Σύγκριση μεθόδων

	Μοντέλο Γλώσσας N-gram	Παλινδρόμηση Κειμένου
Πεδίο	Εξόρυξη Κειμένου	Εξόρυξη Κειμένου
Οικογένεια	Process / pipeline	Process / pipeline
Έτος προέλευσης	—	—
Δημιουργός	—	—
Τύπος	Statistical language model	Supervised regression on text features
Θεμελιώδης πηγή	Jurafsky, D. & Martin, J.H. (2023). Speech and Language Processing, 3rd ed.	Gentzkow, M., Kelly, B. & Taddy, M. (2019). Text as Data. Journal of Economic Literature, 57(3), 535-574.
Εναλλακτικές ονομασίες	n-gram model, statistical language model, N-gram Dil Modeli	text-as-data regression, predicting numeric outcomes from text, Metin Tabanlı Regresyon
Συναφείς	4	4
Σύνοψη	An n-gram language model is a statistical model that predicts the probability of the next word by looking only at the previous n−1 words. Described in detail by Jurafsky and Martin (Speech and Language Processing), it provides foundational infrastructure for text generation, spelling correction, and speech recognition.	Text-based regression predicts a continuous target variable using features extracted from text — TF-IDF scores, embeddings, or n-grams — as the independent variables. Building on the text-as-data programme consolidated by Gentzkow, Kelly and Taddy (2019), it lets a numeric outcome such as a price, a rating, or a sentiment score be estimated directly from documents, and is widely used in social-science, economics, and finance applications.