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Anàlisi morfològica×Anàlisi de sentiments×TF-IDF×
CampMineria de textMineria de textMineria de text
FamíliaProcess / pipelineProcess / pipelineProcess / pipeline
Any d'origen19801988
Autor originalM.F. Porter (Porter stemmer)Salton & Buckley
TipusText-normalisation preprocessing taskNLP text-classification taskText vectorization / term-weighting scheme
Font seminalPorter, M.F. (1980). An Algorithm for Suffix Stripping. Program, 14(3), 130-137. DOI ↗Pang, B. & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval, 2(1-2), 1-135. DOI ↗Salton, G. & Buckley, C. (1988). Term-weighting approaches in automatic text retrieval. Information Processing & Management, 24(5), 513-523. DOI ↗
Àliesstemming, lemmatization, Morfolojik Analiz ve Kök Bulmaopinion mining, polarity detection, duygu analiziterm weighting, tf-idf weighting, TF-IDF Vektörizasyonu
Relacionats433
ResumMorphological analysis splits words into their stems and affixes so that different surface forms of the same word can be treated as one. It covers two complementary approaches — rule-based stemming, such as the Porter (1980) and Snowball algorithms, and dictionary-aware lemmatization — and is a critical text-normalisation step for agglutinative languages such as Turkish and Arabic.Sentiment analysis, also called opinion mining, is a natural-language-processing task that detects the emotional tone of text — typically classifying it as positive, negative, or neutral. It turns unstructured opinion text into structured, quantifiable polarity signals using one of three families of approaches: sentiment lexicons, trained machine-learning classifiers, or pretrained transformer models.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.
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ScholarGateCompara mètodes: Morphological Analysis · Sentiment Analysis · TF-IDF. Recuperat el 2026-06-17 de https://scholargate.app/ca/compare