Methoden vergleichen

	Kookkurrenzanalyse	Schlagwortextraktion
Fachgebiet	Text Mining	Text Mining
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1957	—
Urheber	J.R. Firth (distributional principle)	—
Typ	Text-mining / distributional-semantics technique	NLP text-mining task
Wegweisende Quelle	Firth, J.R. (1957). A Synopsis of Linguistic Theory. Studies in Linguistic Analysis. Oxford: Blackwell.	Mihalcea, R. & Tarau, P. (2004). TextRank: Bringing Order into Texts. EMNLP, 404-411.
Aliasnamen	word co-occurrence, co-occurrence network, Kelime Eş-Oluşum Analizi	keyphrase extraction, key term extraction, Anahtar Kelime Çıkarma (Keyword Extraction)
Verwandt	4	4
Zusammenfassung	Co-occurrence analysis is a text-mining technique that statistically counts the word pairs that appear together within a window or a sentence and uses their frequencies to reveal semantic maps and thematic structure. It rests on the distributional principle articulated by J.R. Firth in 1957 — that a word is characterised by the company it keeps.	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).