방법 비교

	키워드 추출	가독성 분석
분야	텍스트 마이닝	텍스트 마이닝
계열	Process / pipeline	Process / pipeline
기원 연도	—	1975
창시자	—	J. Peter Kincaid et al.
유형	NLP text-mining task	Text-mining readability scoring task
원전	Mihalcea, R. & Tarau, P. (2004). TextRank: Bringing Order into Texts. EMNLP, 404-411.	Kincaid, J.P., Fishburne, R.P., Rogers, R.L. & Chissom, B.S. (1975). Derivation of New Readability Formulas for Navy Enlisted Personnel. Naval Technical Training Command.
별칭	keyphrase extraction, key term extraction, Anahtar Kelime Çıkarma (Keyword Extraction)	readability scoring, readability formulas, Flesch-Kincaid analysis, Okunabilirlik Analizi
관련	4	3
요약	Keyword extraction is a natural-language-processing task that automatically identifies the words or phrases that best represent the content of a document. It turns a body of free text into a compact, ranked list of key terms, drawing on statistical, graph-based methods such as TextRank (Mihalcea & Tarau, 2004), or embedding-based methods such as KeyBERT (Grootendorst, 2020).	Readability analysis measures how well a text suits its intended audience by applying established readability formulas such as Flesch-Kincaid and Gunning Fog. The modern formula family was derived by Kincaid and colleagues in 1975, and it turns prose into a single score or target reading-grade level that signals how easy the text is to read.