Compară metode

	Extragerea cuvintelor cheie	Analiza lizibilității	TF-IDF
Domeniu	Mineritul textelor	Mineritul textelor	Mineritul textelor
Familie	Process / pipeline	Process / pipeline	Process / pipeline
Anul apariției	—	1975	1988
Autorul original	—	J. Peter Kincaid et al.	Salton & Buckley
Tip	NLP text-mining task	Text-mining readability scoring task	Text vectorization / term-weighting scheme
Sursa seminală	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.	Salton, G. & Buckley, C. (1988). Term-weighting approaches in automatic text retrieval. Information Processing & Management, 24(5), 513-523.
Denumiri alternative	keyphrase extraction, key term extraction, Anahtar Kelime Çıkarma (Keyword Extraction)	readability scoring, readability formulas, Flesch-Kincaid analysis, Okunabilirlik Analizi	term weighting, tf-idf weighting, TF-IDF Vektörizasyonu
Înrudite	4	3	3
Rezumat	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.	TF-IDF, introduced by Salton and Buckley (1988), is a term-weighting scheme that scores each word in a document by how often it appears there and how rare it is across the whole collection. It turns raw text into weighted document vectors, giving high weight to terms that are frequent in one document but uncommon elsewhere.