クックパッドにおける研究の活用と支援

Transcript

1. ΫοΫύουʹ͓͚Δݚڀͷ׆༻ͱࢧԉ ΫοΫύουגࣜձࣾ ݪౡ
   ७
2. ൃද֓ཁ ΫοΫύουͰ͸ɺ࠷৽ͷݚڀΛΩϟονΞοϓͯ͠ϓϩμΫτʹ׆༻͢Δ ͱͱ΋ʹɺֶज़తͳݚڀΛαϙʔτͯ͠ΞΧσϛΞʹߩݙ͢Δ͜ͱʹ΋ྗΛ ೖΕ͍ͯ·͢ɻຊൃදͰ͸ɺΫοΫύουʹ͓͚Δ࠷৽ͷݚڀͷ׆༻ࣄྫͱ ֶज़తͳݚڀΛࢧԉ͢ΔͨΊͷऔΓ૊Έʹ͍ͭͯ঺հ͠·͢ɻ ΫοΫύου ݚڀ
3. ݪౡ
   ७ ɾΤϯδχΞʢݕࡧɾฤ੒෦ʣ ɹɾ
   ZFBST
   PG
   EFWFMPQNFOU
   FYQFSJFODF ɾത࢜ʢ৘ใֶʣ ɹɾ
   ZFBST
   PG
   SFTFBSDI
   FYQFSJFODF ɾઐ໳ ɹɾࣗવݴޠॲཧɺ৘ใݕࡧ
4. ΫοΫύου
5. ར༻ঢ়گ IUUQTJOGPDPPLQBEDPNpOBODJBM@IJHIMJHIU
6. Ϩγϐ਺ IUUQTJOGPDPPLQBEDPNpOBODJBM@IJHIMJHIU
7. ΫοΫύουʹ͓͚Δݚڀͷ׆༻ࣄྫ
8. ΫοΫύουʁ ʮ3VCZ
   PO
   3BJMT
   ͱ͔ɺΤϯδχΞϦϯά͕Μ͹ͬͯͦ͏ɻ ɹ͚Ͳɺݚڀʹ͸ڵຯͳ͍Ͱ͠ΐʁʯ
9. ΫοΫύουͷݚڀࣄ৘ ɾࠓ݄ɺݚڀྖҬΛઐ໳ʹѻ͏νʔϜ͕ൃ଍͠·ͨ͠ ɹɾ੒Ռ͸͜Ε͔Β
    ɾ༷ʑͳݚڀΛϓϩμΫτʹ׆༻͍ͯ͠·͢ ɹɾϨγϐͷࣗಈ෼ྨ ɹɾ঎඼ͷݻ༗දݱೝࣝ ɹɾίϯςϯπͷϨίϝϯσʔγϣϯ
10. Ϩγϐͷࣗಈ෼ྨ
11. Ϩγϐͷࣗಈ෼ྨ
12. ɾ47.
    ʹΑΔ෼ྨ ɹɾ-*#-*/&"3
    Λར༻ ɹɾૉੑ͸ൿີ
     ɾϢʔβʹΑΔਪન݁ՌΛ׆༻ ɹɾਖ਼ղσʔλΛߏங͢ΔखؒΛলུ ɾຖ೔શϨγϐʢ໿
    
    ສ඼ʣΛ෼ྨ FH
    εʔϓͱͯ͠ਪન͞ΕͨϨγϐΛɹ ɹ ɹ
    
    
    
    
    
    
    εʔϓͷਖ਼ղσʔλͱͯ͠ར༻ Ϩγϐͷࣗಈ෼ྨ
13. Ϩγϐͷࣗಈ෼ྨ
14. ϖʔδԼʹ ϑΟϧλʔ Ϩγϐͷࣗಈ෼ྨ
15. ঎඼ͷݻ༗දݱೝࣝ
16. ಛച৘ใʢళฮ͔Β౤ߘʣ ݻ༗දݱೝࣝ ঎඼ͷݻ༗දݱೝࣝ ͨ·Ͷ͗ݸ 
    ԁ ͨ·Ͷ͗υϨογϯά 
    ԁ   ͨ·Ͷ͗ݸ ਺ྔ ঎඼໊ ͨ·Ͷ͗υϨογϯά ঎඼໊ ʮͨ·Ͷ͗ʯͰΠϯσΩγϯά ʮͨ·Ͷ͗υϨογϯάʯͰΠϯσΩγϯά 0OMJOF Ϣʔβͷۙลͷళฮ͔Β ঎඼໊ʮͨ·Ͷ͗ʯΛݕࡧ
17. ɾ$3'
    ʹΑΔݻ༗දݱೝࣝ ɹɾ$3'TVJUF
    Λར༻ ɾ໿
    
    छྨͷϥϕϧΛఆٛ ɹɾFH
    ঎඼໊ɺ࢈஍ɺ਺ྔɺ෦Ґ ɾਓखͰਖ਼ղσʔλΛߏங ɹɾܗଶૉղੳͱݻ༗දݱೝࣝͷਖ਼ղσʔλΛߏங ɹɾ֤ϞσϧΛ঎඼ʹ࠷దԽ ঎඼ͷݻ༗දݱೝࣝ
18. ݻ༗දݱೝࣝͷਖ਼ղ ܗଶૉղੳͷਖ਼ղ ঎඼ͷݻ༗දݱೝࣝ
19. ઍ༿࢈ʹΜ͡Μຊ ࠃ࢈ಲ೑ʢϞϞɾΧλʣ ࢈஍ ਺ྔ ઍ༿࢈ʹΜ͡Μຊ ࠃ࢈ಲ೑ʢϞϞɾΧλʣ ෦Ґ ঎඼໊ ෦Ґ ࢈஍ ঎඼໊ ঎඼ͷݻ༗දݱೝࣝ ͚ͨͷ͜ͷཬ ͚ͨͷ͜ͷཬ ঎඼໊
20. ΫΤϦʹԠͯ͡࠷దͳίϯςϯπΛදࣔ ίϯςϯπͷ࠷దԽ
21. ίϯςϯπͷ࠷దԽ ݙཱΛग़ͨ͠Βศརʁ Ϣʔβ͞ΜʹΑΔ ͓͢͢ΊϨγϐͱ͔ ྉཧͷίπͳΜͯͲ͏ʁ 6*
    ͕ෳࡶԽ ৽͍͠ίϯςϯπΛग़ͦ͏ʂ χϡʔεɺಈըɺ
22. ɾଟ࿹όϯσΟοτ ɹɾ୳ࡧͱ׆༻Λ࢖͍෼͚ͯใुΛ࠷େԽ ɹɹɾ୳ࡧɿ৘ใΛऩू͢ΔͨΊʹ࿹Λબ୒ ɹɹɾ׆༻ɿऩूͨ͠࿹ʹج͍ͮͯ࿹Λબ୒ ɹɾ୳ࡧͱ׆༻͸τϨʔυΦϑ ɾίϯςΩετ෇͖ଟ࿹όϯσΟοτ ɹɾ࿹ͷใु͕ίϯςΩετʹΑͬͯҧ͏ʢFH
    ޿ࠂͷ
    $53ʣ ɹɾίϯςΩετΛૉੑͰදݱͯ͠ɺใु͕࠷େͱͳΔΑ͏ʹॏΈΛֶश ɹɾίϯςΩετ͝ͱʹ࿹Λબ୒ ࿹ ίϯςϯπͷ࠷దԽ
23. ɾίϯςΩετ෇͖ଟ࿹όϯσΟοτʹΑΔίϯςϯπ࠷దԽ ɹɾ7PXQBM
    8BCCJU
    Λར༻ ɾ࿹
    ʹ
    ίϯςϯπ ɹɾFH
    ݙཱɺهࣄɺྉཧಈը ɾใु
    ʹ
    $53 ɹɾϢʔβʹظ଴͞ΕΔ࿹͕׆༻࣌ʹબ୒͞ΕΔ ɾ࿹ͷબ୒ ɹɾ୳ࡧ࣌ɿҰ෦
    17
    ͰϥϯμϜʹબ୒ ɹɾ׆༻࣌ɿ$53
    ࠷େͱظ଴͞ΕΔ΋ͷΛબ୒ 10/9
    10/10% 10/11% 10/9
    10/10% 10/11% m/d
    m/d
    md%   % md%  % construct%training% and%test%data
    m/d% % %m’/d’% 
    mdm’d’ %   % Amazon%S3
     
    
    10/9% % 10/11% 
    …
    …
    predict%ac:ons
    learn%model%   
     % 
    % 
    Offline
    
    explore
    exploit
    log*show/click*events
    
    Treasure*Data
    
      
       
    Online
    ίϯςϯπͷ࠷దԽ
24. ɾ$53
    
    ഒ ɹɾ ׆༻࣌ͷ
    $53
    
    ୳ࡧ࣌ͷ
    $53 ɾબ୒͞Εͨίϯςϯπʢׅހ಺͸֤ΫϦΤΠςΟϒͷ
    $53ʣ ྫྷౚཛ هࣄʢ
    ʣ ͚ͨͷ͜ ๐ཱͯ
    ੜΫϦʔϜ
    ؆୯ جຊ஌ࣝʢ
    ʣ ྉཧಈըʢ
    ʣ ίϯςϯπͷ࠷దԽ
25. ɾΫοΫύουʹ͓͚Δݚڀͷ׆༻ࣄྫ ɹɾϨγϐͷࣗಈ෼ྨ ɹɾ঎඼ͷݻ༗දݱೝࣝ ɹɾίϯςϯπͷ࠷దԽ ɾࠓޙͷల๬ ɹɾػց຋༁
    XF
    BSF
    IJSJOH ɹɾը૾ೝࣝʁ લ൒ͷ·ͱΊ IUUQSFDSVJUDPPLQBEDPN
26. ֶज़తͳݚڀΛࢧԉ͢ΔऔΓ૊Έ
27. Α͋͘Δ૬ஊ ʮϨγϐͷσʔλΛ࢖͍͍ͨʂݚڀ͕ਐ·ͳ͍ʂʂʂʯ
28. ૬ஊ͝ͱʹఏڙɻ͚Ͳ ɾݸผରԠ͕େม ɹɾඞཁͳσʔλͷฉ͖औΓ ɹɾར༻ܖ໿ͷࡦఆɾక݁ ɹɾσʔλͷ४උɾૹ෇ ɾྉཧʹؔ͢Δݚڀ͕޿͕Βͳ͍ ɹɾ૬ஊ͕͋Ε͹σʔλΛఏڙ͍ͯ͠Δ͜ͱΛ୭΋஌Βͳ͍ ɹɾ݁ՌɺϓϩμΫτʹ׆༻Ͱ͖Δݚڀ੒Ռ͕ࣦΘΕΔ
29. σʔλެ։
30. ɾݚڀऀ ɹɾϨγϐσʔλ͕ར༻Մೳ ɹɾڞ௨ͷσʔληοτΛ௨ͯ͠ɺઌߦݚڀͱͷൺֱ͕༰қʹ ɾΫοΫύου ɹɾݸผରԠͷख͕ؒݮগʢσʔλɾར༻ܖ໿ͷҰຊԽʣ ɹɾྉཧʹؔ͢Δݚڀ͕૿Ճ 8JO8JO
31. ެ։σʔλʢϨγϐʣ ɾλΠτϧ ɾ֓ཁ ɾࡐྉ ɾखॱ ɾίπɾϙΠϯτ ɾ͜ͷϨγϐͷੜཱ͍ͪ ɾͭ͘ΕΆ ɾFUD
32. ެ։σʔλʢݙཱʣ ɾλΠτϧ ɾ͜ͷݙཱͷϙΠϯτ ɾௐཧ࣌ؒ ɾஈऔΓͷίπ ɾओࡊ ɾ෭ࡊ ɾࢀߟʹͳͬͨʂ ɾ͜ͷݙཱͷओͳ৯ࡐδϟϯϧγʔϯ
33. ར༻ํ๏ ɾ/**
    Λ௨ͯ͡ར༻Մೳ ɹɾIUUQXXXOJJBDKQDTDFOUFSJESDPPLQBEDPPLQBEIUNM ɾެతͳݚڀػؔͷํ͕ར༻Մೳ ɹɾاۀͷݚڀػؔͷํ͸ผ్͝૬ஊ͍ͩ͘͞ ɾར༻ن໿͸ҎԼͷϖʔδ ɹɾIUUQTDPPLQBEDPNUFSNTDPPLQBE@EBUB
34. ਃ੥खॱ
35. ਃ੥खॱ
36. ίϯτϦϏϡʔγϣϯ ɾެ։͔Β࢛ϲ݄Ͱ
    
    ݚڀࣨʹఏڙ ɹɾجຊతʹ͸େֶ͔Βͷਃ੥ʢͨ·ʹߴઐͳͲ͔Β΋ʣ ɾاۀ͔Β΋ෳ਺ͷਃ੥ ɹɾఏڙՄೳ͔͸Ҋ݅࣍ୈʢݚڀ໨తͰͳ͍Ҋ݅͸μϝʣ ɾࠓޙɺڞ௨ͷσʔληοτͱͯ͠ར༻Մೳ ɹɾઌߦݚڀͱͷൺֱ͕༰қʹ
37. ϋοΧιϯʢ༨ஊʣ ४උͷख͕ؒল͚ͨ
    
38. ɾֶज़తͳݚڀΛࢧԉ͢ΔऔΓ૊Έ ɹɾΫοΫύουσʔλͷެ։ ɹɾ
    ݚڀࣨʹఏڙࡁΈ ɾࠓޙͷల๬ ɹɾը૾ެ։ʢ༧ఆʣ ɹɾ৯ϝσΟΞݚڀձͷ։࠵ʢ
    ݄ʣ ޙ൒ͷ·ͱΊ
39. ·ͱΊ
40. ·ͱΊ ຊൃදͰ͸ɺΫοΫύουʹ͓͚Δ࠷৽ͷݚڀͷ׆༻ࣄྫͱֶज़తͳݚڀΛ ࢧԉ͢ΔͨΊͷऔΓ૊Έʹ͍ͭͯ঺հ͠·ͨ͠ɻΫοΫύουͰ͸ɺࠓ݄ɺ ݚڀྖҬΛઐ໳ʹѻ͏νʔϜ΋ൃ଍͠·ͨ͠ɻࠓޙɺΑΓҰ૚ݚڀྖҬʹྗ ΛೖΕ͍ͯ͘༧ఆͰ͢ɻ ΫοΫύου ݚڀ