Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Morfoloģiskā analīze× | Valodu identifikācija (LID)× | |
|---|---|---|
| Nozare | Teksta ieguve | Teksta ieguve |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 1980 | — |
| Autors≠ | M.F. Porter (Porter stemmer) | — |
| Tips≠ | Text-normalisation preprocessing task | NLP text-classification task |
| Pirmavots≠ | Porter, M.F. (1980). An Algorithm for Suffix Stripping. Program, 14(3), 130-137. DOI ↗ | Lui, M. & Baldwin, T. (2012). langid.py: An Off-the-shelf Language Identification Tool. Proceedings of the ACL 2012 System Demonstrations. link ↗ |
| Citi nosaukumi | stemming, lemmatization, Morfolojik Analiz ve Kök Bulma | language detection, LID, Dil Tanımlama (Language Identification) |
| Saistītās | 4 | 4 |
| Kopsavilkums≠ | 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. | Language identification is a natural-language-processing task that automatically detects which language a piece of text is written in. Building on off-the-shelf tools such as langid.py (Lui & Baldwin, 2012) and the efficient classifiers of Joulin et al. (2017), it is widely used to preprocess and filter multilingual data sets. |
| ScholarGateDatu kopa ↗ |
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