October 2022
Beginner to intermediate
504 pages
12h 57m
Korean
Content preview from 파이썬 라이브러리를 활용한 텍스트 분석
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327
9
장
텍스트 요약
이 방법은
TF
-
IDF
값을 사용해 텍스트의 중간 표현을 만들고, 이를 기반으로 문장에 점수를
매긴 후 점수가 가장 높은 세 문장을 선택했다. 이 방법으로 선택한 문장은 이전에 수동으로 작
성한 요약과 일치하고 기사에서 다루는 주요 요점을 포착했다. 업계에서 퀄컴
Qualcomm
의 중요
성 및
5G
기술의 특정 응용 프로그램 같은 일부 뉘앙스가 누락되었다. 그러나 이 방법은 중요
한 문장을 빠르게 식별하고 뉴스 기사의 요약을 자동으로 생성하는 좋은 전략이다. 이 부분을
tfidf
_
summary
함수로 래핑하겠다. 이 함수는 예시 코드 노트북에 정의되었으며 이 장의 뒷
부분에서 재사용하니 참고하자.
9.3.2
LSA
알고리즘
추출 기반 요약에 사용되는 최신 방법 하나는 잠재 의미 분석
latent
semantic
analysis
(
LSA
)이다.
LSA
는 토픽 모델링, 문서 유사성 및 기타 작업에 사용되는 범용 알고리즘이다.
LSA
는 의미가
비슷한 단어가 동일한 문서에 등장할 것이라고 가정한다. 먼저
LSA
알고리즘에서는 전체 기사
를 문장-용어 행렬의 형태로 나타낸다. 문서-용어 행렬의 개념은
8
장에 소개했으며 문장-용
어 행렬에 맞게 개념을 조정할 수 있다. 각 행은 문장을 나타내고 각 열은 단어를 나타낸다. 이
행렬의 각 칸 값은 종종
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.