方法证据记录
Text Coherence Scoring
Text coherence scoring computes a document-level coherence score with machine learning, rooted in the entity-based local coherence model introduced by Barzilay and Lapata (2008). It measures how well the sentences of a text hang together, using either an entity-grid model, a graph-based approach, or a transformer-based model.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Text Coherence Scoring (Local Coherence Modeling)
分类方法记录 · process-pipeline / text-mining
- Barzilay, R. & Lapata, M. (2008). Modeling Local Coherence: An Entity-Based Approach. Computational Linguistics, 34(1), 1-34. · DOI 10.1162/coli.2008.34.1.1
- Guinaudeau, C. & Strube, M. (2013). Graph-based Local Coherence Modeling. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL), 93-103. · URL
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