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A Practical Guide to Hybrid Natural Language Processing

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Cover of 'A Practical Guide to Hybrid Natural Language Processing'

Table of Contents

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    Book Overview
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    Chapter 1 Hybrid Natural Language Processing: An Introduction
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    Chapter 2 Word, Sense, and Graph Embeddings
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    Chapter 3 Understanding Word Embeddings and Language Models
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    Chapter 4 Capturing Meaning from Text as Word Embeddings
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    Chapter 5 Capturing Knowledge Graph Embeddings
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    Chapter 6 Building Hybrid Representations from Text Corpora, Knowledge Graphs, and Language Models
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    Chapter 7 Quality Evaluation
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    Chapter 8 Capturing Lexical, Grammatical, and Semantic Information with Vecsigrafo
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    Chapter 9 Aligning Embedding Spaces and Applications for Knowledge Graphs
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    Chapter 10 A Hybrid Approach to Disinformation Analysis
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    Chapter 11 Jointly Learning Text and Visual Information in the Scientific Domain
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    Chapter 12 Looking into the Future of Natural Language Processing
Attention for Chapter 2: Word, Sense, and Graph Embeddings
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