Introduces a fuzzy hypergraph using topical sentence representations and submodular optimization to select sentences maximizing query relevance, centrality, and topic coverage for extractive summarization.
Pedregosa et al., Scikit-learn: Machine learning in Python, Journal of Machine Learning Research, 12 (2011) 2825-2830
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Learning with fuzzy hypergraphs: a topical approach to query-oriented text summarization
Introduces a fuzzy hypergraph using topical sentence representations and submodular optimization to select sentences maximizing query relevance, centrality, and topic coverage for extractive summarization.