Abstract
Guinaudeau and Strube (2013) introduce a graph based model to compute local entity coherence. We propose a computationally efficient normalization method for these graphs and then evaluate it on three tasks: sentence ordering, summary coherence rating and readability assessment. In all tasks normalization improves the results.
Cite
CITATION STYLE
APA
Mesgar, M., & Strube, M. (2014). Normalized entity graph for computing local coherence. In Proceedings of TextGraphs@EMNLP 2014: The 9th Workshop on Graph-Based Methods for Natural Language Processing (pp. 1–5). The Association for Computer Linguistics. https://doi.org/10.3115/v1/w14-3701
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