stemmingstype
Stemmingstype is a term used in computational linguistics to classify stemming approaches by how they reduce words to their base forms. It emphasizes the trade-offs among speed, accuracy, and linguistic resource requirements. Stemmingstype can be understood along several axes: aggressiveness (how aggressively affixes are removed), the basis of the method (rule-based, dictionary-based, or statistical/learned), and language orientation (language-specific versus language-agnostic).
Rule-based stemmers apply a fixed set of transformation rules to strip inflectional suffixes. They are typically
Stemmingstype is complementary to lemmatization, which aims for canonical dictionary forms and often uses part-of-speech information
Applications include information retrieval, search engines, and text mining, where reducing word forms to a common
See also: stemming, lemmatization, information retrieval, natural language processing.