Entity-Oriented Search.

• Superior document: The Information Retrieval Series ; v.39
• Author: Balog, Krisztian.
• Place / Publishing House: Cham : : Springer International Publishing AG,, 2018.; Ã2018.
• Year of Publication: 2018
• Edition: 1st ed.
• Language: English
• Series: The Information Retrieval Series
• Physical Description: 1 online resource (358 pages)

Table of Contents

• 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&amp
• 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.