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Found 5 papers, 1 papers with code
Context-Aware Automatic Text Simplification of Health Materials in Low-Resource Domains
We also show the enhanced accuracy of our system over directly-supervised neural methods in this low-resource setting.
Equipping Educational Applications with Domain Knowledge
One of the challenges of building natural language processing (NLP) applications for education is finding a large domain-specific corpus for the subject of interest (e. g., history or science).
Document Similarity for Texts of Varying Lengths via Hidden Topics
This is because of the lexical, contextual and the abstraction gaps between a long document of rich details and its concise summary of abstract information.
Fixing the Infix: Unsupervised Discovery of Root-and-Pattern Morphology
We present an unsupervised and language-agnostic method for learning root-and-pattern morphology in Semitic languages.
MORSE: Semantic-ally Drive-n MORpheme SEgment-er
We present in this paper a novel framework for morpheme segmentation which uses the morpho-syntactic regularities preserved by word representations, in addition to orthographic features, to segment words into morphemes.
