Teaching GuideTerm Faculty of Computer Science |
Grao en Ciencia e Enxeñaría de Datos |
Subjects |
Natural Language Processing and Text Mining |
Contents |
Identifying Data | 2024/25 | |||||||||||||
Subject | Natural Language Processing and Text Mining | Code | 614G02043 | |||||||||||
Study programme |
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Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
Graduate | 2nd four-month period |
Fourth | Optional | 6 | ||||||||||
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Topic | Sub-topic |
Constituent parsing for text mining | Syntax of constituents Statistical constituent analysis with dynamic programming Analysis of shift-reduce constituents with neural networks Analysis of discontinuous constituents Sequence-by-sequence constituent analysis |
Dependency parsing for text mining |
Dependency Syntax Annotation criteria and universal dependencies Dependency analysis based on transitions Analysis of dependencies based on graphs Non-projectivity |
Semantics | Analysis of semantic dependencies Dense vectors using SVD Dense vectors using word prediction: skip-gram and CBOW Properties of dense vectors Brown clustering |
Computing with word senses | Word senses Relations between senses Databases of lexical relationships Disambiguation of the meaning of words |
Practical applications of text mining | - |
Multilingual language processing | Processing of morphologically-rich languages Non-segmented language processing Language processing with few resources Translingual processing |
Emerging technologies | - |
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