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ࡒ௡େՆ, ࡾ୐༔հ / Pepabo R&D Institute, GMO Pepabo, Inc. 2020.05.15 ୈ49ճ ৘ใॲཧֶձ Πϯλʔωοτͱӡ༻ٕज़ݚڀձ ECαΠτʹ͓͚ΔӾཡཤྺΛ༻͍ͨ ߪങʹܨ͕ΔߦಈͷมԽݕग़

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1. ݚڀͷ໨త 2. ՝୊ 3. ఏҊख๏ 4. ࣮ݧͱߟ࡯ 5. ·ͱΊͱࠓޙ 2 ໨࣍

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1. ݚڀͷ໨త

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• ECαΠτΛ๚ΕΔϢʔβʔ͸ෳ਺ͷ໨తΛ࣋ͭ • ྫʣʮ΢Οϯυ΢γϣοϐϯάʯʮ঎඼ͷ୳ࡧʯʮಛఆ঎඼ͷߪങʯͳͲ • ECαΠτͷӡӦऀ͕؍ଌՄೳͳϢʔβʔͷߦಈ͸໨తʹΑͬͯมԽ͢Δ • ྫʣʮ঎඼ͷݕࡧʯʮ঎඼ͷӾཡʯʮ঎඼ͷߪങʯͳͲ ঎඼ͷ୳ࡧ͕໨త ➡ ঎඼ͷछྨͰݕࡧͯ͠ݕࡧ݁ՌΛ਺ϖʔδӾཡ ಛఆ঎඼ͷߪങ͕໨త ➡ ঎඼໊Ͱݕࡧͯ͠঎඼ϖʔδΛৄ͘͠Ӿཡ 4 ECαΠτͷϢʔβʔͷ໨తͱߦಈ

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• ϢʔβʔͷߦಈͷมԽʹ߹ΘͤͯECαΠτͷγεςϜΛదԠతʹ มԽͤ͞Δ͜ͱͰߪങ཰ͷ޲্͕ظ଴͞ΕΔ • ঎඼Λ୳ࡧ͍ͯ͠Δ ➡ ଟ༷ੑͷ͋Δਪનख๏ʹ੾Γସ͑ͯڵຯΛऒ͘ • ಛఆ঎඼ͷߪങΛߦ͓͏ͱ͍ͯ͠Δ ➡ ܾࡁಋઢΛࣔͯ͠ߪങΛଅ͢ • ECαΠτͷγεςϜͷదԠతͳมԽΛ࣮ݱ͢ΔͨΊʹɼ Ϣʔβʔ͕ԿΒ͔ͷߦಈΛऔͬͨ௚ޙʹมԽΛݕग़͍ͨ͠ 5 Ϣʔβʔͷߦಈʹ߹ΘͤͨECαΠτͷదԠతͳมԽ

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• ECαΠτͷγεςϜͷదԠతͳมԽΛ࣮ݱ͢ΔͨΊʹɼ Ϣʔβʔ͕ԿΒ͔ͷߦಈΛऔͬͨ௚ޙʹมԽΛݕग़͍ͨ͠ • Ϣʔβʔ͕औΓ͏Δߦಈ͸ECαΠτ͝ͱʹ༷ʑ • ຊใࠂͰ͸ECαΠτʹڞ௨ͷߦಈͱͯ͠ߪങʹܨ͕ΔߦಈͷมԽݕग़ΛఏҊ 6 ࠓճͷใࠂͷൣғ

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2. ՝୊

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• ECαΠτ͝ͱʹར༻Մೳͳಛ௃ྔͷ͏ͪɼͲΕΛߪങʹܨ͕Δߦಈͷ มԽݕग़ʹ༻͍Δ΂͖͔͕ະ஌ • ಛ௃ྔΛશͯ༻͍Δਂ૚ֶश΍HMMͳͲͷֶशϕʔεͷख๏͕͋Δ͕ɼ • ࣍ݩ਺͕૿͑Δ΄ͲඞཁͳαϯϓϧαΠζ͕૿େ͢Δ • Ϟσϧͷ൚ԽੑೳΛ޲্ͤ͞Δ͜ͱ͕ࠔ೉ʹͳΔ • ࣍ݩ਺ͷগͳ͍୯७ͳಛ௃ྔͰߦಈͷมԽΛݕग़Ͱ͖Δ͜ͱ͕๬·͍͠ 8 ՝୊ᶃมԽݕग़ʹ༻͍Δ΂͖ಛ௃ྔ͕ະ஌

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• طଘݚڀʹ͓͚ΔʮϢʔβʔͷ໨తʹରԠ͢ΔӾཡύλʔϯͷ෼ྨʯ(*1,2) • ॳظஈ֊ɿΧςΰϦʔϖʔδͱ঎඼ϖʔδΛଟ͘Ӿཡ͢Δ • ߪങͷ௚લɿগ਺ͷ঎඼ϖʔδʹӾཡ͕ूத͢Δ • Ϣʔβʔ͝ͱͷ͋Δظؒͷʮ঎඼Ӿཡճ਺ʯͱʮ঎඼ͷछྨͷ਺ʯ͸ ࣍ݩ਺ͷগͳ͍ಛ௃ྔʹͳΓ͏Δ *1 Moe, W.W.: Buying, searching, or browsing: Differentiating between online shoppers using in-store navigational clickstream, Journal of Consumer Psychology, Vol.13, Is-sues 1-2, pp.113-123 (2003). *2 ΢Οϥϫϯɾυχɾμϋφ:৘ใ୳ࡧͷ໨తΛߟྀͨ͠ߪങܾఆϞσϧ,ϚʔέςΟϯάɾαΠΤϯε, Vol.25, No.1,pp.15-35 (2017). 9 طଘݚڀ͔Βͷಛ௃ྔͷީิ

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• Ϣʔβʔ͝ͱͷ͋Δظؒͷʮ঎඼Ӿཡ਺ʯͱʮ঎඼ͷछྨͷ਺ʯ͸ ECαΠτ΍Ϣʔβʔ͝ͱʹಛ௃ྔͷ஋͕औΔൣғʹࠩҟ͕͋Δ • શͯͷϢʔβʔʹֶ͍ͭͯशσʔλΛ४උ͢Δ͜ͱ͸ࠔ೉ • ֶशෆཁͳΞϓϩʔνͰߦಈͷมԽΛݕग़͢Δ 10 ՝୊ᶄ؀ڥ͝ͱʹಛ௃ྔͷ஋͕औΔൣғʹࠩҟ͕͋Δ

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3. ఏҊख๏

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• ᶃߪങʹܨ͕ΔߦಈͷมԽݕग़ʹ༻͍Δ΂͖ಛ௃ྔ͕ະ஌ • ࣍ݩ਺ͷগͳ͍୯७ͳಛ௃ྔͰߦಈͷมԽΛݕग़Ͱ͖Δ͜ͱ͕๬·͍͠ • ᶄ؀ڥ͝ͱʹಛ௃ྔͷ஋͕औΔൣғʹࠩҟ͕͋Γֶशσʔλͷ४උ͕ࠔ೉ • ֶशෆཁͳΞϓϩʔνͰߦಈͷมԽΛݕग़͢Δ 12 ՝୊ͷ੔ཧ

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• ECαΠτͷγεςϜͷదԠతͳมԽΛ࣮ݱ͢ΔͨΊʹɼ Ϣʔβʔ͕ԿΒ͔ͷߦಈΛऔͬͨ௚ޙʹมԽΛݕग़͍ͨ͠ • ᶃ࣍ݩ਺ͷগͳ͍୯७ͳಛ௃ྔΛ༻͍ͯᶄֶशෆཁͳΞϓϩʔνͰ ߪങʹܨ͕ΔߦಈͷมԽݕग़Λߦ͏ • ᶃ঎඼ͷӾཡճ਺ʹର͢Δ঎඼ͷଐੑͷछྨͷൺ • ઌߦݚڀΑΓɼ͜ͷ஋͸ߪങʹ޲͚ͯখ͘͞ͳΔͱԾఆ • ᶄ౷ܭతԾઆݕఆʹΑΔฏۉ஋ͷࠩͷݕఆ 13 ఏҊख๏

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• ঎඼ͷӾཡճ਺ʹର͢Δ঎඼ͷଐੑͷछྨͷൺ • Ϣʔβʔ ͷߦಈཤྺ • ʹ͸঎඼Ӿཡ ΍঎඼ݕࡧ ͳͲ͕͋Δ • ͷ೚ҙͷҐஔͷ΢Οϯυ΢ Λߟ͑Δ • ୠ͠ɼ΢Οϯυ΢αΠζ ͱ ͔ͭ Λຬͨ͢࠷খͷࣗવ਺ Λ༻͍ͯ u Su = (a1 , a2 , …, al ) a aview asearch Su Wu (t) = (a′ 1 , a′ 2 , a′ 3 , …, at ) w 1 < n < w t − w + n > 0 n a′ 1 = at−w+n a′ 2 = at−w+n+1 a′ 3 = at−w+n+2 14 ಛ௃ྔͷఆٛᶃ

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• ঎඼ͷӾཡճ਺ʹର͢Δ঎඼ͷଐੑͷछྨͷൺ • ͷ೚ҙͷҐஔͷ΢Οϯυ΢ ʹ͓͚Δ • ঎඼ͷଐੑ ͷछྨʹؔ͢Δू߹ Λ༻͍ͯ ಛ௃ྔ • ஋͕খ͍͞΄Ͳߪങʹ޲͔͍ͬͯΔ Su Wu (t) = (a′ 1 , a′ 2 , a′ 3 , …, at ) aview ͷର৅ͱͳͬͨ঎඼ͷଐੑ attr ͷछྨ ঎඼ͷӾཡ aview ͷճ਺ attr rattr(Wu (t)) = || count(aview) 15 ಛ௃ྔͷఆٛᶄ

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• Ϣʔβʔɹͷߦಈཤྺ • Ͱͷ঎඼IDʹؔ͢Δಛ௃ྔ • ͱ ͷର৅ͷ঎඼ID=1ɼ ͷର৅ͷ঎඼ID=2ͱ͢Δͱ Su = (asearch 1 , aview 2 , aview 3 , asearch 4 , aview 5 , aview 6 , aview 7 , aview 8 , aview 9 , apurchase 10 ) Wu (5) = (asearch 1 , aview 2 , aview 3 , asearch 4 , aview 5 ) aview 2 aview 3 aview 5 rID(Wu (5)) = || count(aview) = 2 3 16 ಛ௃ྔͷྫ u Wu (5)

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• ಛ௃ྔͷਪҠͷ΢Οϯυ΢ Λߟ͑Δ • ୠ͠ɼ΢Οϯυ΢αΠζ ͱ ͔ͭ Λຬͨ͢࠷খͷࣗવ਺ Λ༻͍ͯ(*) • Λ೚ҙͷ఺Ͱೋ෼ͨ͠΢Οϯυ΢ ͱ ʹରͯ͠ ౷ܭతԾઆݕఆʹΑΔฏۉ஋ͷࠩͷݕఆΛద༻ • ༗ҙਫ४ Ͱ༗ҙࠩ͋Γͱݟͳͨ͠৔߹ʹ ͷ࠷ॳͷཁૉΛมԽ఺ͱݟͳ͢ * r' ΛٻΊΔࣜΛݚڀใࠂͷ࣌఺͔Βमਖ਼͍ͯ͠·͢ W′ u (t) = (r′ 1 , r′ 2 , r′ 3 , …, rattr(Wu (t))) w′ 1 < m < w′ t − w′ + m > 0 m r′ 1 = rattr(Wu (t − w′ + m)) r′ 2 = rattr(Wu (t − w′ + m + 1)) r′ 3 = rattr(Wu (t − w′ + m + 2)) W′ u (t) W′ 1 W′ 2 s W′ 2 17 ಛ௃ྔͷਪҠΛ༻͍ͨมԽݕग़ͷఆٛᶃ

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• ౷ܭతԾઆݕఆʹΑΔฏۉ஋ͷࠩͷݕఆʹ͸ Welch ͷ ݕఆΛ༻͍Δ • Student ͷ ݕఆͷվྑ • ฼෼ࢄ͕౳͍͜͠ͱΛԾఆ͠ͳ͍ • ෼෍ͷ࿪ΈʹରԠ͕Մೳ • ඪຊͷ฼෼ࢄ͕౳͘͠ͳ͍৔߹ʹ΋޿ൣʹରԠ͠͏Δ t t 18 ಛ௃ྔͷਪҠΛ༻͍ͨมԽݕग़ͷఆٛᶄ

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• ͷͱ͖ ͷ֤૊ʹ Welch ͷ ݕఆΛద༻ • ͱ ͷ૊Ͱ༗ҙࠩ͋Γͱݟͳͨ͠৔߹ ͷ࣌ࠁ ΛมԽ఺ͱݟͳ͢ W′ u (t) = (r′ 1 , r′ 2 , r′ 3 , r′ 4 , r′ 5 ) W′ 1 = (r′ 1 ) W′ 2 = (r′ 2 , r′ 3 , r′ 4 , r′ 5 ) W′ 1 = (r′ 1 , r′ 2 ) W′ 2 = (r′ 3 , r′ 4 , r′ 5 ) W′ 1 = (r′ 1 , r′ 2 , r′ 3 ) W′ 2 = (r′ 4 , r′ 5 ) W′ 1 = (r′ 1 , r′ 2 , r′ 3 , r′ 4 ) W′ 2 = (r′ 5 ) t W′ 1 = (r′ 1 , r′ 2 ) W′ 2 = (r′ 3 , r′ 4 , r′ 5 ) r′ 3 = rattr(Wu (t − w′ + m + 2)) t 19 ಛ௃ྔͷਪҠΛ༻͍ͨมԽݕग़ͷྫ

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4. ࣮ݧͱߟ࡯

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• ࣮ࡍͷECαΠτͷӾཡཤྺʹ͓͚ΔఏҊख๏ͷ༗ޮੑͷݕূ • GMOϖύϘגࣜձࣾͷӡӦ͢ΔECαΠτʮminneʯͷӾཡཤྺʹద༻ͨ͠ 1. ϋΠύʔύϥϝʔλͷݕ౼ 2. ఏҊख๏ʹదͨ͠࡞඼ଐੑͷߟ࡯ 3. ݸผͷϢʔβʔʹର͢ΔมԽݕग़ͷ݁Ռͷ֬ೝ • ECαΠτͷߦಈ෼ੳʹ༻͍ΒΕΔӅΕϚϧίϑϞσϧͱͷਫ਼౓ͷൺֱ • ܭࢉ࣌ؒͷ֬ೝ ࣮ݧͷ໨తͱํ๏ 21

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• ECαΠτʮminneʯͷϓϩμΫγϣϯ؀ڥʹ͓͚ΔӾཡཤྺ • 2020೥3݄1೔0͔࣌Β24࣌·Ͱͷσʔλ • Ӿཡཤྺ ͷܥྻ௕ ͷ 96,984 Ϣʔβʔ • ൺֱͷͨΊߪങΛߦͬͨϢʔβʔͱߦΘͳ͔ͬͨϢʔβʔʹ෼ׂ • ࡞඼ʹඥͮ͘4ͭͷଐੑͰ࣮ݧ • ࡞඼IDɼ࡞඼ͷग़඼ऀIDɼ࡞඼ͷΧςΰϦάϧʔϓɼ࡞඼ͷΧςΰϦ Su l ≥ 6 σʔληοτ 22

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• ΧςΰϦάϧʔϓ • ྫʣʮϑΝογϣϯʯΧςΰϦάϧʔϓͷΧςΰϦ • TγϟπɼϫϯϐʔεɼτοϓεɼίʔτɼεΧʔτ ͳͲ ࡞඼ଐੑ - ࡞඼ͷΧςΰϦάϧʔϓͱΧςΰϦ 23

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ϋΠύʔύϥϝʔλͷݕ౼ • Ӿཡཤྺ͔Βಛ௃ྔͷ஋ΛٻΊΔࡍͷ΢Οϯυ΢ͷ෯ Λ {5,10} Ͱ࣮ݧ • ಛ௃ྔͷ஋ͷมԽΛݕग़͢Δࡍͷ΢Οϯυ΢ͷ෯ Λ {3,5} Ͱ࣮ݧ • ߪങϢʔβʔʹؔͯ͠ΑΓଟ͘ͷมԽ఺Λݕग़͠ɼඇߪങϢʔβʔʹؔͯ͠ গͳ͍มԽ఺Λݕग़ͨ͠ ͱ ΛҎ߱ͷ࣮ݧʹ༻͍ͨ • ༗ҙਫ४ • ׳ྫతͳ஋ͱͯ͠ Λ༻͍ͨ w w′ w = 10 w′ = 5 s s = 0.05 24

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• ࡞඼ଐੑ͝ͱͷಛ௃ྔͷ஋ͷਪҠΛശͻ͛ਤͰ֬ೝ • ྫ ఏҊख๏ʹద͢Δ࡞඼ଐੑͷߟ࡯ 25 • ԣ࣠ɿ࣌ܥྻ • ॎ࣠ɿಛ௃ྔͷ஋ • ശͷ্୺ɿୈࡾ࢛෼Ґ਺ • ശͷԼ୺ɿୈҰ࢛෼Ґ਺ • ശͷதͷԣઢɿதԝ஋ • ͻ͛ͷ্୺ɿୈࡾ࢛෼Ґ਺ʴ࢛෼Ґൣғͷ1.5ഒ • ͻ͛ͷԼ୺ɿୈҰ࢛෼Ґ਺−࢛෼Ґൣғͷ1.5ഒ • ͻ͛ͷ্Լͷ఺ɿ֎Ε஋ • ੺͍ॎઢɿதԝ஋ʹରͯ͠ఏҊख๏Λద༻ͯ͠ݕग़ͨ͠มԽ఺

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ఏҊख๏ʹద͢Δ࡞඼ଐੑ ߪങϢʔβʔ ඇߪങϢʔβʔ ࡞඼*% ࡞඼ͷग़඼ऀ*% 26 • ߪങϢʔβʔɿಛ௃ྔͷ஋͕Լ͕Δ౓ʹมԽΛݕग़ • ඇߪങϢʔβʔɿ΄΅มԽΛݕग़͍ͯ͠ͳ͍ʢߦಈͷॳظ͸ಛ௃ྔͷ஋ͷมಈ͕େ͖͍ͨΊ1Օॴݕग़ʣ ➡ ఏҊख๏ͷಛ௃ྔʹ༻͍Δ࡞඼ଐੑͱͯ͠ద͍ͯ͠Δ

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ఏҊख๏ʹద͞ͳ͍࡞඼ଐੑ ߪങϢʔβʔ ඇߪങϢʔβʔ ࡞඼ͷΧςΰϦάϧʔϓ ࡞඼ͷΧςΰϦ 27 • ߪങϢʔβʔͱඇߪങϢʔβʔͷ྆ํͰ࣌ܥྻͷॳظʹಛ௃ྔͷ஋͕Լ͕ΓɼͦͷޙมԽ͠ͳ͘ͳΔ • minne Ͱ͸ΧςΰϦͷߜΓࠐΈ͕ߪങͷ༗ແͱؔ܎ͳ͘ߦಈͷॳظʹߦΘΕΔ ➡ ఏҊख๏ͷಛ௃ྔʹ༻͍Δ࡞඼ଐੑͱͯ͠ద͍ͯ͠ͳ͍

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ӅΕϚϧίϑϞσϧʢHMMʣͱͷൺֱᶃ • ݸผͷϢʔβʔʹର͢Δਫ਼౓ͷݕ౼ • Ϟσϧͷग़ྗΛ༧ଌϥϕϧʮߪങϢʔβʔʯʹϚοϐϯά͢Δ • ఏҊख๏ɿมԽ఺Λݕग़ͨ͠৔߹ • HMMɿӅΕঢ়ଶ2ͷ͏ͪಛ௃ྔͷ஋ͷฏۉ͕௿͍ঢ়ଶʹભҠͨ͠৔߹ • HMMͷϞσϧͷߏஙͷͨΊσʔληοτΛ9:1ʹ෼ׂ • ܇࿅σʔλɿ87,285Ϣʔβʔ • ςετσʔλɿ9,523Ϣʔβʔ 28

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ӅΕϚϧίϑϞσϧʢHMMʣͱͷൺֱᶄ • ఏҊख๏ΑΓ΋HMMͷํ͕ੵۃతʹʮߪങϢʔβʔʯͷϥϕϧΛ෇͚ͨ ࡞඼IDΛಛ௃ྔʹ༻͍ͨ৔߹ͷࠞಉߦྻ ਖ਼ղϥϕϧ ߪങ ඇߪങ ༧ଌϥϕϧ ఏҊख๏ ߪങ 526 4551 ඇߪങ 201 4245 HMM ߪങ 662 5571 ඇߪങ 65 3225 ࡞඼ͷग़඼ऀIDΛಛ௃ྔʹ༻͍ͨ৔߹ͷࠞಉߦྻ ਖ਼ղϥϕϧ ߪങ ඇߪങ ༧ଌϥϕϧ ఏҊख๏ ߪങ 483 5719 ඇߪങ 244 3077 HMM ߪങ 679 7047 ඇߪങ 48 1749 29

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ӅΕϚϧίϑϞσϧʢHMMʣͱͷൺֱᶅ • ఏҊख๏ • ਅͷඇߪങϢʔβʔʹର͢Δਫ਼౓͕ߴ͍ • ِཅੑ཰ʹରِͯ͠ӄੑ཰͕௿͍ • ߪങʹܨ͕ΔϢʔβʔͷߦಈͷมԽݕग़ͷ໨తʹԊ͍ͬͯΔ • HMM • ਅͷߪങϢʔβʔʹର͢Δਫ਼౓͕ߴ͍ • ʮߪങ͠ͳ͔ͬͨʯʹϚοϐϯά͞ΕΔӅΕঢ়ଶͷ෼෍͕ฏۉ1.0ɼඪ४ภࠩ1.16*10−8ͱͳͬͯ ͓Γɼ͔ᷮͰ΋ಛ௃ྔͷ஋͕ݮগ͢Δͱʮߪങͨ͠ʯӅΕঢ়ଶʹભҠ͍ͯͨ͠ 30

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ܭࢉ࣌ؒ • 3.1GHz ΫΞουίΞ Intel Core i7 Λར༻͢ΔධՁ؀ڥʹ͓͍ͯɼ΢Οϯυ ΢ ͋ͨΓͷܭࢉ࣌ؒ͸1.71ϛϦඵʙ1.75ϛϦඵ • ΢ΣϒαΠτͷಡΈࠐΈ࣌ؒ͸1,000ϛϦඵະຬ͕๬·͍͠ͱ͞Ε͓ͯΓɼఏ Ҋख๏ʹΑΔมԽݕग़ʹֻ͔Δ࣌ؒ͸े෼ʹখ͍͞ W′ u (t) 31

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5. ·ͱΊͱࠓޙ

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·ͱΊ • ߪങʹܨ͕ΔϢʔβʔͷߦಈͷมԽݕग़ • Ӿཡཤྺ͔Βಛ௃ྔΛ࡞੒ͯ͠౷ܭతԾઆݕఆʹΑͬͯมԽݕग़Λߦ͏ • ࣮ࡍͷECαΠτͷσʔλΛ༻͍ͯಛ௃ྔʹ༻͍Δ঎඼ଐੑͷݕ౼ͱਫ਼౓͓Α ͼܭࢉ࣌ؒͷ֬ೝΛߦͬͨ • HMMͱͷൺֱͰ͸ඇߪങϢʔβʔʹؔ͢Δਫ਼౓ʹ্ؔͯ͠ճΓɼࣄલͷֶश ͕ෆཁ 33

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ࠓޙʹ͍ͭͯ • ఏҊख๏ͷਫ਼౓ͷվળ • ಛ௃ྔͷ஋͕มԽ͢Δࡍͷਖ਼ෛํ޲ͷϞσϧ΁ͷ૊ΈࠐΈ • ಛ௃ྔͷ஋ͷมಈ͕େ͖͍ظؒͷআ֎ͳͲ • ܭࢉ࣌ؒͷ୹ॖ • มԽݕग़ʹ༻͍Δ΢Οϯυ΢Λ֤ཁૉͰ෼ׂͤͣҰՕॴͰ౳෼ׂ͢Δ • খඪຊʹରͯ͠ؤ݈ͳ౷ܭతԾઆݕఆͷख๏ͷݕ౼ 34