2017
EACL
EACL 2017
The Content Types Dataset: a New Resource to Explore Semantic and Functional Characteristics of Texts
Abstract
AbstractThis paper presents a new resource, called Content Types Dataset, to promote the analysis of texts as a composition of units with specific semantic and functional roles. By developing this dataset, we also introduce a new NLP task for the automatic classification of Content Types. The annotation scheme and the dataset are described together with two sets of classification experiments.
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Interdisciplinary Bridge
— Data Science & Analytics and Interdisciplinary and Machine Learning and Natural Language Processing
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Keyword Pioneer
— annotation scheme
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Hot Topic Early Bird
— dataset creation
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Core Methods > Classification
Natural Language Processing > Understanding > Semantic Analysis
Natural Language Processing > Applications > Text Classification
Natural Language Processing > Resources & Methods > Text Representation
Interdisciplinary > Linguistics > Computational Linguistics
Data Science & Analytics > Applications > Information Retrieval