Methoden vergleichen
Prüfen Sie die ausgewählten Methoden nebeneinander; abweichende Zeilen sind hervorgehoben.
| Sprachidentifikation (LID)× | Textklassifizierung× | |
|---|---|---|
| Fachgebiet | Text Mining | Text Mining |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr | — | — |
| Urheber | — | — |
| Typ≠ | NLP text-classification task | Supervised NLP classification task |
| Wegweisende Quelle≠ | 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 ↗ |
| Aliasnamen≠ | language detection, LID, Dil Tanımlama (Language Identification) | text categorization, document classification, topic classification, metin sınıflandırma |
| Verwandt | 4 | 4 |
| Zusammenfassung≠ | 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. |
| ScholarGateDatensatz ↗ |
|
|