Extraction of Dependency Subtree Features for Writing Style Indexing
3.1 ख๏
BCCWJ LBαϯϓϧ(10,511 αϯϓϧ)Λจ୯Ґ (1,651,084จ)ʹׂ͠ɼCaboCha-0.69
(UniDicओࣙنଇ)ʹΑΓจઅΓड͚ղੳΛߦ͏ɻจઅΓड͚ղੳ݁Ռ2.3અʹड़ͨ
ख๏Ͱ୯ޠΓड͚ղੳ݁Ռʹม͢ΔɻҎԼʹมࣄྫΛࣔ͢ɿ
(˜EOS(ډΔ(ɻ(ͨ(ͯ(ࢧ͑Δ))(ֺ(Λ))(྆ख(Ͱ))(৳͢(ɼ(চ(ʹ))(ମ(Λ(͠ͳ͔(ͩ(εϦϜ(ͩ))))))))(ΦΫλϏ Ξϯ((ɹ(˜BOS))))))))
(˜EOS(ײͣΔ(ɻ(ଖΕ(Λ))(ԣإ(ʹ(˜BOS))))))
(˜EOS(͔Δ(ɻ(ͳ͍(ࢲ((ʹ)))(ߦ͘(ɼ(͔(ͷ(ͨ(Կॲ())(ਓ(͕(ϝϯωϯΧϧτ(˜BOS)))))))))))))
จମࢦඪnஈ֊ධՁʹΑΓϨʔςΟϯάϥϕϧͰ͋ΔɻҰํɼࠓճ༻͍Δࣝผֶशثೋ
ྨثͰ͋ΔɻೋྨثΛϨʔςΟϯάϥϕϧʹରͯ͠ద༻͢Δख๏ͱͯ͠ɼॱংϥϕϧ ͷΑ͏ʹϨʔςΟϯάͷ্ҐԼҐʹجͮ͘ख๏(5)͕ߟ͑ΒΕΔ͕ɼࢦඪʹΑͬͯϥϕϧ͕ن ఆ͞Ε͍ͯͳ͍ͷ͋Γɼ୯७ͳone-vs-others๏Λ༻͍Δ͜ͱͱͨ͠ɻධՁʹ͓͍ͯɼશͯ
ͷೋྨث͕ෛͷΛฦͨ͠߹ʹʮϥϕϧͳ͠ʯͱͯ͠ೝఆ͢Δ͜ͱͱͨ͠ɻ
(2)./configure --with-posset=unidic
(3) ҎԼͷΑ͏ͳCaboChaͷग़ྗʹ͓͍ͯɼ1ߦͷ* 0 1D 2/4 0.000000ͷ2/4͕ओࣙΛද͢ɻ /ࠨͷ2͕༰ޠओࣙͰɼ4͕ػೳޠओࣙɿ
* 0 1D 2/4 0.000000
ʡ ิॿه߸,ׅހ։,*,*,*,*,,ʡ,*,,*,*,*,*,*,*,*
ܯ ໊ࢺ,ී௨໊ࢺ,Ұൠ,*,*,*,έΠαπ,ܯ,*,έʔαπ,*,*,*,*,*,*,*
ϝσΟΞ ໊ࢺ,ී௨໊ࢺ,Ұൠ,*,*,*,ϝσΟΞ,ϝσΟΞ,*,ϝσΟΞ,*,*,*,*,*,*,*
ʡ ิॿه߸,ׅހด,*,*,*,*,,ʡ,*,,*,*,*,*,*,*,*
͕ ॿࢺ,֨ॿࢺ,*,*,*,*,Ψ,͕,*,Ψ,*,*,*,*,*,*,*
(4)ओࣙޙஔܕ1ɿ༰ޠͱ֨ཁૉͱͳΔޙஔࢺ۟ͷؒͰઌʹߏΛ࡞Δ۟ߏΛ࡞Γɼ֨ߏͰ࠷ӈཁૉΛओࣙͱ͢
Δʀ
ओࣙޙஔܕ̎ɿଓॿࢺΛআ͍ͨड़෦ͷจઅ૬ͷ୯ҐͰઌʹߏΛ࡞Δ۟ߏΛఆ͠ɼ֨ߏͰ࠷ӈཁૉΛ ओࣙͱ͢Δʀ
ड़෦༰ޠओࣙܕɿड़෦ͷจઅ૬ͷ୯ҐͰઌʹߏΛ࡞Δ۟ߏΛఆ͠ɼड़෦ʹ͓͍ͯ࠷ࠨཁૉΛओࣙͱ͢
Δɻ
(5){1,2,3,4}ͱ͍͏ϨʔςΟϯάϥϕϧʹରͯ͠ɼ{1}vs.{2,3,4}ɾ{1,2}vs.{3,4}ɾ{1,2,3}vs.{4}ͷ3छྨͷೋྨثΛ ߏ͠ɼ͜ΕΒͷଟܾʹΑΓྨ͢Δख๏ɻ
ຊ࣮ݧͰbactͷiterationճΛ10,000ճͱͯ͠ɼBCCWJ LBαϯϓϧશͯͰϞσϧΛ
ֶश͠ɼbactʹΑͬͯಘΒΕͨ࿈ଓ෦Λੳ͢Δɻ 3.2 ಘΒΕͨنଇ
ಘΒΕͨنଇΛຊߘඌͷද2ͷʮنଇʯͷྻʹࣔ͢ɻ͓Αͦɼ֤ϥϕϧ͝ͱʹඦ (min. 157, max. 411)ɼจମࢦඪ͝ͱʹઍલޙ(min. 558, max. 1683)ఔͷಛྔʹجͮ͘ن ଇ͕ಘΒΕ͍ͯΔɻ
ಘΒΕͨنଇͷҰྫͱͯ͠ɼද1ʹ٬؍ʹରͯ͠ಘΒΕͨಛྔʢ্Ґ10ҐɾԼҐ10Ґ
·ͰʣΛࣔ͢ɻ٬؍తͳͷͷྫͱͯ͠ɼҾ༻දݱʢ“ݴ͏ ɻ”, “ʯɻ”ͳͲ)ɼ๏༻ޠʢ“๏”,
“”ͳͲʣͳͲ্͕ҐʹདྷΔ͕͋ΔɻҰํɼओ؍తͳͷͷྫͱͯ͠ɼҰਓশදݱʢ“ࢲ”,
“”, “Զ”ͳͲʣײ୰ූɾٙූͳͲ্͕ҐʹདྷΔ͕͋Δɻ
ᐈほᗘ
䝕䝣䜷䝹䝖 㻙㻜㻚㻜㻜㻞㻠㻡㻣㻝㻤㻡㻡㻌 㻌㻙㻜㻚㻜㻜㻜㻢㻜㻞㻤㻥㻞㻤 㻙㻜㻚㻜㻜㻝㻤㻢㻞㻠㻣㻞 㻌㻙㻜㻚㻜㻜㻞㻞㻝㻝㻥㻞㻟㻤
ୖ㻝 㻌㻌㻌㻜㻚㻜㻜㻝㻞㻠㻝㻥㻟㻥㻤⼍ 㻌㻌㻌㻜㻚㻜㻜㻞㻣㻟㻟㻞㻞㻢㻣߷ߑߵ 㻌㻌㻌㻜㻚㻜㻜㻟㻞㻢㻝㻜㻢㻡㻠 㻌㻌㻌㻜㻚㻜㻜㻝㻥㻤㻥㻠㻡㻢㻠ݴޖݙ
ୖ㻞 㻌㻌㻌㻜㻚㻜㻜㻝㻜㻡㻝㻟㻝㻡㻠ᜬ 㻌㻌㻌㻜㻚㻜㻜㻞㻣㻝㻡㻜㻟㻟㻟⼼a%26 㻌㻌㻌㻜㻚㻜㻜㻞㻜㻢㻝㻠㻥㻜㻣a(26ᩯݗܭݞ 㻌㻌㻌㻜㻚㻜㻜㻝㻤㻤㻣㻥㻣㻝㻤દ
ୖ㻟 㻌㻌㻌㻜㻚㻜㻜㻝㻜㻠㻥㻤㻥㻟㻟ܸܭ 㻌㻌㻌㻜㻚㻜㻜㻝㻤㻣㻤㻟㻝㻟㻞⯧ೋ 㻌㻌㻌㻜㻚㻜㻜㻜㻢㻤㻠㻤㻜㻣㻥⼍ 㻌㻌㻌㻜㻚㻜㻜㻝㻠㻜㻟㻜㻜㻢㻠ᕫޞܭݳ
ୖ㻠 㻌㻌㻌㻜㻚㻜㻜㻝㻜㻟㻜㻝㻡㻢㻡ᕫޞܭݳ 㻌㻌㻌㻜㻚㻜㻜㻝㻡㻣㻝㻣㻟㻜㻟 㻌㻌㻌㻜㻚㻜㻜㻜㻢㻟㻢㻝㻣㻡㻠ܭݳ 㻌㻌㻌㻜㻚㻜㻜㻝㻟㻠㻝㻝㻢㻞㻠ṡ
ୖ㻡 㻌㻌㻌㻜㻚㻜㻜㻝㻜㻝㻞㻡㻥㻝㻥⼊⼉a%26 㻌㻌㻌㻜㻚㻜㻜㻝㻜㻤㻠㻡㻞㻣㻝တޞܭ 㻌㻌㻌㻜㻚㻜㻜㻜㻡㻣㻤㻥㻡㻟㻡ཻਈ 㻌㻌㻌㻜㻚㻜㻜㻝㻞㻢㻝㻜㻟㻣㻥⼂
ୖ㻢 㻌㻌㻌㻜㻚㻜㻜㻜㻤㻣㻢㻤㻟㻜㻞ඨ 㻌㻌㻌㻜㻚㻜㻜㻜㻢㻟㻡㻠㻞㻠㻜a(26ᕫޞܭݳ 㻌㻌㻌㻜㻚㻜㻜㻜㻡㻢㻤㻤㻤㻢㻝ৢೋ 㻌㻌㻌㻜㻚㻜㻜㻝㻞㻡㻝㻡㻤㻤㻡⼠
ୖ㻣 㻌㻌㻌㻜㻚㻜㻜㻜㻤㻠㻣㻞㻝㻟㻥‣⇄ 㻌㻌㻌㻜㻚㻜㻜㻜㻡㻢㻝㻜㻣㻜㻟a(26ᕫޞܭݲݳ 㻌㻌㻌㻜㻚㻜㻜㻜㻡㻢㻢㻜㻣㻣㻢ṡ 㻌㻌㻌㻜㻚㻜㻜㻜㻤㻠㻞㻢㻟㻣㻡ܭ
ୖ㻤 㻌㻌㻌㻜㻚㻜㻜㻜㻣㻤㻞㻡㻢㻞㻣⼊ 㻌㻌㻌㻜㻚㻜㻜㻜㻠㻟㻥㻥㻞㻜㻥ܭޑݬ 㻌㻌㻌㻜㻚㻜㻜㻜㻡㻝㻜㻟㻟㻥㻞 㻌㻌㻌㻜㻚㻜㻜㻜㻣㻟㻠㻠㻤㻟㻣ޛ
ୖ㻥 㻌㻌㻌㻜㻚㻜㻜㻜㻢㻤㻠㻢㻡㻡㻣ᡱ 㻌㻌㻌㻜㻚㻜㻜㻜㻟㻤㻢㻝㻞㻞㻞◲ݙܭ 㻌㻌㻌㻜㻚㻜㻜㻜㻡㻜㻞㻞㻥㻤㻝a(26ᕫޞܭݳ 㻌㻌㻌㻜㻚㻜㻜㻜㻢㻥㻡㻞㻜㻣㻡
ୖ㻝㻜 㻌㻌㻌㻜㻚㻜㻜㻜㻡㻡㻡㻜㻟㻞㻜ᖠ 㻌㻌㻌㻜㻚㻜㻜㻜㻞㻤㻣㻥㻢㻝㻞ނ 㻌㻌㻌㻜㻚㻜㻜㻜㻠㻤㻟㻞㻣㻠㻣ܫܫ 㻌㻌㻌㻜㻚㻜㻜㻜㻡㻣㻥㻤㻥㻜㻠ހ
ୗ㻝㻜 㻙㻜㻚㻜㻜㻜㻢㻤㻥㻢㻢㻠㻝㻌 ཻਈ 㻌㻙㻜㻚㻜㻜㻜㻡㻞㻢㻟㻡㻣㻠ᇿݙ 㻌㻙㻜㻚㻜㻜㻜㻡㻠㻣㻡㻡㻜㻥 ิ౨ 㻌㻙㻜㻚㻜㻜㻜㻢㻤㻠㻝㻢㻤㻣ජޞ
ୗ㻥 㻌㻙㻜㻚㻜㻜㻜㻢㻥㻣㻝㻢㻢㻡∽ 㻌㻙㻜㻚㻜㻜㻜㻡㻡㻥㻜㻣㻠㻜ܭݲṡ 㻌㻙㻜㻚㻜㻜㻜㻡㻣㻢㻢㻟㻥㻜 ⦍┷ 㻌㻙㻜㻚㻜㻜㻜㻢㻥㻠㻜㻢㻥㻞⼊
ୗ㻤 㻌㻙㻜㻚㻜㻜㻜㻣㻡㻡㻝㻜㻥㻣ހ 㻌㻙㻜㻚㻜㻜㻜㻡㻢㻡㻣㻣㻥㻠ހ 㻌㻙㻜㻚㻜㻜㻜㻢㻝㻢㻞㻢㻞㻞 ⼏ 㻌㻙㻜㻚㻜㻜㻜㻣㻜㻢㻤㻟㻟㻞
ୗ㻣 㻌㻙㻜㻚㻜㻜㻜㻤㻢㻡㻟㻝㻢㻢ᆽ 㻌㻙㻜㻚㻜㻜㻜㻡㻥㻞㻣㻠㻜㻠ݽ 㻌㻙㻜㻚㻜㻜㻜㻢㻥㻟㻠㻝㻞㻜 Ⓨ⏕ 㻌㻙㻜㻚㻜㻜㻜㻣㻝㻣㻜㻠㻥㻜
ୗ㻢 㻌㻙㻜㻚㻜㻜㻜㻤㻣㻤㻟㻜㻠㻡ܭݳ 㻌㻙㻜㻚㻜㻜㻜㻤㻡㻞㻞㻡㻢㻢⼂ 㻌㻙㻜㻚㻜㻜㻜㻣㻠㻢㻟㻟㻞㻥 ᮲ 㻌㻙㻜㻚㻜㻜㻜㻣㻝㻥㻟㻥㻥㻠শᛅ
ୗ㻡 㻌㻙㻜㻚㻜㻜㻝㻜㻡㻜㻥㻤㻟㻤⼂ 㻌㻙㻜㻚㻜㻜㻜㻥㻝㻠㻠㻡㻢㻤a(26တޞܭ 㻌㻙㻜㻚㻜㻜㻜㻣㻢㻜㻥㻣㻣㻤 ඨa%26 㻌㻙㻜㻚㻜㻜㻜㻣㻡㻢㻜㻠㻠㻜ඨ
ୗ㻠 㻌㻙㻜㻚㻜㻜㻝㻜㻣㻥㻢㻟㻜㻥⼠ 㻌㻙㻜㻚㻜㻜㻜㻥㻣㻢㻢㻣㻡㻠ޛ 㻌㻙㻜㻚㻜㻜㻜㻤㻜㻣㻤㻤㻜㻢 ⼊ 㻌㻙㻜㻚㻜㻜㻜㻤㻠㻟㻢㻢㻟㻜ᴀ
ୗ㻟 㻌㻙㻜㻚㻜㻜㻝㻞㻟㻥㻥㻣㻡㻞ݨަ 㻌㻙㻜㻚㻜㻜㻝㻡㻥㻣㻞㻡㻡㻢ṡ 㻌㻙㻜㻚㻜㻜㻝㻜㻥㻜㻞㻠㻝㻠 ᕫޞܭݳ 㻌㻙㻜㻚㻜㻜㻜㻥㻟㻥㻞㻠㻜㻣⼏
ୗ㻞 㻌㻙㻜㻚㻜㻜㻝㻞㻤㻢㻣㻟㻥㻡દ 㻌㻙㻜㻚㻜㻜㻞㻜㻣㻜㻡㻡㻟㻟ܸ⼠ 㻌㻙㻜㻚㻜㻜㻝㻞㻜㻜㻠㻤㻥㻣 ᩯݗܭݞ 㻌㻙㻜㻚㻜㻜㻝㻣㻤㻢㻞㻟㻠㻟a(26ᕫޞܭݳ
ୗ㻝 㻌㻙㻜㻚㻜㻜㻝㻡㻝㻞㻞㻤㻜㻢ṡ 㻌㻙㻜㻚㻜㻜㻞㻝㻟㻠㻠㻣㻢㻤દ 㻌㻙㻜㻚㻜㻜㻞㻜㻝㻞㻠㻢㻣㻞 ⼍ 㻌㻙㻜㻚㻜㻜㻞㻤㻣㻣㻠㻠㻞㻢⼍
㻝㻌䛸䛶䜒ᐈほⓗ 㻞㻌䛹䛱䜙䛛䛸䛔䛘䜀ᐈほⓗ 㻟㻌䛹䛱䜙䛛䛸䛔䛘䜀ほⓗ 㻠㻌䛸䛶䜒ほⓗ
ද1 ྨࢦඪʮ٬؍ʯʹର͢Δنଇʢ࿈ଓ෦ύλʔϯʣ
4. ަࠩݕఆʹΑΔධՁ
࣍ʹɼߏͨࣝ͠ผֶशثͷੑೳΛධՁ͢ΔͨΊʹɼBCCWJ LBσʔλ(10,551αϯϓϧ)
্Ͱͷ5ׂަࠩݕఆΛߦ͏ɻϑΝΠϧ໊͕αϯϓϧͷଐੑͷใΛؚΜͰ͍ΔͨΊʹɼཚ
Λൃߦ͢Δ͜ͱʹΑΓαϯϓϧ୯ҐͰLBσʔλΛ5ׂͨ͠ɻࣝผֶशจ୯ҐͰߦ͍ɼจ ୯ҐධՁ(4.1અ)ɾαϯϓϧ୯ҐධՁ(4.2અ)ɾαϯϓϧશମʹ͓͚ΔจͷҐஔʹର͢Δਖ਼
(4.3અ)ͷ3छྨͷධՁΛ࣮ࢪͨ͠ɻ 4.1 จ୯ҐධՁ
จ୯ҐͷධՁ݁ՌΛຊߘඌͷද2ͷʮจ୯ҐධՁʯͷྻʹࣔ͢ɻOKࠨʹࣔ͢ϥϕϧ ΛγεςϜ͕ਖ਼ͨ݅͠ɼSYSࠨʹࣔ͢ϥϕϧΛγεςϜ͕ग़ྗͨ݅͠ʢӈʹશମʹ
͓͚Δׂ߹Λ%ͰදࣔʣɼGOLDࠨʹࣔ͢ϥϕϧΛਓखʹΑΓ༩͞Εͨ݅ʢӈʹશମ ʹ͓͚Δׂ߹Λ %ͰදࣔʣɼPREC͕ਫ਼(precision)ͰOK/SYSɼREC͕࠶ݱ(recall)Ͱ OK/GOLDΛҙຯ͢Δɻ
શମͷͱͯ͠ɼGOLDʹ͓͚Δͷେ͖͍ͷ͕ɼSYSʹ͓͍ͯେྔʹੜ͞ΕΔ Α͏ʹઑ͕ߴ͘ͳΔʹ͋Δɻݴ͍͑Δͱɼֶशσʔλʹ͓͍ͯଟͷͷͷ࠶ݱ͕
ߴ͘ͳΔʹ͋Γɼֶशσʔλʹ͓͍ͯগͷͷͷਫ਼͕ߴ͘ͳΔʹ͋Δɻ
͞Βʹɼࣝผֶशثͷग़ྗඞͣ͠ݩͷαϯϓϧͷΛอଘ͢ΔΑ͏ͳͷͰͳ͘ɼ
ࣝผֶशثͷΛ༻͍ͯɼίʔύεͷจମͷܭྔతͳௐࠪΛߦ͏͜ͱෆదͰ͋Δ͜
ͱ͕Θ͔Δɻ
Ұํɼසͷϥϕϧʹ͍ͭͯࣝผ݁Ռͷਫ਼ͷߴ͍͜ͱɼكͳจମϥϕϧͷࣄྫʹࣅͨ
ࣄྫΛେྔͷίʔύε͔Βநग़͢Δͷʹద͍ͯ͠Δͱߟ͑Δɻ 4.2 αϯϓϧ୯ҐධՁ
αϯϓϧΛߏ͢Δจ୯ҐͷධՁͷॏΈͳ͠ଟܾΛ༻͍ͯɼαϯϓϧ୯ҐͷධՁΛߦͬ
ͨɻαϯϓϧ୯ҐͷධՁ݁ՌΛຊߘඌͷද2ͷʮαϯϓϧ୯ҐධՁʯͷྻʹࣔ͢ɻ֤ྻͷҙ ຯʮจ୯ҐධՁʯͱಉ͡Ͱ͋Δɻ
ॏΈͳ͠ଟܾΛߦ͏݁ՌɼΑΓҰGOLDʹ͓͚Δͷେ͖͍ͷ͕SYSʹ͓͍ͯେ
ྔʹੜ͞ΕΔ͕ڧ͘ͳΓɼͷখ͍͞ͷͷఆͷग़ݱ͢Δ͕֬Լ͕Δʹ͋Δɻ
ྫ͑ɼઐʹ͓͍ͯ98.3%͕ʮ3Ұൠ͖ʯͱग़ྗ͞ΕΔɻ٬؍ʹ͓͍ͯ94.3%͕ ʮϥϕϧͳ͠ʯͱग़ྗ͞ΕΔɻ
4.3 αϯϓϧશମʹ͓͚ΔจͷҐஔʹର͢Δਖ਼
ධՁ10จҎ্ͷαϯϓϧͷΈʹ͍ͭͯߦͬͨɻදத(n)-(n-1)%αϯϓϧશମʹ͓͚Δ ධՁରจͷҐஔΛද͢ɻ
Ͳͷࢦඪ80-90%, 90-100%Ͱਖ਼ͷԼ͕Δ͕ݟΒΕͨɻαϯϓϦϯάʹ͓͍ͯ
90-100%ʹҐஔ͢Δσʔλ͕গͳ͘ͳΔʹ͋Δ(6)ʹͯ͠ɼ༗ҙʹ͕ࠩ͋Δɻ
͜ΕαϯϓϧͷඌʹϓϩϑΟʔϧ·ͱΊͳͲͷຊจͱҟͳΔจମ͕ग़ݱ͍ͯ͠ΔͨΊ Ͱͳ͍͔ͱߟ͑Δɻ
5. େنίʔύεͷద༻
࠷ޙʹݱࡏࠃޠݚίʔύε։ൃηϯλʔͰ։ൃ͍ͯ͠Δେنίʔύε(Asahara et al.
(2014))ʢ201410-12݄ऩूʣશจ ʢ1,463,142,939จ=14.6ԯจɼ23,836,100,595ޠ=238 ԯޠɼEOSɾ۟Λؚ·ͣʣʹ3અͰߏͨࣝ͠ผֶशثΛద༻ͨ݁͠ՌΛද2ӈͷʮେن
ίʔύεʯʹࣔ͢ɻ
جຊతʹSYSʢγεςϜ͕ग़ྗͨ݅͠ʣͱͦͷׂ߹ͷΈΛࣔ͢ɻ4અʹࣔͨ͠௨Γɼֶ
शݩσʔλʹ͓͚Δͷେ͖͍ϥϕϧ͕ΑΓଟ͘ग़ྗ͞ΕΔʹ͋Δɻ͔͠͠ͳ͕Βɼ
ͷখ͍͞ϥϕϧͰग़ྗ͞ΕΔ͜ͱ͕͋Γɼ͜ΕΒͷग़ྗ݁Ռਫ਼ͷߴ͍ͷͰ͋Δͱߟ
͑Δɻ
(6)ྫ͑ɼαϯϓϧத19จͷ߹ɼ90-100%ͷจ͕1ʹର͠ɼଞͷՕॴจ2ͱͳΔɻ
6. ͓ΘΓʹ
6.1 ຊݚڀͷ·ͱΊ
ຊݚڀͰɼBCCWJ LBαϯϓϧʹ༩͞ΕͨจମࢦඪΛ୯ޠΓड͚෦Λಛྔͱ
ͨࣝ͠ผֶशثʹΑΓϞσϧԽ͠ɼੳΛߦͬͨɻ
ಛྔͷநग़(3અ)ʹ͓͍ͯɼ୯ޠɾ୯ޠྻͷಛతͳදݱΛநग़͍ͯ͠Δ͕ɼ୯ޠΓ ड͚Λ͏༗ޮੑ·Ͱ֬ೝ͢Δ͜ͱ͕Ͱ͖ͳ͔ͬͨɻަࠩݕఆʹΑΔੑೳධՁ(4અ)ʹ͓
͍ͯɼνϟϯεϨϕϧͱൺֱ͢ΔͱΑ͍ੑೳ͕ಘΒΕ͕ͨɼֶशݩσʔλͷΛͦͷ··
γεςϜग़ྗ͢Δ͜ͱ͕ͳ͍͜ͱ͕֬ೝ͞Εͨɻ
ࠓճֶशͨࣝ͠ผֶशثΛWeb͔Βऩूͨ͠14ԯจنͷςΩετίʔύεʹద༻ͨ͠(5 અ)ɻࣝผֶशثͷग़ྗͷΛ༻͍ͯจମࢦඪͷΛੳ͢Δ͜ͱ͕ࠔͰ͋ΔҰํɼগͳ
͍ϥϕϧͷਫ਼͕ߴ͍͜ͱ͔ΒɼେྔͷςΩετ͔ΒࣅͨจମͷࣄྫΛߴਫ਼Ͱऩू͢Δ͜ͱ
͕ՄೳͰ͋Δͱߟ͑ΒΕΔɻ 6.2 ࠓޙͷݕ౼՝
ࠓޙݕ౼͖͢՝ҎԼͷͱ͓ΓͰ͋Δɿ
• ಛྔεύʔεvs.ࣄྫεύʔε
2.2અʹड़ͨ௨Γɼࠓճ༻͍ͨࣝผֶशثಛྔΛநग़͢Δ͜ͱʹΑΔೋྨث Ͱ͋Δɻܭࢉྔେ͖͘ͳΔ͕Tree Kernelʹجͮ͘Large Margin ClassifierͳͲΛ༻
͍Δ͜ͱͰࣄྫεύʔεͳղΛ༩͑ͯɼڥքࣄྫΛੳ͢Δ͜ͱΛߟ͍͑ͨɻ
• bactʹ༩͑Δ୯ޠΓड͚
ຊޠʹ͓͍ͯจઅΓड͚ʹجͮࣗ͘વݴޠॲཧͷݚڀ͕ਐΜͰ͍ΔҰํɼจ અΓड͚ʹج͍ͮͯͲͷΑ͏ͳ୯ޠΓड͚Λ༩͑Δ͔Λݕ౼͢Δඞཁ͕͋Δɻ 2.3અʹࣔͨ͠௨Γɼ͜͜ຊޠͷ୯ޠΓड͚ͷنఆʹ͍༷ͭͯʑͳఏҊ͕ͳ
͞Ε͓ͯΓɼจͷࣝผͱͯ͠ఆࣜԽͨ͠จମࢦඪੳʹ࠷దͳ୯ޠΓड͚Λௐ
ࠪ͢Δඞཁ͕͋Δɻ
• ೋྨثͷϨʔςΟϯάϥϕϧదԠ
ຊݚڀͰઙݪ΄͔(2014, 2015b)ͷରԠੳͷ݁Ռ͔ΒɼϨʔςΟϯάϥϕϧ͕ඞͣ
͠ઢܗ্ʹ͍ͯ͠ͳ͍ͱ͠ɼone-vs-others๏Λ༻͍ͨɻͦͷ݁ՌɼͷภΓΛ
૿͢ΔΑ͏ͳࣝผֶशثΛߏ͢Δ͜ͱʹͳͬͨɻͲͷΑ͏ʹϥϕϧۭؒΛߏֶश ثʹөͤ͞Δ͔Λݕ౼͢Δඞཁ͕͋Δɻ
ँࣙ
ຊݚڀͷҰ෦ࠃޠݚجװܕڞಉݚڀϓϩδΣΫτʮίʔύεΞϊςʔγϣϯͷجૅݚڀʯ͓Αͼࠃޠ ݚʮେنίʔύεߏஙϓϩδΣΫτʯʹΑΔͷͰ͢ɻ
ࢀߟจݙ
ઙݪਖ਼ɾՃ౻ɾཱՖࢠɾദՂࢠ(2014)ɽʮจମࢦඪͱޠኮͷରԠੳʯ ୈ6ճίʔύεຊ ޠֶϫʔΫγϣοϓ, pp. 11–20ɽ
ઙݪਖ਼ɾాහੜ(2015a)ɽʮίʔύείϯίʔμϯαʰChaKi.NETʱͷʮจॻ-෦ߏߦྻʯग़ྗػ
ೳʯ ୈ8ճίʔύεຊޠֶϫʔΫγϣοϓɽ
ઙݪਖ਼ɾՃ౻ɾཱՖࢠɾദՂࢠ(2015b)ɽʮจମࢦඪͱޠኮܥྻͷରԠੳʯ ୈ7ճίʔύ εຊޠֶϫʔΫγϣοϓ, pp. 7–16ɽ
Asahara, Masayuki, Kikuo Maekawa, Mizuho Imada, Sachi Kato, and Hikari Konishi (2014). “Archiving and analysing techniques of the ultra-large-scale web-based corpus project of ninjal, japan.”Alexandria, 25:1-2, pp. 129–148.
de Marneffe, Marie-Catherine, and Christopher D. Manning (2008). “The stanford typed dependencies repre- sentation.”Prof. of COLING-2008: Workshop on Cross-framework and Cross-domain Parser Evaluation.
ۚࢁതɾٶඌ༞հɾాதوळɾ৴հɾઙݪਖ਼ɾ২দ͢ΈΕ(2015)ɽʮຊޠUniversal Dependencies ͷࢼҊʯ ݴޠॲཧֶձୈ21ճ࣍େձൃදจू, pp. 505–508ɽ
ദՂࢠɾཱՖࢠɾอాɾؙࢁַɾԞଜֶɾࠤ౻ཧ࢙ɾಙӬ݈৳ɾେ௩༟ࢠɾࠤౡࣿ৫(2012a)ɽ ʮςΩετͷߗ͞ͱೈΒ͔͞ͷߟ–ʰݱຊޠॻ͖ݴ༿ۉߧίʔύεʱͷऩॻ੶Λରʹ–ʯ ୈ
1ճίʔύεຊޠֶϫʔΫγϣοϓ, pp. 131–138ɽ
ദՂࢠɾԞଜֶ(2012b)ɽʮॻ੶ςΩετͷྨࢦඪਓख༩ͷࢼΈ–ʰݱຊޠॻ͖ݴ༿ۉߧ ίʔύεʱͷऩॻ੶Λରʹ–ʯ ݴޠॲཧֶձୈ18ճ࣍େձ, pp. 1260–1263ɽ
ദՂࢠ(2013)ɽʮॻ੶αϯϓϧͷจମΛྨ͢Δʯ ࠃޠݚϓϩδΣΫτϨϏϡʔ, 4:1, pp. 43–53ɽ Ճ౻ɾദՂࢠɾཱՖࢠɾؙࢁַ(2014)ɽʮޠΓ͔͚Δॻ͖͜ͱͷදݱʯ ࠃཱࠃޠݚڀॴ
ू, 8, pp. 85–108ɽ
Kudo, Taku, and Yuji Matsumoto (2004). “A boosting algorithm for classification of semi-structured text.”
Proc. of EMNLP-2004, pp. 301–308.
McDonald, Ryan T., Joakim Nivre, Yvonnne Quirmbach-Brundage, Yoav Goldberg, Dipanjan Das, and Slav Petrov Hao Zhang Oscar T¨ackstr¨om Kuzman T¨ackstr¨om, Keith B. Hall (2013). “Universal dependency annotation for multilingual parsing.”Prof. ACL-2013(2) 92-97.
Mori, Shinsuke, Hideki Ogura, and Tetsuro Sasada (2014). “A japanese word dependency corpus.”Proc. of LREC-2014, pp. 1631–1636.
ాதوळɾӬాণ໌(2015)ɽʮຊޠͷϥϕϧ͖ґଘߏղੳͷݕ౼ʯ ݴޠॲཧֶձୈ21ճ࣍େ
ձൃදจू, pp. 1044–1047ɽ
Universal-Dependencies-contributors (2015). Universal Dependencies. https://
universaldependenceis.github.io/docs/.
อాɾദՂࢠɾཱՖࢠɾؙࢁַ(2012a)ɽʮʮޠΓ͔͚ੑʯΛ༗͢Δͱஅ͞ΕΔॻ͖͜ͱͷ දݱʯ ୈ2ճίʔύεຊޠֶϫʔΫγϣοϓ, pp. 43–50ɽ
อాɾദՂࢠɾཱՖࢠɾؙࢁַ(2012b)ɽʮʮޠΓੑʯΛ༗͢Δॻ͖͜ͱͷయܕྫͷੳʯ ୈ 1ճίʔύεຊޠֶϫʔΫγϣοϓ, pp. 139–146ɽ
อాɾദՂࢠɾཱՖࢠ(2012c)ɽʮ૯ମͱͯ͠ҹΛ༩͑ΔදݱɿʮޠΓ͔͚ੑʯΛ༗͢Δͱஅ
͢Δࠜڌʯ ਓೳֶձୈ41ճ͜ͱֶݚڀձɽ
อాɾཱՖࢠɾദՂࢠɾؙࢁַ(2013a)ɽʮʮϕςϥϯΛอޢ͢Δʯ͕ޠΓ͔͚Δͱ͖ʯ ୈ 4ճίʔύεຊޠֶϫʔΫγϣοϓ, pp. 345–354ɽ
อాɾദՂࢠɾཱՖࢠɾؙࢁַ(2013b)ɽʮΞϊςʔλʔίϝϯτΛ༻͍ͨʮޠΓ͔͚ੑʯੳ ͷࢼΈ–සใ͔Βଊ͍͑ςΩετੑ࣭ͷղ໌ʹ͚ͯ–ʯ ݴޠॲཧֶձୈ19ճ࣍େձൃද
จू, pp. 358–361ɽ
อాɾദՂࢠɾཱՖࢠɾؙࢁַ(2013c)ɽʮޠΓ͔͚Δͱஅ͞ΕΔจମ–େنίʔύεΛ༻
͍ͨಛతදݱͷੳ–ʯ ຊจମֶձୈ104ճେձɽ
อాɾദՂࢠɾཱՖࢠɾؙࢁַ(2013d)ɽʮॻ͖͜ͱʹ͓͚ΔʮޠΓ͔͚ʯԿͷͨΊʹ༻͍
ΒΕΔͷ͔ʯ ୈ3ճίʔύεຊޠֶϫʔΫγϣοϓ, pp. 143–152ɽ
ᑓ㛛ᗘ ᕸศ䝇䝟䞊䝁ᶍつ㉸౯ホ༢䝹䝥䞁䝃౯ホ༢ᩥ 㻿㼅㻿㻯㻱㻾㻯㻱㻾㻼㻰㻸㻻㻳㻿㼅㻿㻷㻻㻯㻱㻾㻯㻱㻾㻼㻰㻸㻻㻳㻿㼅㻿㻷㻻ᩘ๎つ䝹䝧䝷 㻞㻚㻜㻑㻠㻚㻢㻝㻜㻟㻣㻘㻝㻑㻠㻚㻜㻜㻠㻜㻝㻝㻝㻜㻚㻜㻝㻤㻝㻚㻜㻑㻟㻚㻣㻝㻣㻠㻥㻘㻠㻤㻞㻑㻝㻚㻝㻡㻥㻡㻘㻣㻝㻟㻥㻝㻘㻟䛧䛺䝹䝧䝷㻡㻜㻜㻚㻜㻜㻡㻠㻘㻟㻥㻥㻘㻞㻡㻜㻜㻚㻟㻑 1ᑓ㛛ᐙྥࡁ㻟㻥㻝㻞㻤㻟㻢㻣㻜㻚㻜㻑㻝㻡㻘㻥㻥㻞㻝㻚㻜㻑㻜㻚㻜㻣㻢㻜㻚㻜㻜㻝㻜㻜㻜㻚㻜㻑㻝㻠㻝㻝㻚㻟㻑㻜㻚㻜㻜㻜㻜㻚㻜㻜㻜㻝㻟㻘㻤㻟㻟㻜㻚㻜㻑 2ࡸࡸᑓ㛛ⓗ࡞୍⯡ྥࡁ㻠㻝㻝㻣㻘㻥㻢㻝㻞㻝㻘㻥㻥㻤㻝㻚㻟㻑㻝㻜㻢㻘㻢㻤㻡㻢㻚㻡㻑㻜㻚㻟㻢㻝㻜㻚㻜㻣㻠㻤㻝㻝㻟㻤㻝㻚㻟㻑㻥㻞㻥㻤㻚㻤㻑㻜㻚㻡㻤㻢㻜㻚㻜㻤㻣㻞㻘㻜㻠㻞㻘㻡㻝㻜㻜㻚㻝㻑 3୍⯡ྥࡁ㻞㻟㻤㻝㻘㻜㻣㻢㻘㻣㻠㻤㻝㻘㻢㻜㻞㻘㻣㻟㻣㻥㻣㻚㻝㻑㻝㻘㻜㻥㻟㻘㻥㻜㻡㻢㻢㻚㻟㻑㻜㻚㻢㻣㻝㻜㻚㻥㻤㻠㻣㻘㻜㻟㻢㻝㻜㻟㻣㻞㻥㻤㻚㻟㻑㻣㻘㻜㻢㻡㻢㻣㻚㻜㻑㻜㻚㻢㻣㻤㻜㻚㻥㻥㻡㻝㻘㻠㻡㻢㻘㻢㻝㻟㻘㻤㻞㻝㻥㻥㻚㻢㻑 4୰㧗⏕ྥࡁ㻟㻥㻡㻞㻤㻜㻢㻞㻝㻜㻚㻜㻑㻥㻝㻘㻤㻢㻢㻡㻚㻢㻑㻜㻚㻠㻡㻜㻜㻚㻜㻜㻟㻜㻜㻜㻚㻜㻑㻟㻤㻠㻟㻚㻢㻑㻜㻚㻜㻜㻜㻜㻚㻜㻜㻜㻥㻘㻞㻟㻤㻜㻚㻜㻑 5ᑠᏛ⏕࣭ᗂඣྥࡁ㻞㻠㻤㻠㻘㻢㻥㻥㻣㻘㻣㻢㻢㻜㻚㻡㻑㻡㻣㻘㻢㻤㻥㻟㻚㻡㻑㻜㻚㻢㻜㻡㻜㻚㻜㻤㻝㻝㻝㻜㻚㻜㻑㻟㻜㻞㻞㻚㻥㻑㻝㻚㻜㻜㻜㻜㻚㻜㻜㻟㻢㻠㻘㻞㻤㻣㻜㻚㻜㻑 㻥㻟㻥㻘㻞㻠㻝㻘㻟㻢㻠㻘㻝㻝㻡㻡㻘㻜㻝㻝㻡㻡㻘㻜㻝㻤㻞㻝㻘㻣㻠㻤㻜㻘㻝㻡㻢㻘㻝㻠㻤㻜㻘㻝㻡㻢㻘㻝㻥㻜㻥㻘㻞㻥㻜㻘㻝㻟㻤㻢㻘㻝ィ ◳ᗘ ᕸศ䝇䝟䞊䝁ᶍつ㉸౯ホ༢䝹䝥䞁䝃౯ホ༢ᩥ 㻿㼅㻿㻯㻱㻾㻯㻱㻾㻼㻰㻸㻻㻳㻿㼅㻿㻷㻻㻯㻱㻾㻯㻱㻾㻼㻰㻸㻻㻳㻿㼅㻿㻷㻻ᩘ๎つ䝹䝧䝷 㻜㻟㻣㻘㻝㻑㻣㻚㻠㻝㻤㻠㻡㻘㻝㻞㻤㻞㻤㻤㻝㻚㻜㻠㻥㻝㻚㻜㻑㻟㻚㻣㻝㻣㻠㻥㻘㻠㻤㻞㻑㻣㻚㻢㻝㻣㻟㻟㻘㻢㻣㻞㻢㻠㻤㻘㻟㻡䛧䛺䝹䝧䝷㻝㻢㻚㻠㻑㻜㻚㻝㻤㻞㻜㻚㻝㻢㻟㻡㻞㻢㻘㻜㻡㻜㻘㻟㻢㻥㻟㻢㻚㻜㻑 1࡚ࡶ◳࠸㻟㻤㻥㻝㻘㻣㻣㻡㻠㻘㻣㻠㻝㻜㻚㻟㻑㻢㻤㻘㻝㻥㻠㻠㻚㻝㻑㻜㻚㻟㻣㻠㻜㻚㻜㻞㻢㻝㻜㻝㻟㻜㻚㻝㻑㻢㻝㻥㻡㻚㻥㻑㻜㻚㻣㻢㻥㻜㻚㻜㻝㻢㻠㻢㻠㻘㻜㻟㻠㻜㻚㻜㻑 2ࡕࡽ࠸࠼ࡤ◳࠸㻞㻡㻞㻣㻤㻘㻢㻥㻥㻝㻣㻡㻘㻣㻢㻡㻝㻜㻚㻢㻑㻠㻞㻜㻘㻣㻟㻠㻞㻡㻚㻡㻑㻜㻚㻠㻠㻣㻜㻚㻝㻤㻣㻢㻞㻞㻝㻘㻝㻝㻞㻝㻜㻚㻡㻑㻟㻘㻜㻢㻡㻞㻥㻚㻜㻑㻜㻚㻡㻡㻥㻜㻚㻞㻜㻞㻠㻣㻘㻢㻡㻡㻘㻡㻜㻡㻟㻚㻟㻑 3ࡕࡽ࠸࠼ࡤ㌾ࡽ࠸㻝㻤㻞㻢㻜㻠㻘㻣㻟㻥㻝㻘㻝㻥㻞㻘㻞㻢㻢㻣㻞㻚㻞㻑㻣㻡㻟㻘㻟㻤㻟㻠㻡㻚㻢㻑㻜㻚㻡㻜㻣㻜㻚㻤㻜㻞㻠㻘㻜㻤㻣㻣㻘㻤㻣㻣㻣㻠㻚㻣㻑㻠㻘㻠㻠㻜㻠㻞㻚㻝㻑㻜㻚㻡㻝㻤㻜㻚㻥㻞㻜㻤㻤㻤㻘㻡㻢㻢㻘㻝㻥㻠㻢㻜㻚㻣㻑 4࡚ࡶ㌾ࡽ࠸㻞㻝㻠㻤㻝㻥㻝㻘㻥㻣㻡㻜㻚㻝㻑㻝㻞㻟㻘㻤㻞㻢㻣㻚㻡㻑㻜㻚㻠㻝㻠㻜㻚㻜㻜㻢㻜㻝㻜㻚㻜㻑㻢㻥㻣㻢㻚㻢㻑㻜㻚㻜㻜㻜㻜㻚㻜㻜㻜㻠㻜㻢㻘㻤㻟㻣㻜㻚㻜㻑 㻥㻟㻥㻘㻞㻠㻝㻘㻟㻢㻠㻘㻝㻝㻡㻡㻘㻜㻝㻝㻡㻡㻘㻜㻝㻝㻜㻜㻘㻡㻠㻤㻜㻘㻝㻡㻢㻘㻝㻠㻤㻜㻘㻝㻡㻢㻘㻝㻤㻣㻤㻘㻥㻟㻣㻣㻟㻜㻘㻝ィ 䛟䛰䛡ᗘ ᕸศ䝇䝟䞊䝁ᶍつ㉸౯ホ༢䝹䝥䞁䝃౯ホ༢ᩥ 㻿㼅㻿㻯㻱㻾㻯㻱㻾㻼㻰㻸㻻㻳㻿㼅㻿㻷㻻㻯㻱㻾㻯㻱㻾㻼㻰㻸㻻㻳㻿㼅㻿㻷㻻ᩘ๎つ䝹䝧䝷 㻠㻚㻢㻝㻜㻟㻣㻘㻝㻑㻠㻚㻟㻣㻡㻟㻡㻡㻟㻡㻝㻚㻜㻟㻣㻝㻚㻜㻑㻟㻚㻣㻝㻣㻠㻥㻘㻠㻤㻞㻑㻟㻚㻡㻝㻜㻤㻤㻘㻝㻡㻞㻝㻞㻣㻘㻟㻠䛧䛺䝹䝧䝷㻑㻜㻚㻝㻡㻠㻜㻚㻜㻟㻝㻝㻣㻥㻘㻢㻜㻥㻘㻢㻣㻡㻝㻞㻚㻟㻑 1࡚ࡶࡃࡔࡅ࡚࠸ࡿ㻝㻡㻣㻟㻞㻤㻝㻘㻜㻡㻞㻜㻚㻝㻑㻤㻥㻘㻠㻝㻥㻡㻚㻠㻑㻜㻚㻟㻝㻝㻜㻚㻜㻜㻟㻜㻜㻜㻚㻜㻑㻠㻣㻟㻠㻚㻡㻑㻜㻚㻜㻜㻜㻜㻚㻜㻜㻜㻟㻠㻣㻘㻝㻥㻣㻜㻚㻜㻑 2ࡕࡽ࠸࠼ࡤࡃࡔࡅ࡚࠸ࡿ㻝㻢㻟㻝㻡㻤㻘㻝㻞㻞㻟㻡㻟㻘㻠㻝㻥㻞㻝㻚㻠㻑㻡㻝㻝㻘㻢㻤㻜㻟㻝㻚㻜㻑㻜㻚㻠㻠㻣㻜㻚㻟㻜㻥㻤㻝㻟㻝㻘㻡㻞㻢㻝㻠㻚㻡㻑㻞㻘㻢㻥㻢㻞㻡㻚㻢㻑㻜㻚㻡㻟㻞㻜㻚㻟㻜㻝㻝㻤㻘㻢㻝㻠㻘㻠㻟㻢㻝㻚㻟㻑 3ࡃࡔࡅ࡚࠸࡞࠸㻞㻤㻣㻡㻡㻜㻘㻞㻟㻜㻝㻘㻜㻠㻠㻘㻣㻟㻟㻢㻟㻚㻟㻑㻣㻢㻡㻘㻜㻟㻤㻠㻢㻚㻟㻑㻜㻚㻡㻞㻢㻜㻚㻣㻝㻥㻡㻘㻝㻤㻤㻤㻘㻢㻢㻤㻤㻞㻚㻞㻑㻡㻘㻢㻡㻞㻡㻟㻚㻢㻑㻜㻚㻡㻥㻤㻜㻚㻥㻝㻣㻝㻘㻞㻢㻠㻘㻡㻣㻝㻘㻢㻟㻝㻤㻢㻚㻠㻑 㻥㻟㻥㻘㻞㻠㻝㻘㻟㻢㻠㻘㻝㻝㻡㻡㻘㻜㻝㻝㻡㻡㻘㻜㻝㻢㻡㻜㻘㻢㻠㻤㻜㻘㻝㻡㻢㻘㻝㻠㻤㻜㻘㻝㻡㻢㻘㻝㻝㻜㻠㻘㻞㻡㻣㻣㻜㻢ィ ㄒ䜚䛛䛡ᛶᗘ ᕸศ䝇䝟䞊䝁ᶍつ㉸౯ホ༢䝹䝥䞁䝃౯ホ༢ᩥ 㻿㼅㻿㻯㻱㻾㻯㻱㻾㻼㻰㻸㻻㻳㻿㼅㻿㻷㻻㻯㻱㻾㻯㻱㻾㻼㻰㻸㻻㻳㻿㼅㻿㻷㻻ᩘ๎つ䝹䝧䝷 㻝㻜㻟㻣㻘㻝㻑㻡㻚㻝㻝㻢㻝㻞㻘㻝㻤㻤㻞㻞㻝㻝㻚㻜㻠㻡㻞㻚㻜㻑㻟㻚㻣㻝㻣㻠㻥㻘㻠㻤㻞㻑㻢㻚㻣㻢㻝㻢㻘㻡㻞㻝㻣㻠㻥㻘㻝㻟䛧䛺䝹䝧䝷㻢㻚㻠㻑㻜㻚㻝㻤㻣㻜㻚㻝㻟㻝㻠㻢㻘㻢㻥㻟㻘㻥㻜㻢㻟㻚㻞㻑 1䛸䛶䜒ㄒ䜚䛛䛡ᛶ䛜䛒䜛㻞㻜㻢㻝㻟㻘㻝㻤㻞㻠㻡㻘㻠㻡㻝㻞㻚㻤㻑㻝㻝㻞㻘㻠㻠㻝㻢㻚㻤㻑㻜㻚㻞㻥㻜㻜㻚㻝㻝㻣㻥㻝㻠㻜㻚㻝㻑㻤㻟㻟㻣㻚㻥㻑㻜㻚㻢㻠㻞㻜㻚㻜㻝㻜㻝㻘㻞㻥㻣㻘㻤㻢㻟㻜㻚㻝㻑 2䛹䛱䜙䛛䛸䛔䛘䜀ㄒ䜚䛛䛡ᛶ䛜䛒䜛㻝㻣㻥㻡㻣㻠㻝㻢㻜㻚㻜㻑㻝㻥㻣㻘㻢㻠㻢㻝㻞㻚㻜㻑㻜㻚㻝㻟㻣㻜㻚㻜㻜㻜㻜㻝㻜㻚㻜㻑㻝㻘㻟㻣㻥㻝㻟㻚㻝㻑㻜㻚㻜㻜㻜㻜㻚㻜㻜㻜㻤㻜㻡㻜㻚㻜㻑 3≉䛻ㄒ䜚䛛䛡ᛶ䛿䛺䛔㻝㻣㻟㻝㻘㻜㻜㻟㻘㻥㻢㻟㻝㻘㻠㻣㻥㻘㻢㻜㻝㻤㻥㻚㻢㻑㻝㻘㻜㻡㻢㻘㻜㻡㻜㻢㻠㻚㻜㻑㻜㻚㻢㻣㻤㻜㻚㻥㻡㻜㻢㻘㻠㻜㻥㻥㻘㻟㻞㻜㻤㻤㻚㻟㻑㻢㻘㻢㻜㻥㻢㻞㻚㻢㻑㻜㻚㻢㻤㻣㻜㻚㻥㻢㻥㻝㻘㻠㻝㻡㻘㻝㻡㻜㻘㻟㻢㻡㻥㻢㻚㻣㻑 㻥㻟㻥㻘㻞㻠㻝㻘㻟㻢㻠㻘㻝㻝㻡㻡㻘㻜㻝㻝㻡㻡㻘㻜㻝㻢㻜㻣㻘㻢㻠㻤㻜㻘㻝㻡㻢㻘㻝㻠㻤㻜㻘㻝㻡㻢㻘㻝㻥㻠㻝㻘㻥㻠㻜㻘㻝㻤㻡㻡ィ ᐈほᗘ ᕸศ䝇䝟䞊䝁ᶍつ㉸౯ホ༢䝹䝥䞁䝃౯ホ༢ᩥ 㻿㼅㻿㻯㻱㻾㻯㻱㻾㻼㻰㻸㻻㻳㻿㼅㻿㻷㻻㻯㻱㻾㻯㻱㻾㻼㻰㻸㻻㻳㻿㼅㻿㻷㻻ᩘ๎つ䝹䝧䝷 㻑㻟㻚㻠㻥㻤㻠㻥㻘㻥㻥㻜㻢㻘㻠㻡㻤㻢㻚㻜㻞㻥㻡㻚㻜㻑㻤㻚㻢㻡㻞㻡㻞㻘㻣㻟㻥㻑㻣㻚㻡㻢㻤㻝㻡㻘㻠㻤㻜㻘㻝㻞㻡㻣㻘㻞㻡㻢䛧䛺䝹䝧䝷㻠㻘㻢㻡㻜㻠㻠㻚㻝㻑㻜㻚㻠㻢㻟㻜㻚㻥㻥㻝㻝㻘㻟㻜㻞㻘㻡㻞㻞㻘㻣㻠㻟㻤㻥㻚㻜㻑 1࡚ࡶᐈほⓗ㻟㻠㻜㻣㻘㻜㻟㻥㻝㻤㻘㻢㻞㻣㻝㻚㻝㻑㻝㻜㻞㻘㻤㻡㻤㻢㻚㻞㻑㻜㻚㻟㻣㻣㻜㻚㻜㻢㻤㻣㻟㻝㻝㻞㻝㻚㻝㻑㻥㻡㻜㻥㻚㻜㻑㻜㻚㻢㻡㻝㻜㻚㻜㻣㻢㻟㻘㻣㻢㻝㻘㻜㻜㻥㻜㻚㻟㻑 2ࡕࡽ࠸࠼ࡤᐈほⓗ㻝㻥㻤㻥㻥㻘㻡㻟㻤㻟㻣㻠㻘㻡㻣㻣㻞㻞㻚㻣㻑㻞㻥㻥㻘㻞㻤㻞㻝㻤㻚㻝㻑㻜㻚㻞㻢㻡㻜㻚㻟㻟㻞㻞㻠㻝㻠㻤㻣㻠㻚㻢㻑㻞㻘㻡㻞㻟㻞㻟㻚㻥㻑㻜㻚㻠㻥㻠㻜㻚㻜㻥㻡㻝㻠㻞㻘㻥㻥㻟㻘㻠㻠㻥㻥㻚㻤㻑 3ࡕࡽ࠸࠼ࡤほⓗ㻞㻣㻢㻤㻘㻟㻟㻞㻢㻜㻘㻝㻢㻥㻟㻚㻢㻑㻞㻜㻜㻘㻤㻝㻠㻝㻞㻚㻞㻑㻜㻚㻝㻟㻤㻜㻚㻜㻠㻝㻝㻟㻜㻚㻜㻑㻝㻘㻡㻢㻢㻝㻠㻚㻤㻑㻜㻚㻟㻟㻟㻜㻚㻜㻜㻜㻡㻝㻢㻘㻤㻞㻣㻜㻚㻜㻑 4࡚ࡶほⓗ㻞㻣㻤㻝㻝㻘㻠㻝㻢㻝㻝㻟㻘㻝㻥㻟㻢㻚㻥㻑㻝㻝㻜㻘㻤㻣㻤㻢㻚㻣㻑㻜㻚㻝㻜㻜㻜㻚㻝㻜㻞㻝㻝㻜㻚㻜㻑㻤㻢㻞㻤㻚㻞㻑㻝㻚㻜㻜㻜㻜㻚㻜㻜㻜㻝㻟㻘㻟㻠㻤㻘㻥㻝㻝㻜㻚㻥㻑 㻥㻟㻥㻘㻞㻠㻝㻘㻟㻢㻠㻘㻝㻝㻡㻡㻘㻜㻝㻝㻡㻡㻘㻜㻝㻡㻞㻥㻘㻠㻠㻤㻜㻘㻝㻡㻢㻘㻝㻠㻤㻜㻘㻝㻡㻢㻘㻝㻣㻣㻜㻘㻥㻣㻣㻞㻥㻜㻝ィ య䛻䛚䛡䜛⨨䛻ᑐ䛩䜛ṇ⟅⋡ 㻙㻜㻥㻑㻜㻥㻙㻜㻤㻑㻜㻤㻙㻜㻣㻑㻜㻣㻙㻜㻢㻑㻜㻢㻙㻜㻡㻑㻜㻡㻙㻜㻠㻑㻜㻠㻙㻜㻟㻑㻜㻟㻙㻜㻞㻑㻜㻞㻙㻜㻝㻑㻜㻝㻙㻜䠅ୖ௨ᩥ㻜㻝䠄㻝㻜㻜㻑㻥㻜㻙㻝㻜㻜㻑 㻝㻜㻠㻚㻜㻝㻜㻠㻚㻜㻣㻞㻢㻚㻜㻟㻣㻢㻚㻜㻡㻣㻢㻚㻜㻡㻣㻢㻚㻜㻡㻣㻢㻚㻜㻡㻣㻢㻚㻜㻡㻣㻢㻚㻜㻣㻣㻢㻚㻜㻡㻣㻢㻚㻜ᗘ㛛ᑓ 㻝㻟㻟㻚㻜㻝㻟㻟㻚㻜㻞㻠㻠㻚㻜㻡㻢㻠㻚㻜㻣㻢㻠㻚㻜㻤㻢㻠㻚㻜㻜㻣㻠㻚㻜㻣㻢㻠㻚㻜㻥㻢㻠㻚㻜㻣㻢㻠㻚㻜㻟㻢㻠㻚㻜ᗘ◳ 㻡㻢㻟㻚㻜㻡㻢㻟㻚㻜㻜㻝㻡㻚㻜㻢㻠㻡㻚㻜㻠㻠㻡㻚㻜㻤㻠㻡㻚㻜㻥㻠㻡㻚㻜㻝㻡㻡㻚㻜㻜㻡㻡㻚㻜㻜㻡㻡㻚㻜㻤㻠㻡㻚㻜ᗘ䛡䛰䛟 㻜㻡㻠㻚㻜㻜㻡㻠㻚㻜㻣㻜㻢㻚㻜㻤㻟㻢㻚㻜㻥㻟㻢㻚㻜㻥㻟㻢㻚㻜㻜㻠㻢㻚㻜㻜㻠㻢㻚㻜㻝㻠㻢㻚㻜㻝㻠㻢㻚㻜㻜㻠㻢㻚㻜ᗘᛶ䛡䛛䜚ㄒ 㻤㻡㻟㻚㻜㻤㻡㻟㻚㻜㻣㻣㻠㻚㻜㻟㻥㻠㻚㻜㻝㻥㻠㻚㻜㻡㻥㻠㻚㻜㻝㻥㻠㻚㻜㻞㻥㻠㻚㻜㻠㻥㻠㻚㻜㻡㻥㻠㻚㻜㻟㻥㻠㻚㻜ᗘほᐈ 䝃䞁䝥䝹༢㻡ศᕪ᳨ᐃ䠄䝷䞁䝎䝮㡰ศ䠅 ᩥ༢ホ౯䠖䚷䝃䞁䝥䝹䜢ᩥ༢䛻ศ䛧䛶䚸ྛᩥ䛜䛹䛾䝷䝧䝹䛻ᒓ䛩䜛䛛䜢᥎ᐃ䚹䛹䜜䛻䜒ศ㢮䛥䜜䛺䛔䜀䛒䛔䛻䛿䛂䝷䝧䝹䛺䛧䛃䜢䛴䛡䜛䚹 䝃䞁䝥䝹༢ホ౯䠖䚷ᩥ༢䛷ホ౯䛧䛯䜒䛾䛾ከᩘỴ䚹 ㉸つᶍ䝁䞊䝟䝇ศᕸ䠖䚷㉸つᶍ䝁䞊䝟䝇䜢ゎᯒ䛧䛯䜒䛾䛾䝅䝇䝔䝮ฟຊ䛾ศᕸ䚹 㻻㻷㻌䛿ṇᙜ䛧䛯ᩘ䚸㻿㼅㻿䛿䝅䝇䝔䝮䛜ฟຊ䛧䛯ᩘ䛷ྑ䛻⥲ᩘ䛻ᑐ䛩䜛ྜ䠄䠂䠅䜢䚸㻳㻻㻸㻰䛿ேᡭ䛷䛧䛯ᩘ䛷ྑ䛻⥲ᩘ䛻ᑐ䛩䜛ྜ䠄䠂䠅䜢䚹 㻼㻾㻱㻯㻌䛿⢭ᗘ㻌䠄㻻㻷㻛㻿㼅㻿㻕䚸㻾㻱㻯㻌䛿⌧⋡㻌㻔㻻㻷㻛㻳㻻㻸㻰㻕䚹 య䛻䛚䛡䜛⨨䛻ᑐ䛩䜛ṇ⟅⋡䠖䚷䝃䞁䝥䝹䛜㻝㻜ᩥ௨ୖ䛾䜒䛾䛻ᑐ䛧䚸య䛻䛚䛡䜛⨨䛻ᑐ䛩䜛ṇ⟅⋡䚹
ද2 จମੳ݁Ռ