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Found 3 papers, 1 papers with code
Abstractive Text Summarization: Enhancing Sequence-to-Sequence Models Using Word Sense Disambiguation and Semantic Content Generalization
Abstract Nowadays, most research conducted in the field of abstractive text summarization focuses on neural-based models alone, without considering their combination with knowledge-based approaches that could further enhance their efficiency.
Abstractive Text Summarization Based on Deep Learning and Semantic Content Generalization
This work proposes a novel framework for enhancing abstractive text summarization based on the combination of deep learning techniques along with semantic data transformations.
Fixed Similes: Measuring aspects of the relation between MWE idiomatic semantics and syntactic flexibility
We shed light on aspects of the relation between the semantics and the syntactic flexibility of multiword expressions by investigating fixed adjective similes (FS), a predicative multiword expression class not studied in this respect before.
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