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Prezrite si vybrané metódy vedľa seba; riadky, ktoré sa líšia, sú zvýraznené.
| Ťažba argumentov× | Klasifikácia textu× | |
|---|---|---|
| Odbor | Dolovanie textu | Dolovanie textu |
| Rodina | Process / pipeline | Process / pipeline |
| Rok vzniku≠ | 2016 | — |
| Tvorca≠ | Lippi & Torroni (state-of-the-art survey) | — |
| Typ≠ | NLP information-extraction task | Supervised NLP classification task |
| Pôvodný zdroj≠ | Lippi, M. & Torroni, P. (2016). Argumentation Mining: State of the Art and Emerging Trends. ACM Transactions on Internet Technology, 16(2), Article 10, 1-25. DOI ↗ | 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 ↗ |
| Ďalšie názvy≠ | argumentation mining, argument extraction, Argüman Madenciliği | text categorization, document classification, topic classification, metin sınıflandırma |
| Príbuzné | 4 | 4 |
| Zhrnutie≠ | Argument mining is a natural-language-processing task that automatically detects claims, premises and the argumentative structures that link them within text. Consolidated as a field by Lippi and Torroni's 2016 state-of-the-art survey, it is applied to scientific writing, legal documents and debate analysis to turn free-form argumentation into structured, analysable units. | 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. |
| ScholarGateDátová sada ↗ |
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