Natural Language Processing for the Semantic Web. Diana Maynard

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СКАЧАТЬ Performance

       3.10 Summary

       4 Relation Extraction

       4.1 Introduction

       4.2 Relation Extraction Pipeline

       4.3 Relationship between Relation Extraction and other IE Tasks

       4.4 The Role of Knowledge Bases in Relation Extraction

       4.5 Relation Schemas

       4.6 Relation Extraction Methods

       4.6.1 Bootstrapping Approaches

       4.7 Rule-based Approaches

       4.8 Supervised Approaches

       4.9 Unsupervised Approaches

       4.10 Distant Supervision Approaches

       4.10.1 Universal Schemas

       4.10.2 Hybrid Approaches

       4.11 Performance

       4.12 Summary

       5 Entity Linking

       5.1 Named Entity Linking and Semantic Linking

       5.2 NEL Datasets

       5.3 LOD-based Approaches

       5.3.1 DBpedia Spotlight

       5.3.2 YODIE: A LOD-based Entity Disambiguation Framework

       5.3.3 Other Key LOD-based Approaches

       5.4 Commercial Entity Linking Services

       5.5 NEL for Social Media Content

       5.6 Discussion

       6 Automated Ontology Development

       6.1 Introduction

       6.2 Basic Principles

       6.3 Term Extraction

       6.3.1 Approaches Using Distributional Knowledge

       6.3.2 Approaches Using Contextual Knowledge

       6.4 Relation Extraction

       6.4.1 Clustering Methods

       6.4.2 Semantic Relations

       6.4.3 Lexico-syntactic Patterns

       6.4.4 Statistical Techniques

       6.5 Enriching Ontologies

       6.6 Ontology Development Tools

       6.6.1 Text2Onto

       6.6.2 SPRAT

       6.6.3 FRED

       6.6.4 Semi-automatic Ontology Creation

       6.7 Summary

       7 Sentiment Analysis

       7.1 Introduction

       7.2 Issues in Opinion Mining

       7.3 Opinion-Mining Subtasks

       7.3.1 Polarity Recognition

       7.3.2 Opinion Target Detection

       7.3.3 Opinion Holder Detection

       7.3.4 Sentiment Aggregation

       7.3.5 Further Linguistic Subcomponents

       7.4 Emotion Detection

       7.5 Methods for Opinion Mining

       7.6 Opinion Mining and Ontologies

       7.7 Opinion-Mining Tools

       7.8 Summary

       8 NLP for Social Media

       8.1 Social Media Streams: Characteristics, Challenges, and Opportunities

       8.2 Ontologies for Representing Social Media Semantics

       8.3 Semantic Annotation of Social Media

       8.3.1 Keyphrase Extraction

       8.3.2 Ontology-based Entity Recognition in Social Media

       8.3.3 Event Detection

       8.3.4 Sentiment Detection and Opinion Mining

       8.3.5 Cross-media Linking

       8.3.6 Rumor Analysis

       8.3.7 Discussion

       9 Applications

       9.1 Semantic Search

       9.1.1 What is Semantic Search?

       9.1.2 Why Semantic Full-text Search?

       9.1.3 Semantic Search Queries

       9.1.4 Relevance Scoring and Retrieval

       9.1.5 Semantic Search Full-text Platforms

       9.1.6 Ontology-based Faceted Search

       9.1.7 Form-based Semantic Search Interfaces СКАЧАТЬ