(ͦΕΛͬͯ)ࣄલֶशࡁΈͷ୯ޠࢄදݱ • Կ͔͠Βͷରͷૉੑ(৽ޠɾsynsetͳͲ) ͱͦͷग़ݱจ຺ Λ༩͑ͯɺରૉੑͷࢄදݱ Λon the flyͰ֫ಘ CV vw f Cf V w Cw vf beef up the army we must beef up our organization … v(beef,up) Cf
(ͨͩ͠ ֶश͞ΕΔࣸ૾ύϥϝʔλ) • ಋग़͞ΕΔ ͋Γ͖ͨΓͳํ (common wordͷํ) Λshrinkͤ͞Δಇ͖͕͋Δ[Arora+. 2018] • ดܗࣜͰ࠷దԽͰ͖ΔͷͰಛʹ༨ܭͳνϡʔχϯά͍Βͳ͍ ͨͩ͠ɺίʔύεͷසͰॏΈ͚͢ΔͳͲ͍ͯ͠Δ vw ⇡ Avadditive w = A ✓ 1 |Cw | X c2Cw X w02c vw0 ◆ A A
CorpusͰGloveΛֶशޙ ಉίʔύεͰn-gramͷࢄදݱΛߏங • จ຺ͷࢄදݱͷߏங࣌ͷwindowαΠζ10 • ҎԼࣜͰn-gramͷࢄදݱ͔ΒจॻͷࢄදݱΛ֫ಘޙ, ϩδεςΟοΫճؼͰ༧ଌ ※ n͕େ͖͍ͱจ຺͕গͳ࣭͘తʹඍົͳͷͰnͰׂΔ vT D = L X t=1 vT wt . . . 1 n L n+1 X t=1 vT (wt,...,wL+n 1)
and Andrej Risteski. 2018. Linear algebraic structure of word senses, with applications to polysemy. TACL • Sanjeev Arora, Yingyu Liang, and Tengyu Ma. 2017. A simple but tough-to- beat baseline for sentence embeddings. In Proc. ICLR. • Angeliki Lazaridou, Marco Marelli, and Marco Baroni. 2017. Multimodal word meaning induction from minimal exposure to natural text. Cognitive Science. • Jiaqi Mu and Pramod Viswanath. 2018. All-but-thetop: Simple and effective post-processing for word representations. In Proc. ICLR. • Alessandro Raganato, Claudio Delli Bovi, and Roberto Navigli. 2017. Neural sequence learning models for word sense disambiguation. In Proc. EMNLP.