pluto.ai.kyutech.ac.jp
Abstract One of car navigation system’s functions is restaurant search. The current restaurant search is based on
the premise that a user gives it a cooking name. However, a user tends to give abstract information to the system.
In this paper, we focus on sizzle words, and acquire cooking names from sizzle words. Also, there is a movement to
combine task-oriented dialogue system and non-task-oriented dialogue system. Methods on recent non-task-oriented
researches, such as Sequence-to-Sequence models, tend to generate generic responses. We extract a miscellaneous
knowlede sentence from the Web, and create a dialogue system with miscellaneous knowledge from sizzle words.
Key words Sizzle Word, Miscellaneous Knowledge, Chat, Dialogue Systemͱ͸े෼ʹߟ͑ΒΕΔɽ‫ࡏݱ‬ͷΧʔφϏͰ͸ɼ͜ͷΑ͏ͳൃ࿩

1. · ͑ ͕ ͖ʹରͯ͠ద੾ʹରԠͰ͖ͳ͍ɽຊ‫Ͱڀݚ‬͸ɼ͜ͷ໰୊΁ͷରԠର࿩γεςϜͷҰͭʹɼΧʔφϏήʔγϣϯγεςϜʢΧʔࡦͱͯ͠ɼʮγζϧϫʔυʯʹண໨͢Δɽγζϧϫʔυͱ͸৯φϏʣ͕͋ΔɽΧʔφϏ͸ɼҿ৯ళ‫ࡧݕ‬΍໨త஍·Ͱͷ‫ܦ‬࿏‫ݕ‬΂෺ͷඒຯ͠͞ͳͲΛද‫͢ݱ‬Δ୯‫ޠ‬ͷ͜ͱͰɼʮ͋ͬ͞ΓʯͳࡧͳͲɼϢʔβͷ༷ʑͳཁ‫ʹٻ‬౴͑Δඞཁ͕͋Δɽ͜ͷΑ͏ͳͲ͕֘౰͢Δɽ͜ͷγζϧϫʔυ͸ྉཧϨγϐͷλΠτϧ໊ͳϢʔβ͔Βཁ‫͞ٻ‬ΕͨλεΫΛ਱ߦ͢Δର࿩γεςϜ͸λεΫ

Ͳʹ࢖ΘΕΔ͜ͱ͕͋ΔͨΊɼྉཧϨγϐ͔Βγζϧϫʔυͱࢦ޲‫ݺͱܕ‬͹Ε͓ͯΓɼۙ೥Ͱ͸ Partially Observable Markov

ؔ܎͋Δྉཧ໊͕֫ಘͰ͖Δͱߟ͑ΒΕΔɽΑͬͯɼຊ‫Ͱڀݚ‬

Decision Process (POMDP) Λ༻͍ͨ‫[ ڀݚ‬1] ΍ End-to-End

͸ Web ϖʔδ͔Β֫ಘͨ͠Ϩγϐʹ‫͖ͮج‬ɼγζϧϫʔυ͔Λ༻͍ͨ‫[ ڀݚ‬2] ͕ߦΘΕ͍ͯΔɽ͜ΕΒͷ‫ڀݚ‬΍‫ࡏݱ‬ͷΧʔΒ૝‫͞ى‬ΕΔྉཧ໊Λ֫ಘ͢Δख๏ΛఏҊ͢ΔɽφϏͰ͸ɼϢʔβ͕۩ମతͳ৘ใΛ༩͑Δ͜ͱΛલఏͱ͍ͯ͠

·ͨɼۙ೥Ͱ͸λεΫࢦ޲‫ܕ‬ͷର࿩γεςϜͱɼࡶஊର࿩γΔͨΊɼσʔλϕʔε΋ͦΕʹԊͬͯߏங͞Ε͍ͯΔɽ͔͠͠ɼ

εςϜΛ୅දͱ͢ΔඇλεΫࢦ޲‫ܕ‬ͷର࿩γεςϜΛ૊Έ߹ΘϢʔβ͸ඞͣ͠΋۩ମతͳ৘ใΛ༩͑Δͱ͸‫ݶ‬Βͳ͍ɽྫ͑

ͤΔ͜ͱͰɼϢʔβͷຬ଍౓ͳͲͷ޲্ΛਤΔಈ͖͕‫ݟ‬ΒΕ͹ɼΧʔφϏʹରͯ͠Ϣʔβ͕ҿ৯ళ‫ࡧݕ‬Λͯ͠΄͍͠ͱࢥͬ

ΔɽΧʔφϏʹ͍ͭͯ΋ɼࡶஊର࿩‫ػ‬ೳΛ௥Ճ͢Δ͜ͱͰɼ‫ډ‬ͨ࣌ɼʮ͋ͬ͞Γͨ͠΋ͷ͕৯΂͍ͨʯͷΑ͏ͳൃ࿩Λ͢Δ͜຾Γӡసͷ๷ࢭͳͲ༷ʑͳ఺ʹߩ‫͖Ͱݙ‬Δͱߟ͑ΒΕΔɽඇλ- 77 -—1—

This article is a technical report without peer review, and its polished and/or extended version may be published elsewhere.

Copyright ©2017 by IEICEεΫࢦ޲‫ܕ‬ͷର࿩γεςϜʹ͓͍ͯɼۙ೥Ͱ͸ Sequence-to-ද1γζϧϫʔυʮϐϦਏʯͱࡐྉͱͷ T F IDF ͷҰྫ

Sequence (Seq2Seq) ϞσϧΛ༻͍ͨख๏͕Ұఆͷ੒ՌΛ‫͛ڍ‬ࡐྉ໊

T F IDF ͷ஋͍ͯΔ [3] [4]ɽ͔͠͠ɼ͜ͷϞσϧ͸൚༻తͳจʢ
ʮ͸͍ʯ΍ʮͦ

XO ে

4.84418708645859

͖͋ͭ͞
..
.

4.15103990589865..
.

͏Ͱ͢ͶʯͳͲɼจ຺ʹґଘͤͣ࢖༻Ͱ͖ΔจʣΛੜ੒͠΍͍͢܏޲͕͋ΔͨΊɼϢʔβ͕ର࿩ʹ๞͖ͯ͠·͏‫ݥة‬ੑ͕͋Δɽද2ϢʔβΛର࿩ʹ๞͖ͤ͞ͳ͍ͨΊʹ͸ɼϢʔβΛָ͠·ͤΔจΛੜ੒ͯ͠ର࿩ʹҾ͖ࠐΉඞཁ͕͋ΔɽΑͬͯɼຊ‫Ͱڀݚ‬͸ࡶֶΛ‫ؚ‬Μͩจʢࡶֶจʣ͕ϢʔβΛָ͠·ͤΔจͰ͋Δͱͯ͠ɼ·ͨɼຊ‫ڀݚ‬͸ΧʔφϏΛ૝ఆ͍ͯ͠ΔͨΊɼఏҊ͢Δ 2 ͭζϧϫʔυΛ‫ؚ‬ΉೖྗจΛड͚औͬͨ࣌ɼͦͷγζϧϫʔυ͔Β૝‫͞ى‬ΕΔྉཧͷࡶֶจΛग़ྗ͢Δର࿩γεςϜΛߏங͢Δɽ

2. ؔ ࿈ ‫ڀ ݚ‬

ࡐྉ໊

T F IDF ͷ஋

XO ে

4.57471097850338

͓Ζ͠ʹΜʹ͘ 6.26941298614615
..
..
.
.

Wikipediaʢ஫ 1ʣ͔ΒࡶֶจΛ֫ಘ͢Δख๏ΛఏҊ͢Δɽͷख๏Λ૊Έ߹Θͤͨର࿩γεςϜΛߏங͢ΔɽϢʔβ͔Βγྉཧ໊ʮຑം՘ࢠʯͱࡐྉͱͷ T F IDF ͷҰྫϦʔϛʔͰτϩτϩͳΧϨʔ͏ͲΜͷ࡞ΓํʯͷΑ͏ʹɼγζϧϫʔυͱྉཧ໊Λ‫ؚ‬Ή΋ͷ͕ଘࡏ͢ΔɽΑͬͯɼγζϧϫʔυͱྉཧ໊ͷରԠؔ܎Λ֫ಘ͢Δ࠷΋୯७ͳํ๏͸ɼϨγϐλΠτϧʹ͓͚Δྉཧ໊ͱγζϧϫʔυͷ‫܎ؔىڞ‬Λ֫ಘ͢Δ
͜ͱͰ͋Δɽ͔͠͠ɼ͜ͷํ๏Ͱ͸γζϧϫʔυͱྉཧ໊ͷରԠؔ܎Λे෼ʹ֫ಘ͢Δ͜ͱ͸Ͱ͖ͳ͍ɽྫ͑͹ɼ‫ݩ‬ʑʮϔϧγζϧϫʔυʹؔ͢Δ‫ͯ͠ͱڀݚ‬ɼՃ౻Β [5] ͷ‫͕͋ڀݚ‬Δɽ
Ճ౻Β͸ɼ৯඼ʹର͢Δγζϧϫʔυͷ࢖ΘΕํ͕ϝσΟΞʹ
ΑͬͯҟͳΔͱͯ͠ɼTwitterʢ஫ 2ʣɼWeb ϖʔδɼྉཧϨγϐ౤ߘ Web αΠτ CookPadʢ஫ 3ʣ ͷ 3 ͭͷϝσΟΞʹ͓͚Δγζϧϫʔυͱ৯඼ͷؔ࿈ੑΛ෼ੳ͍ͯ͠Δɽγʔʯͳྉཧʢ
ʮαϥμʯͳͲʣʹରͯ͠ɼʮϔϧγʔͳʓʓʯͱ
໌ࣔతʹॻ͘͜ͱ͸গͳ͍ɽ·ͨɼຯ֮తͳཁૉΛࣔ͢γζϧϫʔυʢʮܹਏʯͳͲʣͰ΋ಉ༷ͷ܏޲͕ߟ͑ΒΕΔɽྫ͑͹ɼʮΩϜννήʯͷλΠτϧʹΘ͟Θ͟ʮܹਏʯͱॻ͘͜ͱ͸ඞͣ͠΋ଟ͘ͳ͍ɽ͕ͨͬͯ͠ɼϨγϐλΠτϧʹ͓͚Δ‫܎ؔىڞ‬ඇλεΫࢦ޲‫ܕ‬ͷର࿩γεςϜͷ‫Ͱڀݚ‬͸ɼҴ༿Β [8] ͕Twitter ͔Βͷࣗಈಠ࿩จੜ੒Λߦ͍ͬͯΔɽTwitter ͔Βಠ࿩จͱͯ͠ར༻Ͱ͖ΔπΠʔτΛநग़͠ɼҙ֎ੑɼϢʔϞΞੑɼτϐοΫʹ͓͚Δಛघੑͷ 3 ͭͷ‫͔఺؍‬ΒείΞΛ‫͠ࢉܭ‬ɼॱҐ͚ͮΛߦ͍ͬͯΔɽ·ͨɼߐ಄Β [9] ͸ɼWeb ্ͷχϡʔε‫ه‬ࣄͱ Wikipedia ͷ‫ࣄه‬Λ஌ࣝσʔλͱͯ͠ɼMarkov Decision

Process (MDP) Λ༻͍ͨର࿩γεςϜΛߏங͍ͯ͠ΔɽѫࡰҎ֎͔Βɼγζϧϫʔυͱྉཧ໊ͷରԠؔ܎Λ֫ಘ͢Δඞཁ͕
͋Δɽ͜͜Ͱɼઌ΄Ͳ‫͔ྫࣄͨ͛ڍ‬Βɼ۩ࡐͷಛੑ͕ͦͷྉཧͷγζϧϫʔυΛਪఆ͢Δͷʹ໾ཱͭͱ͍͏͜ͱ͕Θ͔Δɽྫ͑͹ɼΩϜν͕࢖ΘΕ͍ͯΔྉཧ͸গͳ͘ͱ΋ਏ͍ྉཧͰ͋ΔͨΊɼʮܹਏʯ΍ʮϐϦਏʯͱ͍ͬͨγζϧϫʔυΛਪఆ͢Δ͜
ͱ͕Ͱ͖ΔɽΑͬͯɼຊ‫Ͱڀݚ‬͸ྉཧͷ۩ࡐ͔Βɼγζϧϫʔυͱྉཧ໊ͷରԠؔ܎Λ֫ಘ͢Δɽ

΍࿩୊ఏࣔͳͲͷ֤Ԡ౴จੜ੒ϞδϡʔϧΛ࡞੒͠ɼMDP ʹΑΓ֫ಘͨ͠ର࿩ઓུΛ༻͍ͯର࿩Λߦ͍ͬͯΔɽ

·ͣɼྉཧ໊ΛΫΤϦͱͯ͠ɼCookPad ʹରͯ͠‫ࡧݕ‬Λߦ͍ɼྉཧͷϨγϐΛ֫ಘ͢Δɽ࣍ʹɼ֫ಘͨ͠Ϩγϐ͔Βࡐຊ ‫ Ͱ ڀ ݚ‬͸ ɼWikipedia Λ ஌ ࣝ ‫ ͍ ͯ ͍ ༻ ͯ ͠ ͱ ݯ‬Δ ɽ

Wikipedia ͔ΒγεςϜͷൃ࿩จΛநग़͢Δ‫ͯ͠ͱڀݚ‬ɼଠాΒ [6] ͷ‫͕͋ڀݚ‬ΔɽଠాΒ͸ɼҙ֎ੑͷ͋Δจ͸ର࿩Λ੝Γ্͛ΔจͰ͋Δͱͯ͠ɼWikipedia ͷ֤‫ࣄه‬ͷจʹରͯ͠ɼ

ྉ໊ͱγζϧϫʔυͷ‫܎ؔىڞ‬Λநग़͢Δɽ͜ͷ‫܎ؔىڞ‬Λར༻ͯ͠ɼ͋Δγζϧϫʔυ swi ʹର͢Δࡐྉ mj ͷ ॏཁ౓

T F IDF (swi , mj ) Λࣜ (1) Ͱ‫͢ࢉܭ‬Δɽ
T F IDF (swi , mj ) = tf (swi , mj ) × idf (mj )TF-IDFɼ୯‫ޠ‬ͷ‫ىڞ‬ස౓ɼจ௕ͷ 3 ͭͷࢦඪʹ‫͖ͮج‬είΞΛ‫͠ࢉܭ‬ɼϧʔϧΛຬͨ͢จʹ͸ϖφϧςΟΛ༩͑Δ͜ͱͰҙ֎ੑͷ͋Δจͷநग़Λߦ͍ͬͯΔɽ͔͠͠ɼ͜ͷख๏Ͱ͸ɼର࿩Λ੝Γ্͛Δͱ൑அ͞ΕͨจΛे෼ʹ֫ಘͰ͖͍ͯͳ͍ͨΊɼվળͷ༨஍͕‫ݟ‬ΒΕΔɽ·ͨɼਿຊΒ [7] ͸ɼWikipedia ͷ‫ه‬ࣄதͷจʹରͯ͠ɼࡶஊର࿩γεςϜʹར༻Ͱ͖ΔจͰ͋Δ͔Ͳ͏͔Λɼ‫ʹ಺ࣄه‬ஔ͚ΔҐஔ৘ใΛ༻͍ͯ෼ྨ͍ͯ͠Δɽจࣈ਺΍ಛఆ୯‫ޠ‬Λ༻͍ͨϑΟϧλϦϯάͳͲΛߦͬͨ‫ޙ‬ɼҐஔ৘ใʹ‫͍ͨͮج‬ಛ௃ྔΛ༻͍ͯ෼ྨΛߦ͍ͬͯΔɽ

(1)

ࣜ (1) ͷ tf (swi , mj ) ͸γζϧϫʔυ swi ʹର͢Δࡐྉ mj ͷ‫ىڞ‬ස౓ɼidf (mj ) ͸γζϧϫʔυΛ 1 จॻͱͨ࣌͠ͷ‫ٯ‬จॻස౓Ͱ͋Δɽಉ༷ʹྉཧ໊ͱࡐྉ໊ͷ‫܎ؔىڞ‬΋நग़Λߦ͍ɼ
͋Δྉཧ໊ ci ʹର͢Δࡐྉ mj ͷॏཁ౓ T F IDF (ci , mj ) Λ‫ܭ‬
ࢉ͢Δɽද 1 ʹɼγζϧϫʔυͱࡐྉͱͷ T F IDF ͷҰྫΛɼ
ද 2 ʹྉཧ໊ͱࡐྉͱͷ T F IDF ஋ͷҰྫΛࣔ͢ɽ࣍ʹɼ֤γζϧϫʔυ sw ͱྉཧ໊ c ʹରͯ͠ɼࡐྉ໊ʹΑΔϕΫτϧΛ
࡞੒͢ΔɽϕΫτϧͷ஋͸ॏཁ౓ T F IDF ͷ஋ͱ͢Δɽ࣍ʹɼ࡞੒ͨ͠ϕΫτϧΛ༻͍ͯɼ֤γζϧϫʔυͱྉཧ໊ͷ cos ྨ

3. γζϧϫʔυ͔Β૝‫͞ى‬ΕΔྉཧ໊ͷ֫ಘࣅ౓Λࣜ (2) Ͱ‫͢ࢉܭ‬Δɽ

Vຊ‫Ͱڀݚ‬͸ɼγζϧϫʔυ͔Β૝‫͞ى‬ΕΔྉཧ໊ΛɼCookPad

COS(swx , cy ) = ʹ͋ΔϨγϐΛ༻͍ͯ֫ಘ͢ΔɽϨγϐͷλΠτϧʹ͸ɼʮΫ

V

i=1

i=1

ʢ஫ 1ʣɿhttps://ja.wikipedia.org/

xiɾyi

x2i ×

V
i=1

(2)
yi2

ࣜ (2) ͷ xi , yi ͸ͦΕͧΕ swx , cy ͷϕΫτϧɼV ͸ϕΫτϧ

ʢ஫ 2ʣɿhttps://twitter.com/

ͷେ͖͞Ͱ͋Δɽ࠷‫ʹޙ‬ɼ֤γζϧϫʔυʹରͯ͠ cos ྨࣅ౓ʢ஫ 3ʣɿhttps://cookpad.com/্Ґͷྉཧ໊Λ֫ಘ͢Δɽ

- 78 -—2—

4. 1. 3 จ ͷ ௕ ͞

4. ࡶֶจͷநग़ଠాΒ͸ɼ௕͗͢Δจ΍୹͗͢Δจ͸γεςϜͷൃ࿩จͱ͠

ຊ‫Ͱڀݚ‬͸ɼ Wikipedia ͔Βࡶֶจͷநग़Λߦ͍ɼಠࣗʹઃͯෆద੾Ͱ͋Δͱߟ͑ɼऩूͨ͠ࡶஊର࿩ίʔύεͷ͓͚Δ֤

ఆͨ͠ࢦඪʹ‫ॱ͖ͮج‬Ґ͚ͮΛߦ͏ɽ4. 1 અͰ Wikipedia ͔Βൃ࿩ͷ‫ܗ‬ଶૉ਺ͷׂ߹ΛείΞʹ༻͍͍ͯΔɽ͔͠͠ɼຊ‫ڀݚ‬ͷࡶֶจநग़ํ๏ʹ͍ͭͯઆ໌͠ɼ4. 2 અͰಠࣗͷࢦඪʹ‫ͮج‬ͷର৅Ͱ͋Δࡶֶจ͸ɼҰൠతͳࡶஊର࿩ʹ͓͚Δൃ࿩จΑΓ͘ॱҐ͚ͮʹ͍ͭͯઆ໌͢Δɽ

΋௕͍ͱߟ͑ΒΕΔɽΑͬͯɼຊ‫Ͱڀݚ‬͸ར༻͠ͳ͍ɽ

4. 1 Wikipedia ͔Βͷࡶֶจநग़

4. 1. 4 ϧ ʔ ϧ

Wikipedia ͔ΒࡶֶจΛநग़͢Δख๏ʹ͍ͭͯઆ໌͢ΔɽຊଠాΒ͸ɼҎԼͷϧʔϧΛຬͨ͢จ͸ɼ1 จͷΈͰҙຯΛཧ‫Ͱڀݚ‬͸ɼલड़ͷଠాΒΛϕʔεͱͨ͠ख๏Λ༻͍ΔɽଠాΒղ͢Δ͜ͱ͕Ͱ͖ͳ͍ෆద੾ͳจͰ͋Δͱͯ͠ഉআ͍ͯ͠Δɽ͸ɼWikipedia ͔Β‫ࣄه‬Λ 1 ͭऔΓग़͠ɼ‫಺ࣄه‬ͷจʹରͯ͠•຤ඌ͕ಡ఺΍ϐϦΦυͰ͸ͳ͍

TF-IDFɼ୯‫ޠ‬ͷ‫ىڞ‬ස౓ɼจͷ௕͞ͷ 3 ͭͷࢦඪʹ‫ͮ͘ج‬ε•ॿࢺͷʮ͕ʯ΋͘͠͸ʮ͸ʯΛ‫͍ͳ·ؚ‬ίΞΛ‫͠ࢉܭ‬ɼϧʔϧʹΑͬͯϖφϧςΟΛ༩͑ͨ‫ޙ‬είΞ্•ମ‫ࢭݴ‬ΊͰऴΘ͍ͬͯΔҐͷจΛநग़͍ͯ͠Δɽຊ‫Ͱڀݚ‬͸ɼଠాΒ͕༻͍ͨࢦඪʹม•઀ଓࢺ͔Β࢝·ΔߋΛՃ͑Δ͜ͱͰɼࡶֶจͷநग़Λߦ͏ɽ•ࢦࣔ‫ޠ‬΍ಛఆͷ୯‫ޠ‬Λ‫ؚ‬Ή

4. 1. 1 IDF

ҰํͰɼ͜ΕΒͷҰ෦Λຬͨ͢จ͸ɼจ຺৘ใͷ௥Ճ΍จ຤දଠాΒ͸ɼWikipedia ͷ‫ࣄه‬தʹ͋ΔॏཁͳจͷධՁΛߴ͘‫ݱ‬ͷิ‫Ͳͳ׬‬Λߦ͏͜ͱͰɼൃ࿩จͱͯ͠ར༻ՄೳʹͳΔͱߟ

͢ΔͨΊʹɼจதͷ໊ࢺʹରͯ͠ TF-IDF Λ‫ٻ‬Ίɼͦͷฏ‫ۉ‬஋͑ΒΕΔͨΊɼഉআ͢Δͷ͸ඞͣ͠΋ద੾Ͱ͸ͳ͍ɽͦ͜Ͱຊ

ΛείΞͱͯ͠༻͍͍ͯΔɽ͔͠͠ɼຊ‫Ͱڀݚ‬ର৅ͱ͢Δࡶֶ

‫Ͱڀݚ‬͸ҎԼͷϧʔϧΛઃ͚ɼഉআ͢ΔͷͰ͸ͳ͘ϧʔϧΛຬจ͕ɼ‫ࣄه‬தͷॏཁͳจͰ͋Δͱ͸‫ݶ‬Βͳ͍ɽ·ͨɼઐ໳ੑͷͨ͢จʹείΞʹ 0.1 Λ৐ࢉ͢Δ͜ͱͰɼ4. 1. 1 અ΍ 4. 1. 2 અߴ͍จ͸ࡶֶจͰ͋ΔՄೳੑ͕ߴ͍ͱߟ͑ΒΕΔɽΑͬͯຊ‫ݚ‬Ͱ‫ٻ‬ΊͨείΞΛॏࢹͭͭ͠ɼҰఆͷείΞΛׂΓ౰ͯΔɽ

‫Ͱڀ‬͸ɼTF-IDF Ͱ͸ͳ͘ IDF ͷΈΛ༻͍Δɽจ Si ʹର͢Δ•

઀ଓࢺ΍ࢦࣔ‫ޠ‬Λ‫ؚ‬Ή

IDF ʹ‫ͮ͘ج‬είΞ IDF (Si ) ͸ࣜ (3) Λ༻͍ͯ‫͢ࢉܭ‬Δɽ

•จதͷ໊ࢺͷ਺͕ 2 ͭҎԼ
IDF (Si ) =w∈Si‫ʹٯ‬ɼWikipedia ͷ‫ࣄه‬ͷ࠷ॳʹॻ͍ͯ͋Δఆٛจ΍Օ৚ॻ͖idf (w)Ͱॻ͔Ε͍ͯΔจʹ͸ɼࡶֶจͰͳ͍จ͕ଟ͘ଘࡏ͢ΔͨΊɼ(3)n(Si )

͜ͷΑ͏ͳจͷείΞ͸ 0 ͱ͢Δɽ

ࣜ (3) ͷ w ͸จ Si தͷ໊ࢺɼidf (w) ͸ w ͷ Web ೔ຊ‫ ޠ‬N ά

4. 1. 5 จͷॱҐ͚ͮϥϜ [10] ͷ 1-gram ʹ͓͚Δ IDF ஋ɼn(Si ) ͸จ Si தͷ໊ࢺͷ૯ҟͳΓ਺Ͱ͋Δɽ

4. 1. 1 અͱ 4. 1. 2 અͰ‫ͨ͠ࢉܭ‬είΞʹ‫͖ͮج‬ɼจ Si ʹର͢ΔείΞ Score(Si ) Λࣜ (6) Λ༻͍ͯ‫͢ࢉܭ‬Δɽ

4. 1. 2 ୯‫ޠ‬ͷ‫ىڞ‬ස౓

Score(Si ) = IDF (Si ) × coF reqlog (Si ) × αଠాΒ͸ɼ‫ىڞ‬ස౓ͷ௿͍୯‫ߏͰޠ‬੒͞ΕΔจ͸ɼҙ֎ੑͷ͋Δ಺༰Λ‫ؚ‬ΜͰ͍ΔՄೳੑ͕ߴ͍ͱͯ͠ɼ୯‫ޠ‬ͷ‫ىڞ‬ස౓ʹα =‫ͮ͘ج‬είΞΛ‫͍ͯ͠ࢉܭ‬Δɽ·ͣɼจ Si ͔Β໊ࢺΛநग़͠ɼ໊֤ࢺʹରͯ͠ 7-gram ͷൣғʹ͋Δ໊ࢺͱͷ໊ࢺϖΞΛ࡞੒

(6)

⎧
⎪
⎨ 0.1

(4. 1. 4 અͷϧʔϧΛຬͨ͢)0(ఆٛจ΋͘͠͸Օ৚ॻ͖ͷจ)1(্‫ه‬ͷͲΕʹ΋౰ͯ͸·Βͳ͍)⎪⎩͢Δɽ࣍ʹɼ࡞੒໊ͨ͠ࢺϖΞͷ‫ىڞ‬ස౓Λɼ Web ೔ຊ‫ ޠ‬N͜ͷ Score(Si ) Λ 1 ͭͷ‫ࣄه‬ͷશจʹରͯ͠‫͠ࢉܭ‬ɼ4. 1. 4 અάϥϜͷ 7-gram Λ༻͍ͯࢉग़͢Δɽ࠷‫ʹޙ‬ɼࣜ (4) Ͱ୯‫ޠ‬ͷͷϧʔϧͰϖφϧςΟΛ༩͑ͨ‫ޙ‬ɼείΞ্ҐͷจΛநग़͢Δɽ‫ىڞ‬ස౓ʹ‫ͮ͘ج‬είΞ coF req(Si ) Λ‫͢ࢉܭ‬Δɽ

coF req(Si ) =⎧cfmax + 1 − cfi
⎪
⎪
⎨
cfmax
⎪
⎪
⎩

0

4. 2 ରԠՄೳ౓ʹΑΔॱҐ͚ͮ
4. 1 અͰநग़ͨ͠จΛɼείΞ Score(Si ) ॱͰର࿩γεςϜ(cfi = 0)ʹ༻͍Δ৔߹ͷ໰୊఺ʹ͍ͭͯઆ໌͢Δɽྫ͑͹ɼʮΠϯυྉ(4)ཧʯͷ‫͔ࣄه‬ΒʮϋΠσϥόʔυͷϋϦʔϜ͕༗໊ʯͱ͍͏จ

(cfi = 0)͕ɼείΞ Score(Si ) ͕࠷΋ߴ͍จͱͯ͠நग़Ͱ͖ͨͱ͢Δɽ

ࣜ (4) ͷ cfi ͸จ Si தͷશͯͷ໊ࢺϖΞͷ‫ىڞ‬ස౓ͷฏ‫ۉ‬ɼ͜͜ͰɼείΞ Score(Si ) ॱͰநग़ͨ͠ࡶֶจΛ༻͍Δ৔߹ɼ

cfmax ͸ cfi ͷ࠷େ஋Ͱ͋Δɽ͔͠͠ɼࣜ (4) ͸ɼcfmax ͷ஋͕͜ͷʮϋΠσϥόʔυͷϋϦʔϜ͕༗໊Ͱ͢ʯͱ͍͏จ͕͸͡ඇৗʹେ͖͘ɼcfi ͱ cfmax ͷؒʹେ͖ͳ͕ࠩ͋Δͱɼ΄ͱΜΊʹग़ྗ͞ΕΔɽ͜ͷ࣌ɼ͜ͷจʹର͢ΔϢʔβͷԠ౴จͱ͠

ͲͷจͷείΞ͕΄΅ಉ͡஋ʹͳΔͱ͍͏໰୊఺͕͋ΔɽΑͬͯɼʮϋΠσϥόʔυ͍͍ͱ͜ΖͰ͢ΑͶʯ΍ʮϋϦʔϜͬͯԿͯɼຊ‫Ͱڀݚ‬͸ࣜ (4) ʹର਺Λద༻ͨࣜ͠ (5) Λ༻͍ͯɼ୯‫ޠ‬Ͱ͔͢ʯͷΑ͏ͳจ͕ߟ͑ΒΕΔɽ͔͠͠ɼʮϋΠσϥόʔυʯͷ‫ىڞ‬ස౓ʹ‫ͮ͘ج‬είΞ coF reqlog (Si ) Λ‫͢ࢉܭ‬Δɽͷ‫ࣄه‬ͷจ਺͕গͳ͍৔߹ɼϋΠσϥόʔυʹ͍ͭͯͷࡶஊΛ

coF reqlog (Si ) =⎧log cfmax + 1 − log cfi⎪⎪⎨
log cfmax⎪⎪⎩0ଓ͚͍ͯ͘͜ͱ͕೉͘͠ͳΔɽ·ͨɼʮϋϦʔϜʯͷ‫͕ࣄه‬ଘࡏ(cfi = 0)͠ͳ͍৔߹ɼΘ͔Βͳ͍ͱ͍͏ࢫͷԠ౴จΛग़ྗ͢Δ͜ͱʹͳ(5)(cfi = 0)ΓɼϢʔβͷର࿩ཉ‫ٻ‬Λ࡟͙͜ͱʹͳΔɽ͜ͷΑ͏ʹɼநग़ͨ͠จͷ಺༰ʹରͯ͠ɼWikipedia ͷ‫͕ͭ࣋ࣄه‬஌ࣝྔ͕ශऑͳ

- 79 -—3—

ユーザ: 〇〇なものが食べたいな

定義質問: Yes

II. 記事検索I. 定義文判定

固有名詞抽出

in: 質問
定義質問: No

in: 情報伝達

out: わかりません+雑学文(現在のトピック)

料理名獲得

抽出: Yes/out: 雑学文 (抽出した固有名詞について)
抽出: No/out: 雑学文 (現在のトピック)

in: 「いいえ」相当

シズルワード-料理名の対応リスト

検索: No/out: わかりません+雑学文(最初のトピック)
検索: Yes/out: 定義文

out: 定義文

S1

システム: [料理名1]を出しているお店にしますか。
それとも[料理名2]にしますか。

IDF値: 閾値未満
out: 雑学文 (抽出した固有名詞について)
抽出: Noout: 雑学文(現在のトピック)

ユーザが料理名を決定

in: 相槌in -> 入力文のタイプ

雑学文出力

S1, S2 -> 状態

雑談状態へ移行γζϧϫʔυΛ‫ؚ‬ΉϢʔβൃ࿩จ͔Βࡶஊঢ়ଶҠߦ·Ͱͷ֓ཁਤS2

II. IDF値判定

in: 「はい」相当

長方形 -> 条件分岐

ਤ1

IDF値: 閾値以上
out: 確認文

抽出: YesI. 固有名詞抽出

out -> システムの出力

ਤ2ࡶஊঢ়ଶ࣌ͷॲཧͷ֓ཁਤ৔߹ɼϢʔβ͔Βͷ࣭໰΍࿩୊ͷҠߦͳͲʹ্ख͘ରԠͰ͖ͳ

ํ๏Ͱ͸ࣅͨΑ͏ͳྉཧΛఏࣔ͢Δ‫ݥة‬ੑ͕͋Δɽྫ͑͹ɼγ͍ͱ͍͏‫ݥة‬ੑ͕͋Δɽຊ‫Ͱڀݚ‬͸ɼ͜ͷ໰୊఺Λղܾ͢ΔͨζϧϫʔυʮεύΠγʔʯʹ͍ͭͯɼcos ྨࣅ౓͕ߴ͍ॱʹʮνΊʹɼϢʔβͷ࣭໰΍࿩୊ͷҠߦʹରԠͰ͖Δ͔Ͳ͏͔Λද͢ΩϯΧϨʔʯɼʮυϥΠΧϨʔʯɼʮλίϥΠεʯɼʮΫϦʔϜΧ

ࢦඪʢରԠՄೳ౓: Response ScoreʣΛ‫͠ࢉܭ‬ɼ4. 1 અͰநग़ϨʔʯɼʮΤεχοΫϥΠεʯͷ 5 ‫ݸ‬ͷྉཧ໊͕֫ಘ͞Εͨ৔߹ɼͨ͠จʹରͯ͠࠶౓ॱҐ͚ͮΛߦ͏ɽcos ྨࣅ౓͕ߴ͍ॱʹఏࣔ͢Δྉཧ໊Λબ୒͢ΔͱɼʮνΩϯରԠՄೳ౓ (RS) ͷ‫͍ͯͭʹࢉܭ‬આ໌͢ΔɽରԠՄೳ౓ʹͭΧϨʔʯͱʮυϥΠΧϨʔʯ͕બ୒͞ΕΔɽ͔͠͠ɼ͜ͷ 2 ͍ͭͯ͸ɼ4. 1. 5 અͰ‫ͨ͠ࢉܭ‬είΞ Score(Si ) ্Ґ 10 จͷΈΛ͸ࣅͨྉཧͰ͋ΔͨΊɼ྆ํΛϢʔβʹఏࣔ͢Δҙຯ͸ͳ͍ɽର৅ʹ‫ࢉܭ‬Λߦ͏ɽ·ͣɼWikipedia ͔Β 1 ͭͷ‫ࣄه‬ΛऔΓग़͕ͨͬͯ͠ɼຊ‫Ͱڀݚ‬͸୯‫ޠ‬ͷҙຯతྨࣅੑΛ༻͍ͯɼ‫ʹ͍ޓ‬

͠ɼ4. 1 અͰநग़ͨ͠จ Si ͔Β‫ݻ‬༗໊ࢺ pnj Λநग़͢Δɽ࣍

ࣅ͍ͯͳ͍ 2 ͭͷྉཧ໊Λબ୒͢Δɽબ୒͢Δ 2 ͭͷྉཧ໊ͷʹɼ‫ݻ‬༗໊ࢺ pnj ͱλΠτϧ͕Ұக͢Δ‫ ࣄه‬Apnj Λ‫͠ࡧݕ‬ɼ͏ͪɼ1 ͭ͸ cos ྨࣅ౓͕࠷΋ߴ͍ྉཧ໊ c Ͱ͋Δɽ΋͏ 1 ͭ

είΞ RS(pnj ) Λࣜ (7) Λ༻͍ͯ‫͢ࢉܭ‬Δɽ

ͷྉཧ໊ͷબ୒ʹ͍ͭͯɼ·ͣ c ʹ‫·ؚ‬ΕΔ໊ࢺΛநग़͠ɼͦN

RS(pnj ) = log sn(Apnj ) +



N =

i=1

Score(Ti )N

10(sn(Apnj ) >= 10)sn(Apnj )(sn(Apnj ) < 10)ͷ໊ࢺΛ‫͍ͳ·ؚ‬΋ͷΛଞͷ 4 ͭͷྉཧ໊͔Βநग़͢Δɽͦ͠

(7)ͯɼநग़ͨ͠ྉཧ໊ͱ c ͱͷྨࣅ౓Λɼ୯‫ޠ‬ͷ෼ࢄද‫[ ݱ‬11] ʹ‫͠ࢉܭ͖ͮج‬ɼ࠷΋ྨࣅ౓͕௿͔ͬͨྉཧ໊Λબ୒͢Δɽ࣍ʹɼࡶஊঢ়ଶͰͷγεςϜͷॲཧͷྲྀΕʹ͍ͭͯઆ໌͢Δɽࣜ (7) ͷ sn(Apnj ) ͸‫ ࣄه‬Apnj ͷจ਺ɼTi ͸‫ ࣄه‬Apnj ʹ͓͚Δ 4. 1. 5 અͷείΞ Score ্Ґ i ൪໨ͷจͰ͋Δɽͦͯ͠ɼ

RS(pnj ) Λจ Si ͷશͯͷ‫ݻ‬༗໊ࢺʹରͯ͠‫ࢉܭ‬Λߦ͍ɼͦͷฏ‫ۉ‬஋Λจ Si ͷରԠՄೳ౓ͱͯ͠ࢉग़͢Δɽ࠷‫ʹޙ‬ɼ֤จʹ֓ཁਤΛਤ 2 ʹࣔ͢ɽࡶஊঢ়ଶͰͷγεςϜ͸ S1 ͱ S2 ͷ 2ͭͷঢ়ଶΛ࣋ͭɽঢ়ଶ S1 ͰͷॲཧͷྲྀΕʹ͍ͭͯઆ໌͢Δɽঢ়ଶ S1 Ͱ͸ɼϢʔβ͔ΒೖྗจΛड͚औͬͨ࣌ɼೖྗจΛҎԼͷ 3 ͭͷλΠϓʹϧʔϧΛ༻͍ͯ෼ྨ͢Δɽ

•ରͯ͠ରԠՄೳ౓Λ‫͠ࢉܭ‬ɼॱҐ͚ͮΛߦ͏ɽ࣭໰ߏจղੳ‫ ث‬KNPʢ஫ 4ʣ Ͱʮٙ໰ʯλά͕෇༩͞ΕΔɼ΋͘͠

5. ࡶֶจΛར༻͢Δର࿩γεςϜ͸ٙ໰ࢺ͕ଘࡏ͢Δɽ•ຊ‫Ͱڀݚ‬͸ɼ3. અͰ֫ಘͨ͠γζϧϫʔυͱྉཧ໊ͷ૊ͱɼ

4. અͰநग़ͨ͠ࡶֶจΛ༻͍ͨର࿩γεςϜΛߏங͢Δɽຊγ•εςϜͷॲཧͷྲྀΕ͸ɼγζϧϫʔυΛ‫ؚ‬ΉϢʔβൃ࿩จ͔Βྉཧ໊Λܾఆ͠ɼࡶஊঢ়ଶ΁Ҡߦ͢Δ·Ͱͷॲཧͱɼࡶஊঢ়ଶ
Ͱͷॲཧͷ 2 ͭʹ෼͔ΕΔɽ·ͣɼγζϧϫʔυΛ‫ؚ‬ΉϢʔβൃ࿩จ͔Βࡶஊঢ়ଶҠߦ·ಘͨ͠γζϧϫʔυͱྉཧͷ૊ͷத͔Β 2 ͭͷྉཧ໊Λબ୒͠ɼϢʔβʹఏࣔΛߦ͏ɽྉཧ໊Λఏࣔͨ͠‫ޙ‬ɼϢʔβʹྉཧ໊Λܾఆͯ͠΋Β͏ɽྉཧ໊͕ܾఆͨ͠Βɼͦͷྉཧ໊ʹؔ͢
ΔࡶֶจΛग़ྗ͠ɼࡶஊঢ়ଶ΁Ҡߦ͢Δɽ
ఏࣔ͢Δྉཧ໊ͷબ୒ํ๏ʹ͍ͭͯઆ໌͢Δɽબ୒͢Δྉཧ໊͸ɼγζϧϫʔυʹରͯ͠ 3. અͰ‫ ͨ͠ࢉܭ‬cos ྨࣅ౓্Ґ 5૬௤‫ݻ‬༗໊ࢺΛ‫͍ͳ·ؚ‬ɼ΋͘͠͸‫ݻ‬༗໊ࢺ͸‫ؚ‬Ή͕ಈࢺ‫ܗͼٴ‬༰ࢺΛ‫͍ͳ·ؚ‬ɽ࣍ʹɼҎԼͷΑ͏ʹλΠϓʹԊͬͨԠ౴จΛੜ੒͢Δɽ•ͰͷॲཧͷྲྀΕʹ͍ͭͯઆ໌͢Δɽ֓ཁਤΛਤ 1 ʹࣔ͢ɽϢʔβ͔ΒγζϧϫʔυΛ‫ؚ‬ΜͩೖྗจΛड͚औͬͨ࣌ɼ3. અͰ֫৘ใ఻ୡ‫ݻ‬༗໊ࢺΛ‫ؚ‬Έɼ͔ͭಈࢺ΋͘͠͸‫ܗ‬༰ࢺΛ‫ؚ‬Ήɽ࣭໰ʹ෼ྨ͞Εͨ৔߹ʢਤ 2 ͷʮin:࣭໰ʯʣʢ I ʣ ·ͣఆٛΛ໰͏࣭໰͔Ͳ͏͔ͷ൑ఆΛߦ͏ɽ͜ͷ࣌ɼ൑ఆ͸ʮԿʯɼʮͲΜͳ΋ͷʯͳͲͷΩʔϫʔυΛ‫ؚ‬ΜͰ͍Δ͔
Ͳ͏͔Ͱߦ͏ɽఆٛΛ໰͏࣭໰Ͱͳ͍৔߹͸ɼʮΘ͔Γ·ͤΜʯͱ͍͏ࢫͷจͱ࠷ॳͷτϐοΫʹؔ͢ΔࡶֶจΛग़ྗ͢Δɽ
ʢ II ʣ ఆٛΛ໰͏࣭໰Ͱ͋ͬͨ৔߹ʹ͸ɼ ࣭໰ର৅ͱͳͬ
͍ͯΔ୯‫ͱޠ‬λΠτϧ͕Ұக͢Δ Wikipedia ͷ‫ࣄه‬Λ‫ࡧݕ‬Λߦ͏ɽͦͯ͠ɼ‫͕ͨͬ͋ࣄه‬৔߹ʹ͸ఆٛจΛग़ྗ͢Δɽ‫ࣄه‬‫ݸ‬ͷྉཧ໊͔Βબ୒͢Δɽྉཧ໊બ୒ͷ࠷΋୯७ͳํ๏͸ɼcosྨࣅ౓ͷߴ͍ॱʹྉཧ໊Λબ୒͢Δํ๏Ͱ͋Δɽ͔͠͠ɼ͜ͷʢ஫ 4ʣɿhttp://nlp.ist.i.kyoto-u.ac.jp/?KNP- 80 -—4—͕ͳ͔ͬͨ৔߹ʹ͸ʮΘ͔Γ·ͤΜʯͱ͍͏ࢫͷจͱ࠷ॳͷτ

6. 2 ࣮ ‫ ํ ݧ‬๏ϐοΫʹؔ͢Δ৽ͨͳࡶֶจΛग़ྗ͢Δɽ

•γζϧϫʔυ͔Β૝‫͞ى‬ΕΔྉཧ໊͸ɼ֤γζϧϫʔυʹର৘ใ఻ୡʹ෼ྨ͞Εͨ৔߹ʢਤ 2 ͷʮin:৘ใ఻ୡʯʣ

ͯ͠ 3. અͰ‫ ͨ͠ࢉܭ‬cos ྨࣅ౓͕࠷΋ߴ্͍Ґ 5 ‫ݸ‬Λ֫ಘ͠Ϣʔβͷೖྗจ͔Β‫ݻ‬༗໊ࢺΛநग़͢Δɽ͜ͷ࣌ɼࠓ·ͰͷͨɽධՁʹ͍ͭͯ͸ɼඃ‫ ऀݧ‬5 ਓʹ֫ಘ͞Εͨγζϧϫʔυ-ྉର࿩ͷதͰτϐοΫʹͳ͍ͬͯͳ͍‫ݻ‬༗໊ࢺͷΈΛର৅ͱ͢Δɽཧ໊ͷ૊Λ‫ͯݟ‬΋Β͍ɼʮྉཧ໊ʹରͯ͠γζϧϫʔυ͕ద੾நग़Ͱ͖ͨ৔߹ʹ͸ɼͦͷ‫ݻ‬༗໊ࢺʹؔ͢ΔࡶֶจΛग़ྗ͠ɼ

Ͱ͋Δ͔Ͳ͏͔ʯΛɼద੾ͳ৔߹͸ 1ɼͦ͏Ͱͳ͍৔߹͸ 0 Ͱநग़Ͱ͖ͳ͔ͬͨ৔߹ʹ͸࠷ॳͷτϐοΫʹؔ͢ΔࡶֶจΛग़ධՁͨ͠ɽͦͷ‫ޙ‬ɼ3 ਓҎ্͕ 1 ͱධՁͨ͠γζϧϫʔυ-ྉཧ

ྗ͢Δɽͳ͓ɼநग़Ͱ͖Δ‫ݻ‬༗໊ࢺ͕ 2 ͭҎ্͋Δ৔߹͸ɼ4. 2

ͷ૊਺ͷׂ߹Λࢉग़ͨ͠ɽ
ࡶֶจʹ͍ͭͯ͸ɼϥϯμϜʹ֫ಘͨ͠ 50 ‫ݸ‬ͷ WikipediaઅͰ‫ͨ͠ࢉܭ‬είΞ RS ͕࠷΋ߴ͍‫ݻ‬༗໊ࢺΛநग़͢Δɽ•૬௤ʹ෼ྨ͞Εͨ৔߹ʢਤ 2 ͷʮin:૬௤ʯʣͷ‫ʹࣄه‬ରͯ͠ɼຊ‫ͱڀݚ‬ଠాΒͷख๏Λ༻͍ͯͦΕͧΕείʢ I ʣ ௚લʹγεςϜ͕ग़ྗͨ͠ࡶֶจ͔Β‫ݻ‬༗໊ࢺΛநग़Ξ Score(Si ) ্Ґ n จΛநग़ͨ͠ɽධՁʹ͍ͭͯ͸ɼར༻͠

͢Δɽ͜ͷ࣌ɼ৘ใ఻ୡͷ࣌ͱಉ͘͡ࠓ·Ͱͷର࿩ͷதͰτͨख๏Λ෬্ͤͨͰɼඃ‫ ऀݧ‬3 ਓʹநग़֤ͨ͠จΛධՁͯ͠΋ϐοΫʹͳ͍ͬͯͳ͍‫ݻ‬༗໊ࢺͷΈΛର৅ͱ͢Δɽநग़Ͱ͖ͳ

ΒͬͨɽධՁํ๏͸ɼ֤จͷ಺༰ʹରͯ͠ʮ೔ৗੜ‫͍͓ͯʹ׆‬͔ͬͨ৔߹͸ɼͦͷ࣌఺ͰͷτϐοΫʹؔ͢ΔࡶֶจΛग़ྗࣗ͢વͱ਎ʹͭ͘ʢ҉໧తʹಘΒΕΔʣ஌ࣝͰͳ͍͔ʯΛɼࣗવ

Δɽͳ͓ɼநग़Ͱ͖Δ‫ݻ‬༗໊ࢺ͕ 2 ͭҎ্͋Δ৔߹͸ɼ4. 2 અͱ਎ʹͭ͘஌ࣝͷ৔߹͸ 0 Λɼͦ͏Ͱͳ͍ͳΒ 1 ͰධՁͨ͠ɽ

Ͱ‫ͨ͠ࢉܭ‬είΞ RS ͕࠷΋ߴ͍‫ݻ‬༗໊ࢺΛநग़͢Δɽ

ͳ͓ɼઆ໌͍ͯ͠Δର৅͕Θ͔Βͳ͍΋ͷɼ΋͘͠͸஌ࣝͱ͠ʢ II ʣ நग़Ͱ͖ͨ৔߹͸ɼͦͷ‫ݻ‬༗໊ࢺͷ IDF ஋͕ᮢ஋ΑΓͯ੒Γཱ͍ͬͯͳ͍΋ͷʢʮຊ߲Ͱ͸ 1. ͷே઱൒ౡ༝དྷͷ໙ྉେ͖͍͔ͷ൑ఆΛߦ͏ɽIDF ஋͕ᮢ஋ΑΓେ͖͍ͳΒʮʓʓͬཧʹ͍ͭͯղઆ͢ΔʯͳͲʣʹ͍ͭͯ͸ 0 ͱͨ͠ɽͦͷ‫ޙ‬ɼ2ͯ͝ଘ஌Ͱ͔͢ʯͱ͍͏֬ೝจΛग़ྗͯ͠ঢ়ଶ S2 ʹભҠ͠ɼਓҎ্͕ 1 ͱධՁͨ͠จͷจ਺ͷׂ߹Λख๏͝ͱʹࢉग़ͨ͠ɽ

ᮢ஋ҎԼͳΒ‫ݻ‬༗໊ࢺʹؔ͢ΔࡶֶจΛग़ྗ͢Δɽ

ͳ͓ɼຊ‫Ͱڀݚ‬͸ n = 5, 10 ͱͨ͠ɽঢ়ଶ S2 ͰͷॲཧͷྲྀΕʹ͍ͭͯઆ໌͢Δɽঢ়ଶ S2 Ͱ͸ɼࡶֶจΛར༻͢Δର࿩γεςϜʹ͍ͭͯ͸ɼରԠՄೳ౓Λ༻Ϣʔβ͔ΒͷೖྗจΛʮ͸͍ʯ૬౰ͱʮ͍͍͑ʯ૬౰ͷ 2 ͭʹ͍ͨ΋ͷͱͦ͏Ͱͳ͍΋ͷͷ 2 ͭΛ༻͍ͯɼඃ‫ ऀݧ‬5 ਓʹର͠ΩʔϫʔυΛ༻͍ͯ෼ྨ͢Δɽ࣮ͯࡍʹର࿩ΛߦͬͨɽධՁʹ͍ͭͯ͸ɼඃ‫ʹऀݧ‬ରͯ͠ Q1:•

ೖྗจ͕ʮ͸͍ʯ૬౰ͷ৔߹ʢਤ 2 ͷʮin:͸͍૬౰ʯʣ

ʢ I ʣ ௚લʹग़ྗͨ͠ࡶֶจ͔Βผͷ‫ݻ‬༗໊ࢺͷநग़Λߦ͏ɽର࿩ͷྲྀΕ͸ࣗવͰ͔͋ͬͨɼQ2: ର࿩͸໘ന͔͔ͬͨɼQ3:·ͨର࿩͍ͨ͠ͱࢥ͏͔ɼͦΕͧΕͷ߲໨Λ 5 ஈ֊ͰධՁͨ͠ɽ

நग़Ͱ͖ͳ͔ͬͨ৔߹͸ɼͦͷ࣌఺ͰͷτϐοΫʹؔ͢Δࡶֶ

6. 3 ݁

จΛग़ྗ͠ɼঢ়ଶ S1 ʹભҠ͢ΔɽՌγζϧϫʔυ͔Β૝‫͞ى‬ΕΔྉཧ໊ͷ֫ಘख๏ʹ͍ͭͯɼඃ

ʢ II ʣ நग़Ͱ͖ͨ৔߹͸ɼͦͷ‫ݻ‬༗໊ࢺͷ IDF ஋͕ᮢ஋Α‫ ऀݧ‬3 ਓҎ্͕ 1 ͱධՁͨ͠γζϧϫʔυ-ྉཧͷ૊਺ͷׂ߹͸Γେ͖͍ͳΒ࠶౓֬ೝจΛग़ྗ͠ɼᮢ஋ҎԼͳΒ‫ݻ‬༗໊ࢺʹؔ

0.511 Ͱ͋ͬͨɽ࣮ࡍʹ֫ಘ͞Εͨγζϧϫʔυ-ྉཧͷ૊Λද͢ΔࡶֶจΛग़ྗͯ͠ঢ়ଶ S1 ʹભҠ͢Δɽ

3 ʹࣔ͢ɽද 3 ͷʮ˓ʯ͸ඃ‫ ऀݧ‬3 ਓҎ্͕ 1 ͱධՁͨ͜͠ͱ

•ೖྗจ͕ʮ͍͍͑ʯ૬౰ͷ৔߹ʢਤ 2 ͷʮin:͍͍͑૬౰ʯʣΛɼʮʷʯ͸ 1 ͱධՁͨ͠ඃ‫ ͕ऀݧ‬2 ਓҎԼͰ͋Δ͜ͱΛද͢ɽ֬ೝจʹ‫·ؚ‬Ε͍ͯΔ‫ݻ‬༗໊ࢺͷఆٛจΛग़ྗ͠ɼঢ়ଶ S1͜ͷ݁ՌΛ౿·͑ௐࠪΛߦͬͨɽຊ࣮‫Ͱݧ‬͸ද 3 ͷΑ͏ʹɼ͋Δγζϧϫʔυʹରͯ͠γζϧϫʔυ-ྉཧ໊ͷ૊Λ 5 ૊֫ಘʹભҠ͢Δɽ

6. ࣮

͍ͯ͠Δɽͦ͜Ͱɼ֤γζϧϫʔυ͝ͱʹඃ‫ ऀݧ‬3 ਓҎ্͕ 1‫ݧ‬ͱධՁͨ͠γζϧϫʔυ-ྉཧ໊ͷ૊ʹ͍ͭͯɼ3 ૊Ҏ্ͷ৔߹γζϧϫʔυͷ֫ಘख๏ɼࡶֶจநग़ख๏ɼ‫ֶࡶͼٴ‬จΛ༻͍ͨର࿩γεςϜͷ༗ޮੑʹ͍ͭͯ‫ূݕ‬ΛߦͬͨɽΛू߹ Sethigh ͱ͠ɼ2 ૊ҎԼͷ৔߹Λू߹ Setlow ͱͯ͠γζϧϫʔυΛ෼ྨͨ͠ɽྫ͑͹ɼද 3 ͷʮϐϦਏʯ͸˓͕ 5 ‫Ͱݸ‬

6. 1 ࣮ ‫ ݧ‬ઃ ఆ͋ΔͨΊɼSethigh ʹ෼ྨ͞ΕΔɽҰํɼʮϓϦϓϦʯ͸˓͕ 1γζϧϫʔυͱྉཧ໊ʹ͍ͭͯ͸ɼਓखͰऩूͨ͠ 615 ‫ݸ‬ͷ͔ͭ͠ͳ͍ͨΊɼSetlow ʹ෼ྨ͞ΕΔɽͦͯ͠ɼͦΕͧΕͷूྉཧ໊ͱ 341 ‫ݸ‬ͷγζϧϫʔυΛ༻͍ͨɽ·ͨɼϨγϐʹ͍ͭ߹ʹରͯ͠ɼ֫ಘͨ͠Ϩγϐʹ͓͚Δγζϧϫʔυͷग़‫਺ݱ‬ͷͯ͸ CookPad ͔Β 1 ͭͷྉཧ໊ʹ͖ͭ࠷େ 30 ݅ऩूͨ͠ɽ

ฏ‫ۉ‬஋Λࢉग़ͨ͠ɽ݁ՌΛද 4 ʹࣔ͢ɽද 4 ΑΓɼSetlow ʹଐͦͷ݁Ռɼ14,704 ݅ͷϨγϐΛ֫ಘ͢Δ͜ͱ͕Ͱ͖ͨɽͳ͓ɼ

͢ΔγζϧϫʔυͷϨγϐग़‫͕਺ݱ‬ɼSethigh ʹଐ͢Δγζϧ341 ‫ݸ‬ͷγζϧϫʔυͷதͰɼ֫ಘͨ͠Ϩγϐதʹग़‫͍ͯ͠ݱ‬ϫʔυͷϨγϐग़‫਺ݱ‬ΑΓগͳ͍͜ͱ͕Θ͔ͬͨɽΑͬͯɼϨͨγζϧϫʔυͷ਺͸ 127 ‫ͨͬ͋Ͱݸ‬ɽWikipedia ͷ‫ͭʹࣄه‬γϐग़‫͕਺ݱ‬গͳ͔ͬͨγζϧϫʔυʹ͍ͭͯɼγζϧϫʔυ͍ͯ͸ɼ2017 ೥ 5 ݄ 21 ೔෇Ͱ΢ΟΩϝσΟΞࡒஂΑΓఏ‫͞ڙ‬ͷಛੑΛද͢ࡐྉ໊ͷϕΫτϧΛ͏·͘࡞੒Ͱ͖ͳ͔ͬͨͨΊʢ஫ 5ʣ͔Βೖखͨ͠΋ͷΛ༻͍ͨɽʹɼద੾ͳྉཧΛ֫ಘ͢Δ͜ͱ͕Ͱ͖ͳ͔ͬͨͱߟ͑ΒΕΔɽ୯‫ޠ‬ͷ෼ࢄද‫͍ͯͭʹݱ‬͸ɼWord2Vecʢ஫ 6ʣ Λ༻͍ͯ֫ಘͨ͠ɽ

ࡶֶจநग़ख๏ͷධՁ݁ՌΛද 5 ʹࣔ͢ɽද 5 ΑΓɼఏҊΕ͍ͯΔσʔλϕʔεɾσʔλख๏͸ଠాΒͷख๏ΑΓࡶֶΛ‫ؚ‬ΜͰ͍Δͱ൑அ͞Εͨจͷจ
ʢ஫ 5ʣɿhttps://dumps.wikimedia.org/jawiki/਺ͷׂ߹͕ߴ͍͜ͱ͕Θ͔Δɽ·ͨɼt ‫ݕ‬ఆʹΑΔ‫ݕ‬ఆͰ͸ɼʢ஫ 6ʣɿhttps://radimrehurek.com/gensim/models/word2vec.html

n = 5 ͷ৔߹ͷ݁Ռʹؔͯ͠ɼp < 0.05 ͷൣғͰ༗ҙࠩΛ֬ೝ

- 81 -—5—ද3֫ಘͨ͠γζϧϫʔυ-ྉཧ໊ͷྫγζϧϫʔυ

ྉཧ໊ 1

ྉཧ໊ 2

ྉཧ໊ 3

ྉཧ໊ 4

ྉཧ໊ 5

ϐϦਏ

ϚʔϘကʢ˓ʣ

ຑം՘ࢠʢ˓ʣ

ຑം՘ࢠကʢ˓ʣ

ճು೑ʢ˓ʣ

ຑം౾෗ʢ˓ʣ

͞ͱ͍΋͝൧ʢ˓ʣ͔΅ͪΌ͕Ώʢʷʣ౔ು͝൧ʢʷʣ

ୄΊ͠ʢʷʣϗΫϗΫ͔΅ͪΌͷࣽ෺ʢ˓ʣ ͔΅ͪΌͷͦ΅Ζ͋Μ͔͚ʢ˓ʣ ཬҶͷͦ΅Ζ͋Μ͔͚ʢ˓ʣ

ϓϦϓϦ͠ΌͿ͠ΌͿʢʷʣද4ू߹ผͷϨγϐதͰͷग़‫਺ݱ‬͔͖͝൧ʢ˓ʣ
ද5λʔϝϦοΫϥΠεʢʷʣࡶֶจநग़ͷධՁ݁Ռද6

ର࿩γεςϜͷධՁ݁Ռநग़ख๏ n = 5

n = 1020.641

ଠాΒ

0.612

0.656

ରԠՄೳ౓͋Γ

3.0 2.8 3.2

8.465

ఏҊख๏

0.700

0.706

ରԠՄೳ౓ͳ͠

3.0 3.4 3.2

ର

ྫ

ू߹

Ϩγϐग़‫਺ݱ‬ͷฏ‫ۉ‬Sethigh
Setlow

ද7

࿩

Q1 Q2 Q3

ൃ࿩ऀ

ൃ࿩จ

Ϣʔβ

ϗΫϗΫͨ͠΋ͷ͕৯΂͍ͨγεςϜ͔΅ͪΌͷࣽ෺Λग़͍ͯ͠Δ͓ళʹ͠·͔͢? ͦΕͱ΋͞ͱ͍΋͝൧ʹ͠·͔͢?

Ϣʔβ͞ͱ͍΋͝൧͕৯΂͍ͨγεςϜ൧ͱ͍͑͹ɺอԹ͢Ε͹ʮσϯϓϯͷྼԽʯ͸๷͛Δ·͚͢Ͳɺ࣭͕ྼԽ͠ष͘ͳΔͦ͏Ͱ͢ΑϢʔβ஌Βͳ͔ͬͨ

γεςϜσϯϓϯͱ͍͑͹ɺδϟΨΠϞʹ͍ͭͯɺ͍ΘΏΔɺย‫܀‬ค͸ɺΧλΫϦͷ஍Լ‫͔ܪ‬Β࠾औͨ͠σϯϓϯΛࢦ͢‫ݴ‬༿Ͱ͋ͬͨɺۙ೥ࢢൢ͞Ε͍ͯΔย‫܀‬คͱ‫ݺ‬͹ΕΔ΋ͷͷ΄ͱΜͲ͸അླॼఽคͱͳ͍ͬͯΔͦ͏Ͱ͢ΑϢʔβย‫܀‬ค͸͡Ό͕͍΋͔ΒͰ͖ͯΔΜͩɾɾɾ

͢Δ͜ͱ͕Ͱ͖ͨɽຊ‫Ͱڀݚ‬͸ɼIDF ͱ coF reqlog ʹରͯ͠ϐϡʔλαΠΤϯε‫͔ॴڀݚ‬Βͷडୗ‫ʹڀݚ‬ΑΔ΋ͷͰ͢ɽͷॏΈΛߟྀ͍ͯ͠ͳ͍ͨΊɼॏΈΛ͚ͭΔ͜ͱͰਫ਼౓ͷ޲্ΛਤΔ͜ͱ͕Ͱ͖ΔͷͰ͸ͳ͍͔ͱߟ͑ΒΕΔɽ
ࡶֶจΛར༻͢Δର࿩γεςϜͷධՁ݁ՌΛද 6 ʹɼ࣮ࡍͷର࿩ྫΛද 7 ʹࣔ͢ɽද 6 ΑΓɼରԠՄೳ౓Λ༻͍ͨγες
Ϝͷ Q2 ͷධՁ஋͸ɼରԠՄೳ౓Λ༻͍ͳ͍৔߹ʹൺ΂௿͍͜ͱ͕Θ͔Δɽ͜Ε͸ɼରԠՄೳ౓Λ༻͍ͨγεςϜ͕ɼ1 ͭͷτϐοΫʹ͍ͭͯͷࡶֶΛଟ͘ग़ྗ͍ͯͨ͜͠ͱ͕‫ݪ‬ҼͰ͋Δ
ͱߟ͑ΒΕΔɼରԠՄೳ౓Λ༻͍ͨγεςϜ͸ɼ‫ݻ‬༗໊ࢺநग़
ʹ͓͍ͯɼ‫ࡏݱ‬ͷτϐοΫͱͳ͍ͬͯΔ୯‫ޠ‬ͷείΞ RS ΑΓ΋ߴ͍είΞΛ࣋ͭ‫ݻ‬༗໊ࢺͷΈΛநग़͠ɼͦͷ‫ݻ‬༗໊ࢺͷࡶֶจΛग़ྗ͢ΔɽΑͬͯɼ͋ΔτϐοΫͷείΞ RS ͕ߴ͍৔߹ɼଞͷτϐοΫʹҠߦ͢Δ͜ͱ͕೉͘͠ͳΔɽΑͬͯɼ͋Δ
τϐοΫʹؔ͢Δࡶֶจͷग़ྗճ਺Λ੍‫͢ݶ‬Δ͜ͱͰɼϢʔβ͕ର࿩ʹ๞͖ʹ͘͘ͳΔͱߟ͑ΒΕΔɽ

7. Ή ͢ ͼຊ‫Ͱڀݚ‬͸ɼγζϧϫʔυ͔Β૝‫͞ى‬ΕΔྉཧ໊Λɼ ࡐྉ໊ʹண໨ͨ͠ϕΫτϧΛ༻͍ͯ֫ಘ͢Δख๏ͱɼଠాΒΛϕʔεͱͨ͠ख๏ʹରԠՄೳ౓Λ૊Έ߹Θͤͨࡶֶจநग़ख๏ΛఏҊͨ͠ɽ·ͨɼఏҊख๏Λ૊Έ߹Θͤɼγζϧϫʔυ͔Β૝‫͞ى‬
ΕΔྉཧ໊ͷࡶֶΛ࿩͢ର࿩γεςϜͷߏஙΛߦͬͨɽ࣮‫ݧ‬ͷ݁Ռɼ51.1%ͷਫ਼౓Ͱγζϧϫʔυʹରͯ͠ద੾ͳྉཧ໊Λ֫
ಘ͢Δ͜ͱ͕Ͱ͖ͨɽ·ͨɼࡶֶจநग़ख๏ʹ͍ͭͯ͸ଠాΒͷख๏ʹରͯ͠༗ҙࠩΛ֬ೝ͢Δ͜ͱ͕Ͱ͖ͨɽର࿩γεςϜʹ͍ͭͯ͸ɼରԠՄೳ౓ͷ༗ޮੑΛ֬ೝ͢Δ͜ͱ͕Ͱ͖ͳ͔ͬ
ͨɽࠓ‫ޙ‬ͷ՝୊ͱͯ͠ɼࡶֶจநग़ͷ֤ࢦඪͷॏΈௐ੔΍ɼಉҰτϐοΫʹ͓͚Δࡶֶจग़ྗճ਺ͷ੍‫͕͛͋Ͳͳݶ‬ΒΕΔɽँࣙຊ‫ڀݚ‬ͷҰ෦͸ฏ੒ 29 ೥౓ FAIS ৽੒௕ઓུਪਐ‫ݚ‬จ‫ݙ‬[1] Steve Young, Milica Gašić, Blaise Thomson, and Jason D
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‫ڀ‬։ൃࣄ‫ۀ‬ʢ࣮༻Խ‫ڀݚ‬։ൃࣄ‫ۀ‬ʣͷॿ੒Λड͚ͨʢ‫ג‬ʣίϯ

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