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Multi-sense embeddings through a word sense disambiguation process ...
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Abstract:
Natural Language Understanding has seen an increasing number of publications in the last few years, especially after robust word embeddings models became prominent, when they proved themselves able to capture and represent semantic relationships from massive amounts of data. Nevertheless, traditional models often fall short in intrinsic issues of linguistics, such as polysemy and homonymy. Any expert system that makes use of natural language in its core, can be affected by a weak semantic representation of text, resulting in inaccurate outcomes based on poor decisions. To mitigate such issues, we propose a novel approach called Most Suitable Sense Annotation (MSSA), that disambiguates and annotates each word by its specific sense, considering the semantic effects of its context. Our approach brings three main contributions to the semantic representation scenario: (i) an unsupervised technique that disambiguates and annotates words by their senses, (ii) a multi-sense embeddings model that can be extended to ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.2101.08700 https://arxiv.org/abs/2101.08700
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Detecting Cross-Language Plagiarism using Open Knowledge Graphs ...
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Detecting Cross-Language Plagiarism using Open Knowledge Graphs ...
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Detecting Cross-Language Plagiarism using Open Knowledge Graphs ...
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Detecting Cross-Language Plagiarism using Open Knowledge Graphs ...
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Detecting Cross-Language Plagiarism using Open Knowledge Graphs ...
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Detecting Cross-Language Plagiarism using Open Knowledge Graphs ...
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Incorporating Word Sense Disambiguation in Neural Language Models ...
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Enhanced word embeddings using multi-semantic representation through lexical chains ...
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Enhanced word embeddings using multi-semantic representation through lexical chains ...
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Semantic Feature Extraction Using Multi-Sense Embeddings and Lexical Chains
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Multi-sense Embeddings through a Word Sense Disambiguation Process
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Semantic-Based Document Retrieval Using Spatial Distributions of Concepts ...
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Exploring and Expanding the Use of Lexical Chains in Information Retrieval
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