Σύγκριση μεθόδων

	Εξαγωγή Πληροφορίας	Ταξινόμηση Κειμένου
Πεδίο	Εξόρυξη Κειμένου	Εξόρυξη Κειμένου
Οικογένεια	Process / pipeline	Process / pipeline
Έτος προέλευσης	—	—
Δημιουργός	—	—
Τύπος	NLP structured-information task	Supervised NLP classification task
Θεμελιώδης πηγή	Cowie, J. & Lehnert, W. (1996). Information Extraction. Communications of the ACM.	Joachims, T. (1998). Text Categorization with Support Vector Machines: Learning with Many Relevant Features. ECML 1998. Lecture Notes in Computer Science, vol 1398. Springer.
Εναλλακτικές ονομασίες	IE, structured information extraction, Bilgi Çıkarma (Information Extraction)	text categorization, document classification, topic classification, metin sınıflandırma
Συναφείς	4	4
Σύνοψη	Information extraction (IE) is a natural-language-processing task that converts unstructured text into structured information — such as events, relations, and attributes — so that facts buried in free-form documents become machine-readable records. The task was consolidated in early surveys by Cowie and Lehnert (1996) and later by Grishman (2012).	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.