Compara mètodes

	Detecció d'intencions	Anàlisi de sentiments
Camp	Mineria de text	Mineria de text
Família	Process / pipeline	Process / pipeline
Any d'origen	—	—
Autor original	—	—
Tipus	NLP / NLU text-classification task	NLP text-classification task
Font seminal	Larson, S. et al. (2019). An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction. EMNLP.	Pang, B. & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval, 2(1-2), 1-135.
Àlies	intent classification, intent recognition, Niyet Tespiti (Intent Detection)	opinion mining, polarity detection, duygu analizi
Relacionats	4	3
Resum	Intent detection is a natural-language-understanding task that classifies the purpose behind a user utterance — such as making a reservation, asking for information, or filing a complaint — into one of a set of predefined intent classes. It is a core NLU component of conversational interfaces and customer-service automation systems, drawing on the benchmarks of Larson et al. (2019) and Casanueva et al. (2020).	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.