قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| وسم أجزاء الكلام (POS Tagging)× | تحليل صرفي× | |
|---|---|---|
| المجال | تنقيب النصوص | تنقيب النصوص |
| العائلة | Process / pipeline | Process / pipeline |
| سنة النشأة≠ | — | 1980 |
| صاحب الطريقة≠ | — | M.F. Porter (Porter stemmer) |
| النوع≠ | NLP sequence-labelling task | Text-normalisation preprocessing task |
| المصدر التأسيسي≠ | 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 ↗ |
| الأسماء البديلة | part-of-speech tagging, grammatical tagging, Sözcük Türü Etiketleme (POS Tagging) | stemming, lemmatization, Morfolojik Analiz ve Kök Bulma |
| ذات صلة≠ | 3 | 4 |
| الملخص≠ | 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. |
| ScholarGateمجموعة البيانات ↗ |
|
|