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๐Ÿ† KISTI 2022 ๊ณผํ•™๊ธฐ์ˆ  ๊ณต๊ณต AI ๋ฐ์ดํ„ฐ ๋ถ„์„ํ™œ์šฉ ๊ฒฝ์ง„๋Œ€ํšŒ ๊ตญํšŒ๋„์„œ๊ด€ ์žฅ๊ด€์ƒ(์žฅ๋ ค์ƒ, ์ƒ๊ธˆ 100๋งŒ์›) ์ˆ˜์ƒ

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Hierarchical loss, representation, and label embedding with plm classifier

๊ณ„์ธต์  loss ๋ฐ representation๊ณผ ๋ ˆ์ด๋ธ” ์ž„๋ฒ ๋”ฉ์„ ์ด์šฉํ•œ ๋…ผ๋ฌธ ๋ฌธ์žฅ ์ˆ˜์‚ฌํ•™์  ๋ถ„๋ฅ˜ ๋ชจ๋ธ(๊ตญ๋‚ด ๋…ผ๋ฌธ ๋ฌธ์žฅ ์˜๋ฏธ ํƒœ๊น… ๋ชจ๋ธ ๊ฐœ๋ฐœ)

๐Ÿ† KISTI 2022 ๊ณผํ•™๊ธฐ์ˆ  ๊ณต๊ณต AI ๋ฐ์ดํ„ฐ ๋ถ„์„ํ™œ์šฉ ๊ฒฝ์ง„๋Œ€ํšŒ ๊ตญํšŒ๋„์„œ๊ด€ ์žฅ๊ด€์ƒ(์žฅ๋ ค์ƒ, ์ƒ๊ธˆ 100๋งŒ์›) ์ˆ˜์ƒ

๊ตญํฌ์ง„: ๋ชจ๋ธ๋ง, ์ „์ฒด ์ฝ”๋“œ ์ž‘์„ฑ
๊น€์˜ํ™”: ๋ชจ๋ธ๋ง
์œค์„ธํœ˜: ๋ฐ์ดํ„ฐ ์ „์ฒ˜๋ฆฌ, ์›น ํŽ˜์ด์ง€
๊ฐ•๋ณ‘ํ•˜: ์›น ํŽ˜์ด์ง€


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1. Model

1.1. ์ „์ฒด ๋ชจ๋ธ ๊ตฌ์กฐ

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1.2. ์‚ฌ์ „ ํ•™์Šต ๋ชจ๋ธ์„ ํ™œ์šฉํ•œ ๋ ˆ์ด๋ธ” ์ž„๋ฒ ๋”ฉ ํ…Œ์ด๋ธ”

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  • ์‚ฌ์ „ ํ•™์Šต ์–ธ์–ด๋ชจ๋ธ(KorSciBERT)์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ ˆ์ด๋ธ” ์ž„๋ฒ ๋”ฉ ํ…Œ์ด๋ธ” ์ดˆ๊ธฐํ™”
  • ํ•™์Šต๊ณผ ํ•จ๊ป˜ ๋ ˆ์ด๋ธ” ์ž„๋ฒ ๋”ฉ ํ…Œ์ด๋ธ”๊ณผ BiLSTM ๋ ˆ์ด์–ด ํŒŒ๋ผ๋ฏธํ„ฐ ์—…๋ฐ์ดํŠธ

1.3. ๊ณ„์ธต์  ์†์‹คํ•จ์ˆ˜

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  • Deep Hierarchical Classification for Category Prediction in E-commerce System(ACL 2020 ECNLP3) ์ฐธ๊ณ 
  • ๊ณ„์ธต์  ์†์‹ค ํ•จ์ˆ˜๋ฅผ ํ†ตํ•ด ๋Œ€๋ถ„๋ฅ˜ ๋ฐ ์†Œ๋ถ„๋ฅ˜ ์นดํ…Œ๊ณ ๋ฆฌ ์˜ˆ์ธก ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ
  • ์ƒ์œ„ ์นดํ…Œ๊ณ ๋ฆฌ์™€ ํ•˜์œ„ ์นดํ…Œ๊ณ ๋ฆฌ ์‚ฌ์ด์˜ ๊ตฌ์กฐ ํ•™์Šต ๊ฐ€๋Šฅ
    • Layer loss(Lloss)
      • ์ƒ์œ„/ํ•˜์œ„ ์นดํ…Œ๊ณ ๋ฆฌ ์˜ˆ์ธก๊ฐ’์— ๋Œ€ํ•œ ์†์‹ค๊ฐ’
    • Dependence loss(Dloss)
      • ์˜ˆ์ธกํ•œ ์ƒ์œ„, ํ•˜์œ„ ์นดํ…Œ๊ณ ๋ฆฌ๊ฐ€ ์„œ๋กœ ํฌํ•จ ๊ด€๊ณ„๊ฐ€ ์•„๋‹Œ ๊ฒฝ์šฐ ํŒจ๋„ํ‹ฐ ๋ถ€์—ฌ

2. Performance

2.1. ์„น์…˜๋ช…(์œ„์น˜ ์ •๋ณด) ์‚ฌ์šฉํ•˜์ง€ ์•Š์•˜์„ ๊ฒฝ์šฐ

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2.2. ์„น์…˜๋ช…(์œ„์น˜ ์ •๋ณด) ์‚ฌ์šฉํ•˜์˜€์„ ๊ฒฝ์šฐ

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3. References

About

๐Ÿ† KISTI 2022 ๊ณผํ•™๊ธฐ์ˆ  ๊ณต๊ณต AI ๋ฐ์ดํ„ฐ ๋ถ„์„ํ™œ์šฉ ๊ฒฝ์ง„๋Œ€ํšŒ ๊ตญํšŒ๋„์„œ๊ด€ ์žฅ๊ด€์ƒ(์žฅ๋ ค์ƒ, ์ƒ๊ธˆ 100๋งŒ์›) ์ˆ˜์ƒ

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