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Umfang: 1 online resource (358 pages)

ISBN: 9783319939353

Serie: The Information Retrieval Ser. ; v.39

Anmerkung: Intro -- Preface -- Website -- Contents -- Acronyms -- Notation -- 1 Introduction -- 1.1 What Is an Entity? -- 1.1.1 Named Entities vs. Concepts -- 1.1.2 Properties of Entities -- 1.1.3 Representing Properties of Entities -- 1.2 A Brief Historical Outlook -- 1.2.1 Information Retrieval -- 1.2.2 Databases -- 1.2.3 Natural Language Processing -- 1.2.4 Semantic Web -- 1.3 Entity-Oriented Search -- 1.3.1 A Bird's-Eye View -- 1.3.1.1 Users and Information Needs -- 1.3.1.2 Search Engine -- 1.3.1.3 Data -- 1.3.2 Tasks and Challenges -- 1.3.2.1 Entities as the Unit of Retrieval -- 1.3.2.2 Entities for Knowledge Representation -- 1.3.2.3 Entities for an Enhanced User Experience -- 1.3.3 Entity-Oriented vs. Semantic Search -- 1.3.4 Application Areas -- 1.4 About the Book -- 1.4.1 Focus -- 1.4.2 Audience and Prerequisites -- 1.4.3 Organization -- 1.4.4 Terminology and Notation -- References -- 2 Meet the Data -- 2.1 The Web -- 2.1.1 Datasets and Resources -- 2.2 Wikipedia -- 2.2.1 The Anatomy of a Wikipedia Article -- 2.2.1.1 Title -- 2.2.1.2 Infobox -- 2.2.1.3 Introductory Text -- 2.2.2 Links -- 2.2.3 Special-Purpose Pages -- 2.2.3.1 Redirect Pages -- 2.2.3.2 Disambiguation Pages -- 2.2.4 Categories, Lists, and Navigation Templates -- 2.2.4.1 Categories -- 2.2.4.2 Lists -- 2.2.4.3 Navigation Templates -- 2.2.5 Resources -- 2.3 Knowledge Bases -- 2.3.1 A Knowledge Base Primer -- 2.3.1.1 Knowledge Bases vs. Ontologies -- 2.3.1.2 RDF -- 2.3.2 DBpedia -- 2.3.2.1 Ontology -- 2.3.2.2 Extraction -- 2.3.2.3 Datasets and Resources -- 2.3.3 YAGO -- 2.3.3.1 Taxonomy -- 2.3.3.2 Extensions -- 2.3.3.3 Resources -- 2.3.4 Freebase -- 2.3.5 Wikidata -- 2.3.6 The Web of Data -- 2.3.6.1 Datasets and Resources -- 2.3.7 Standards and Resources -- 2.4 Summary -- References -- Part I Entity Ranking -- 3 Term-Based Models for Entity Ranking -- 3.1 The Ad Hoc Entity Retrieval Task. , 3.2 Constructing Term-Based Entity Representations -- 3.2.1 Representations from Unstructured Document Corpora -- 3.2.1.1 Document-Level Annotations -- 3.2.1.2 Mention-Level Annotations -- 3.2.2 Representations from Semi-structured Documents -- 3.2.3 Representations from Structured Knowledge Bases -- 3.2.3.1 Predicate Folding -- 3.2.3.2 From Triples to Text -- 3.2.3.3 Multiple Knowledge Bases -- 3.3 Ranking Term-Based Entity Representations -- 3.3.1 Unstructured Retrieval Models -- 3.3.1.1 Language Models -- 3.3.1.2 BM25 -- 3.3.1.3 Sequential Dependence Models -- 3.3.2 Fielded Retrieval Models -- 3.3.2.1 Mixture of Language Models -- 3.3.2.2 Probabilistic Retrieval Model for Semi-Structured Data -- 3.3.2.3 BM25F -- 3.3.2.4 Fielded Sequential Dependence Models -- 3.3.3 Learning-to-Rank -- 3.3.3.1 Features -- 3.3.3.2 Learning Algorithms -- 3.3.3.3 Practical Considerations -- 3.4 Ranking Entities Without Direct Representations -- 3.5 Evaluation -- 3.5.1 Evaluation Measures -- 3.5.2 Test Collections -- 3.5.2.1 TREC Enterprise -- 3.5.2.2 INEX Entity Ranking -- 3.5.2.3 TREC Entity -- 3.5.2.4 Semantic Search Challenge -- 3.5.2.5 INEX Linked Data -- 3.5.2.6 Question Answering over Linked Data -- 3.5.2.7 The DBpedia-Entity Test Collection -- 3.6 Summary -- 3.7 Further Reading -- References -- 4 Semantically Enriched Models for Entity Ranking -- 4.1 Semantics Means Structure -- 4.2 Preserving Structure -- 4.2.1 Multi-Valued Predicates -- 4.2.1.1 Parameter Settings -- 4.2.2 References to Entities -- 4.3 Entity Types -- 4.3.1 Type Taxonomies and Challenges -- 4.3.2 Type-Aware Entity Ranking -- 4.3.3 Estimating Type-Based Similarity -- 4.4 Entity Relationships -- 4.4.1 Ad Hoc Entity Retrieval -- 4.4.2 List Search -- 4.4.3 Related Entity Finding -- 4.4.3.1 Candidate Selection -- 4.4.3.2 Type Filtering -- 4.4.3.3 Entity Relevance -- 4.5 Similar Entity Search. , 4.5.1 Pairwise Entity Similarity -- 4.5.1.1 Term-Based Similarity -- 4.5.1.2 Corpus-Based Similarity -- 4.5.1.3 Distributional Similarity -- 4.5.1.4 Graph-Based Similarity -- 4.5.1.5 Property-Specific Similarity -- 4.5.2 Collective Entity Similarity -- 4.5.2.1 Structure-Based Method -- 4.5.2.2 Aspect-Based Method -- 4.6 Query-Independent Ranking -- 4.6.1 Popularity -- 4.6.2 Centrality -- 4.6.2.1 PageRank -- 4.6.2.2 PageRank for Entities -- 4.6.2.3 A Two-Layered Extension of PageRank for the Web of Data -- 4.6.3 Other Methods -- 4.7 Summary -- 4.8 Further Reading -- References -- Part II Bridging Text and Structure -- 5 Entity Linking -- 5.1 From Named Entity Recognition Toward Entity Linking -- 5.1.1 Named Entity Recognition -- 5.1.2 Named Entity Disambiguation -- 5.1.3 Entity Coreference Resolution -- 5.2 The Entity Linking Task -- 5.3 The Anatomy of an Entity Linking System -- 5.4 Mention Detection -- 5.4.1 Surface Form Dictionary Construction -- 5.4.2 Filtering Mentions -- 5.4.3 Overlapping Mentions -- 5.5 Candidate Selection -- 5.6 Disambiguation -- 5.6.1 Features -- 5.6.1.1 Prior Importance Features -- 5.6.1.2 Contextual Features -- 5.6.1.3 Entity-Relatedness Features -- 5.6.2 Approaches -- 5.6.2.1 Individual Local Disambiguation -- 5.6.2.2 Individual Global Disambiguation -- 5.6.2.3 Collective Disambiguation -- 5.6.3 Pruning -- 5.7 Entity Linking Systems -- 5.8 Evaluation -- 5.8.1 Evaluation Measures -- 5.8.2 Test Collections -- 5.8.2.1 Individual Researchers -- 5.8.2.2 INEX Link-the-Wiki -- 5.8.2.3 TAC Entity Linking -- 5.8.2.4 Entity Recognition and Disambiguation Challenge -- 5.8.3 Component-Based Evaluation -- 5.9 Resources -- 5.9.1 A Cross-Lingual Dictionary for English Wikipedia Concepts -- 5.9.2 Freebase Annotations of the ClueWeb Corpora -- 5.10 Summary -- 5.11 Further Reading -- References -- 6 Populating Knowledge Bases. , 6.1 Harvesting Knowledge from Text -- 6.1.1 Class-Instance Acquisition -- 6.1.1.1 Obtaining Instances of Semantic Classes -- 6.1.1.2 Obtaining Semantic Classes of Instances -- 6.1.2 Class-Attribute Acquisition -- 6.1.3 Relation Extraction -- 6.2 Entity-Centric Document Filtering -- 6.2.1 Overview -- 6.2.2 Mention Detection -- 6.2.3 Document Scoring -- 6.2.3.1 Mention-Based Scoring -- 6.2.3.2 Boolean Queries -- 6.2.3.3 Supervised Learning -- 6.2.4 Features -- 6.2.4.1 Document Features -- 6.2.4.2 Entity Features -- 6.2.4.3 Document-Entity Features -- 6.2.4.4 Temporal Features -- 6.2.5 Evaluation -- 6.2.5.1 Test Collections -- 6.2.5.2 Annotations -- 6.2.5.3 Evaluation Methodology -- 6.2.5.4 Evaluation Methodology Revisited -- 6.3 Slot Filling -- 6.3.1 Approaches -- 6.3.2 Evaluation -- 6.4 Summary -- 6.5 Further Reading -- References -- Part III Semantic Search -- 7 Understanding Information Needs -- 7.1 Semantic Query Analysis -- 7.1.1 Query Classification -- 7.1.1.1 Query Intent Classification -- 7.1.1.2 Query Topic Classification -- 7.1.2 Query Annotation -- 7.1.2.1 Query Segmentation -- 7.1.2.2 Query Tagging -- 7.1.3 Query Interpretation -- 7.2 Identifying Target Entity Types -- 7.2.1 Problem Definition -- 7.2.2 Unsupervised Approaches -- 7.2.2.1 Type-Centric Model -- 7.2.2.2 Entity-Centric Model -- 7.2.3 Supervised Approach -- 7.2.4 Evaluation -- 7.2.4.1 Evaluation Measures -- 7.2.4.2 Test Collections -- 7.3 Entity Linking in Queries -- 7.3.1 Entity Annotation Tasks -- 7.3.1.1 Named Entity Recognition -- 7.3.1.2 Semantic Linking -- 7.3.1.3 Interpretation Finding -- 7.3.2 Pipeline Architecture for Interpretation Finding -- 7.3.3 Candidate Entity Ranking -- 7.3.3.1 Unsupervised Approach -- 7.3.3.2 Supervised Approach -- 7.3.3.3 Gathering Additional Context -- 7.3.3.4 Evaluation and Test Collections -- 7.3.4 Producing Interpretations. , 7.3.4.1 Unsupervised Approach -- 7.3.4.2 Supervised Approach -- 7.3.4.3 Evaluation Measures -- 7.3.4.4 Test Collections -- 7.4 Query Templates -- 7.4.1 Concepts and Definitions -- 7.4.2 Template Discovery Methods -- 7.4.2.1 Classify& -- Match -- 7.4.2.2 QueST -- 7.5 Summary -- 7.6 Further Reading -- References -- 8 Leveraging Entities in Document Retrieval -- 8.1 Mapping Queries to Entities -- 8.2 Leveraging Entities for Query Expansion -- 8.2.1 Document-Based Query Expansion -- 8.2.2 Entity-Centric Query Expansion -- 8.2.3 Unsupervised Term Selection -- 8.2.4 Supervised Term Selection -- 8.2.4.1 Features -- 8.2.4.2 Training -- 8.3 Projection-Based Methods -- 8.3.1 Explicit Semantic Analysis -- 8.3.1.1 ESA Concept-Based Indexing -- 8.3.1.2 ESA Concept-Based Retrieval -- 8.3.2 Latent Entity Space Model -- 8.3.3 EsdRank -- 8.3.3.1 Features -- 8.3.3.2 Learning-to-Rank Model -- 8.4 Entity-Based Representations -- 8.4.1 Entity-Based Document Language Models -- 8.4.2 Bag-of-Entities Representation -- 8.4.2.1 Basic Ranking Models -- 8.4.2.2 Explicit Semantic Ranking -- 8.4.2.3 Word-Entity Duet Framework -- 8.4.2.4 Attention-Based Ranking Model -- 8.5 Practical Considerations -- 8.6 Resources and Test Collections -- 8.7 Summary -- 8.8 Further Reading -- References -- 9 Utilizing Entities for an Enhanced Search Experience -- 9.1 Query Assistance -- 9.1.1 Query Auto-completion -- 9.1.1.1 Leveraging Entity Types -- 9.1.2 Query Recommendations -- 9.1.2.1 Query-Flow Graph -- 9.1.2.2 Exploiting Entity Aspects -- 9.1.2.3 Entity Types -- 9.1.2.4 Entity Relationships -- 9.1.3 Query Building Interfaces -- 9.2 Entity Cards -- 9.2.1 The Anatomy of an Entity Card -- 9.2.2 Factual Entity Summaries -- 9.2.2.1 Fact Ranking -- 9.2.2.2 Summary Generation -- 9.3 Entity Recommendations -- 9.3.1 Recommendations Given an Entity -- 9.3.2 Personalized Recommendations. , 9.3.2.1 Entity-Based Method.

Weitere Ausg.: Print version: Balog, Krisztian Entity-Oriented Search Cham : Springer International Publishing AG,c2018 ISBN 9783319939339

Sprache: Englisch

Schlagwort(e): Electronic books.

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