Linganisha mbinu

	Uchanganuzi wa Hati	TF-IDF
Nyanja	Uchimbaji wa Matini	Uchimbaji wa Matini
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	—	1988
Mwanzilishi	—	Salton & Buckley
Aina	Unsupervised text-mining task	Text vectorization / term-weighting scheme
Chanzo asilia	Aggarwal, C. C. & Zhai, C. (2012). Mining Text Data. Springer. ISBN: 9781461432227	Salton, G. & Buckley, C. (1988). Term-weighting approaches in automatic text retrieval. Information Processing & Management, 24(5), 513-523.
Majina mbadala	text clustering, unsupervised text grouping, Belge Kümeleme (Document Clustering)	term weighting, tf-idf weighting, TF-IDF Vektörizasyonu
Zinazohusiana	4	3
Muhtasari	Document clustering is an unsupervised text-mining task that groups documents with similar content together without using any labels. It is used to organise large collections and for exploratory analysis, drawing on the body of text-mining techniques consolidated by Aggarwal and Zhai (2012) and compared empirically by Steinbach, Karypis and Kumar (2000).	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.