• ਪનγεςϜʹ͍͓ͭͯͬͯ͘͜ͱͰɺͦͷΑ͏ͳϓϩμΫτͱͷΑΓྑ͍͖ ߹͍ํ͕Ͱ͖Δ͔͠Εͳ͍ɻ ͦΕҎ֎ͷਓʢͯ͢ͷਓʣ We have adapted our personalization algorithms to this new scenario in such a way that now 75% of what people watch is from some sort of recommendation. https://netflixtechblog.com/netflix-recommendations-beyond-the-5-stars-part-1-55838468f429 https://newsroom.tiktok.com/ja-jp/how-tiktok-recommends-videos
It is often necessary to make choices without sufficient personal experience of the alternatives. In everyday life, we rely on recommendations from other people either by word of mouth, recommendation letters, movie and book reviews printed in newspapers, or general surveys such as Zagat’s restaurant guides. Recommender systems assist and augment this natural social process. ਪનγεςϜͱ [Resnick+ 97] ࣗͷܦݧ͔ΒͷΈͰ͋·ΓΑ͘Θ͔Βͳ͍ͷͷத͔ΒɼͲ͏ ͯ͠ͲΕ͔Λબͳ͚ΕͳΒͳ͍ͱ͍͏͜ͱΑ͋͘Δɻ͜ͷ Α͏ͳࡍΘͨͨͪ͠ɼޱίϛɼਪનঢ়ɼ ৽ฉͷॻධөըධɼϨ ετϥϯΨΠυͳͲͷଞਓ͔ΒͷਪનʹཔΔ͜ͱΛৗతʹߦͬͯ ͍Δɻ ਪનγεςϜͱɼ͜͏ͨࣾ͠ձͰී௨ʹߦΘΕ͍ͯΔҰ࿈ ͷߦҝΛิॿͨ͠Γɼଅਐͨ͠Γ͢ΔͷͰ͋Δɻ [Resnick 97] P. Resnick and H. R. Varian. Recommender systems. Communications of the ACM, Vol. 40, No. 3, pp. 56–58, 1997.
Recommenders: Tools to help identify worthwhile stuff ਪનγεςϜͱ [Konstan+ 03] ਪનγεςϜ: ͲΕ͕Ձͷ͋Δͷ͔ಛఆ͢ΔͷΛॿ͚Δಓ۩ [Konstan 03] J. A. Konstan and J. Riedl. Recommender systems:
Collaborating in commerce and communities. In Proc. of the SIGCHI Conf. on Human Factors in Computing Systems, Tutorial, 2003.
Recommenders: Tools to help identify worthwhile stuff ࠶ܝɿਪનγεςϜͱ [Konstan+ 03] ਪનγεςϜ: ͲΕ͕Ձͷ͋Δͷ͔ಛఆ͢ΔͷΛॿ͚Δಓ۩ [Konstan 03] J. A. Konstan and J. Riedl. Recommender systems:
Collaborating in commerce and communities. In Proc. of the SIGCHI Conf. on Human Factors in Computing Systems, Tutorial, 2003.
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