Võrdle meetodeid
Vaata valitud meetodeid kõrvuti; erinevad read on esile tõstetud.
| Keel(t)e tuvastamine (LID)× | Teksti klassifitseerimine× | |
|---|---|---|
| Valdkond | Tekstikaeve | Tekstikaeve |
| Perekond | Process / pipeline | Process / pipeline |
| Tekkeaasta | — | — |
| Looja | — | — |
| Tüüp≠ | NLP text-classification task | Supervised NLP classification task |
| Algallikas≠ | Lui, M. & Baldwin, T. (2012). langid.py: An Off-the-shelf Language Identification Tool. Proceedings of the ACL 2012 System Demonstrations. link ↗ | Joachims, T. (1998). Text Categorization with Support Vector Machines: Learning with Many Relevant Features. ECML 1998. Lecture Notes in Computer Science, vol 1398. Springer. DOI ↗ |
| Rööpnimetused≠ | language detection, LID, Dil Tanımlama (Language Identification) | text categorization, document classification, topic classification, metin sınıflandırma |
| Seotud | 4 | 4 |
| Kokkuvõte≠ | 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. | 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. |
| ScholarGateAndmestik ↗ |
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