विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| पार्ट-ऑफ-स्पीच टैगिंग (POS टैगिंग)× | रूप-विश्लेषण× | |
|---|---|---|
| क्षेत्र | पाठ खनन | पाठ खनन |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | — | 1980 |
| प्रवर्तक≠ | — | M.F. Porter (Porter stemmer) |
| प्रकार≠ | NLP sequence-labelling task | Text-normalisation preprocessing task |
| मौलिक स्रोत≠ | Ratnaparkhi, A. (1996). A Maximum Entropy Model for Part-Of-Speech Tagging. EMNLP. link ↗ | Porter, M.F. (1980). An Algorithm for Suffix Stripping. Program, 14(3), 130-137. DOI ↗ |
| उपनाम | part-of-speech tagging, grammatical tagging, Sözcük Türü Etiketleme (POS Tagging) | stemming, lemmatization, Morfolojik Analiz ve Kök Bulma |
| संबंधित≠ | 3 | 4 |
| सारांश≠ | Part-of-speech tagging assigns a grammatical category label — noun, verb, adjective, and so on — to every word in a text. It is a foundational natural-language-processing task, formalised as a statistical model by Ratnaparkhi (1996) and packaged into widely used toolkits such as Stanford CoreNLP (Manning et al., 2014), and it serves as a preliminary step for syntactic analysis and information extraction. | Morphological 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. |
| ScholarGateडेटासेट ↗ |
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