विधियों की तुलना करें

	इरादा पहचान	पाठ वर्गीकरण
क्षेत्र	पाठ खनन	पाठ खनन
परिवार	Process / pipeline	Process / pipeline
उद्भव वर्ष	—	—
प्रवर्तक	—	—
प्रकार	NLP / NLU text-classification task	Supervised NLP classification task
मौलिक स्रोत	Larson, S. et al. (2019). An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction. EMNLP.	Joachims, T. (1998). Text Categorization with Support Vector Machines: Learning with Many Relevant Features. ECML 1998. Lecture Notes in Computer Science, vol 1398. Springer.
उपनाम	intent classification, intent recognition, Niyet Tespiti (Intent Detection)	text categorization, document classification, topic classification, metin sınıflandırma
संबंधित	4	4
सारांश	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).	Text classification, also called text categorization, is a supervised natural-language-processing task that automatically assigns documents to predefined categories. Building on the support-vector-machine approach to text categorization established by Joachims (1998) and consolidated in the text-mining literature by Aggarwal and Zhai (2012), it powers tasks such as spam detection and topic classification by learning from labelled examples.