Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uchanganuzi wa Wigo× | Uainishaji wa Maandishi× | |
|---|---|---|
| Nyanja≠ | Utafiti wa Kimaelezo | Uchimbaji wa Matini |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1989 (Fairclough); 1987 (Potter & Wetherell) | — |
| Mwanzilishi≠ | Norman Fairclough; Jonathan Potter and Margaret Wetherell | — |
| Aina≠ | Method | Supervised NLP classification task |
| Chanzo asilia≠ | Fairclough, N. (1989). Language and power. Longman. 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 ↗ |
| Majina mbadala≠ | DA, Critical Discourse Analysis, Discursive Analysis | text categorization, document classification, topic classification, metin sınıflandırma |
| Zinazohusiana≠ | 2 | 4 |
| Muhtasari≠ | Discourse analysis is a qualitative research methodology that examines how language, communication, and power shape meaning, identity, and social reality. Developed across linguistics, sociology, and psychology (particularly by Norman Fairclough and Jonathan Potter), discourse analysis goes beyond content to analyze language use as a social practice that constitutes and reflects power relations, ideologies, and social structures. | 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. |
| ScholarGateSeti ya data ↗ |
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