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| Abhängigkeitsanalyse× | Lexikalische Diversität – Messung des Wortschatzreichtums× | |
|---|---|---|
| Fachgebiet | Text Mining | Text Mining |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr | — | — |
| Urheber | — | — |
| Typ≠ | NLP syntactic-analysis task | Text quantification / lexical richness measurement |
| Wegweisende Quelle≠ | Nivre, J. (2005). Dependency Grammar and Dependency Parsing. MSI Report. link ↗ | McCarthy, P. M. & Jarvis, S. (2010). MTLD, vocd-D, and HD-D: A validation study of sophisticated approaches to lexical diversity assessment. Behavior Research Methods, 42(2), 381-392. DOI ↗ |
| Aliasnamen | syntactic dependency analysis, dependency tree parsing, Bağımlılık Ayrıştırma (Dependency Parsing) | lexical richness, vocabulary richness, Sözcüksel Çeşitlilik Analizi |
| Verwandt | 3 | 3 |
| Zusammenfassung≠ | Dependency parsing is a natural-language-processing task that reveals the syntactic dependency relations between the words of a sentence as a tree structure. Surveyed in the dependency-grammar tradition by Nivre (2005) and made fast and accurate with neural networks by Chen and Manning (2014), it is commonly used as a prerequisite step for information extraction and relation detection. | Lexical diversity analysis quantifies how varied the vocabulary of a text is — how rich an author's word choice is — using measures such as the type-token ratio (TTR), MTLD, vocd-D, and Yule's K. The MTLD and vocd-D measures were validated by McCarthy and Jarvis (2010), building on earlier work by Tweedie and Baayen (1998) on the stability of lexical-richness measures. |
| ScholarGateDatensatz ↗ |
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