๐Ÿ” 4. ๊ฒ€์ƒ‰์˜ ์žฌํ˜„์œจ, Relevance Feedback

๊น€์ง€์œคยท2023๋…„ 10์›” 22์ผ
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์ •๋ณด๊ฒ€์ƒ‰

๋ชฉ๋ก ๋ณด๊ธฐ
4/11

๐Ÿ” ์žฌํ˜„์œจ์„ ๋†’์ด๋Š” Relevance Feedback

  • ์‚ฌ์šฉ์ด์œ  : ๊ฐ™์€ ์˜๋ฏธ๋ฅผ ๊ฐ€์ง„ ๋‹ค๋ฅธ ๋‹จ์–ด๋„ ๊ฒ€์ƒ‰์ด ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜๊ธฐ์œ„ํ•ด

  • ๊ฒฐ๊ณผ ๋ฌธ์„œ๋“ค์„ ์ˆœ์„œ๋Œ€๋กœ ํƒ์ƒ‰ํ•˜๋ฉฐ ๊ด€๋ จ์žˆ๋Š”์ง€, ์—†๋Š”์ง€ ์ง์ ‘ ์ฒดํฌ

  • ๊ทธ ๊ฒฐ๊ณผ๋ฅผ ๊ฐ€์ง€๊ณ  ๋‹ค์‹œ ๊ฒ€์ƒ‰ํ•˜์—ฌ ๋ณด์—ฌ์คŒ

    -> (Relavance Feedback์œผ๋กœ ์ธํ•œ ๋ณ€ํ™”)

  • Centroid :

    • ๊ฒฐ๊ณผ ๋ฌธ์„œ๋“ค์˜ ์ œ์ผ ๊ฐ€์šด๋ฐ์— ์ ์„ ์ฐ์€ ๊ฒƒ



๐Ÿ” Rocchio algorithm

  • ์ •๋‹ต์ธ ๋ฌธ์„œ๋“ค์˜ centroid + (์ •๋‹ต์ธ ๋ฌธ์„œ๋“ค์˜ centroid - ์ •๋‹ต์ด ์•„๋‹Œ ๋ฌธ์„œ๋“ค์˜ centroid)



๐Ÿ” Relavance Feedback์˜ ๋ฌธ์ œ์ 

  • ์‚ฌ์šฉ์ž๊ฐ€ ์ผ์ผ์ด ์ฒดํฌํ•ด์•ผ ํ•œ๋‹ค.



๐Ÿ” ํ•ด๊ฒฐ์ฑ… : Pseudo-relevance feedback

  • ๊ฒ€์ƒ‰ ๊ฒฐ๊ณผ ์ƒ์œ„ k๊ฐœ์˜ ๋ฌธ์„œ๊ฐ€ ๊ด€๋ จ์„ฑ์ด ๋†’๋‹ค๊ณ  ํŒ๋‹จํ•˜๊ณ , ๋‹ค์‹œ ๊ฒ€์ƒ‰ ๊ฒฐ๊ณผ๋ฅผ ๋„์ถœํ•œ๋‹ค.
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๊พธ์ค€ํ•˜๊ฒŒ ๊ณต๋ถ€ํ•˜๊ณ  ๊ธฐ๋กํ•˜๋Š” ๊ฐœ๋ฐœ์ž

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