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Format: xix, 351 Seiten.

ISBN: 978-3-319-93933-9

Series Statement: The information retrieval series volume 39

Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-3-319-93935-3 10.1007/978-3-319-93935-3

Language: English

Subjects: Computer Science , General works

Keywords: Entity-Relationship-Datenmodell ; Information Retrieval

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)

URL: Volltext  (kostenfrei)

UID:

Format: 1 Online-Ressource (xxxi, 605 Seiten) : , 88 Illustrationen, 66 in Farbe.

ISBN: 978-3-030-99739-7

Series Statement: Lecture notes in computer science 13186

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-99738-0

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-99740-3

Language: English

Keywords: Konferenzschrift

DOI: 10.1007/978-3-030-99739-7

URL: Volltext  (URL des Erstveröffentlichers)

Author information: Hagen, Matthias 1979-

UID:

Format: 1 Online-Ressource (XIX, 351 p. 86 illus., 13 illus. in color)

Edition: 1st ed. 2018

ISBN: 9783319939353

Series Statement: The Information Retrieval Series 39

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-319-93933-9

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-319-93934-6

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-06749-6

Language: English

Subjects: Computer Science , General works

Keywords: Entity-Relationship-Datenmodell ; Information Retrieval

DOI: 10.1007/978-3-319-93935-3

URL: Volltext  (kostenfrei)

UID:

Format: 1 Online-Ressource (xxxii, 705 Seiten) : , 145 Illustrationen, 125 in Farbe.

ISBN: 978-3-030-99736-6

Series Statement: Lecture notes in computer science 13185

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-99735-9

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-99737-3

Language: English

Keywords: Konferenzschrift

DOI: 10.1007/978-3-030-99736-6

URL: Volltext  (URL des Erstveröffentlichers)

Author information: Hagen, Matthias 1979-

UID:

Format: 1 online resource (358 pages)

ISBN: 9783319939353

Series Statement: The Information Retrieval Ser. ; v.39

Note: 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.

Additional Edition: Print version: Balog, Krisztian Entity-Oriented Search Cham : Springer International Publishing AG,c2018 ISBN 9783319939339

Language: English

Keywords: Electronic books. ; Electronic books ; Electronic books.

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UID:

Format: 1 Online-Ressource (xxxi, 605 Seiten) : , 88 Illustrationen, 66 in Farbe.

ISBN: 978-3-030-99739-7

Series Statement: Lecture notes in computer science 13186

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-99738-0

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-99740-3

Language: English

Keywords: Konferenzschrift

DOI: 10.1007/978-3-030-99739-7

URL: Volltext  (URL des Erstveröffentlichers)

Author information: Hagen, Matthias 1979-

UID:

Format: 1 online resource (XIX, 351 p. 86 illus., 13 illus. in color.)

Edition: 1st ed. 2018.

ISBN: 3-319-93935-1

Series Statement: The Information Retrieval Series, 39

Content: This open access book covers all facets of entity-oriented search—where “search” can be interpreted in the broadest sense of information access—from a unified point of view, and provides a coherent and comprehensive overview of the state of the art. It represents the first synthesis of research in this broad and rapidly developing area. Selected topics are discussed in-depth, the goal being to establish fundamental techniques and methods as a basis for future research and development. Additional topics are treated at a survey level only, containing numerous pointers to the relevant literature. A roadmap for future research, based on open issues and challenges identified along the way, rounds out the book. The book is divided into three main parts, sandwiched between introductory and concluding chapters. The first two chapters introduce readers to the basic concepts, provide an overview of entity-oriented search tasks, and present the various types and sources of data that will be used throughout the book. Part I deals with the core task of entity ranking: given a textual query, possibly enriched with additional elements or structural hints, return a ranked list of entities. This core task is examined in a number of different variants, using both structured and unstructured data collections, and numerous query formulations. In turn, Part II is devoted to the role of entities in bridging unstructured and structured data. Part III explores how entities can enable search engines to understand the concepts, meaning, and intent behind the query that the user enters into the search box, and how they can provide rich and focused responses (as opposed to merely a list of documents)—a process known as semantic search. The final chapter concludes the book by discussing the limitations of current approaches, and suggesting directions for future research. Researchers and graduate students are the primary target audience of this book. A general background in information retrieval is sufficient to follow the material, including an understanding of basic probability and statistics concepts as well as a basic knowledge of machine learning concepts and supervised learning algorithms.

Note: 1 Introduction -- 2 Meet the Data -- 3 Term-Based Models for Entity Ranking -- 4 Semantically Enriched Models for Entity Ranking -- 5 Entity Linking -- 6 Populating Knowledge Bases -- 7 Understanding Information Needs -- 8 Leveraging Entities in Document Retrieval -- 9 Utilizing Entities for an Enhanced Search Experience -- 10 Conclusions and Future Directions. , English

Additional Edition: ISBN 3-319-93933-5

Language: English

DOI: 10.1007/978-3-319-93935-3

UID:

Format: 1 Online-Ressource (xxxii, 705 Seiten) : , 145 Illustrationen, 125 in Farbe.

ISBN: 978-3-030-99736-6

Series Statement: Lecture notes in computer science 13185

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-99735-9

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-99737-3

Language: English

Keywords: Konferenzschrift

DOI: 10.1007/978-3-030-99736-6

URL: Volltext  (URL des Erstveröffentlichers)

Author information: Hagen, Matthias 1979-

UID:

Format: 1 Online-Ressource (351 p.)

ISBN: 9783319939353

Series Statement: The Information Retrieval Series

Content: This open access book covers all facets of entity-oriented search—where “search” can be interpreted in the broadest sense of information access—from a unified point of view, and provides a coherent and comprehensive overview of the state of the art. It represents the first synthesis of research in this broad and rapidly developing area. Selected topics are discussed in-depth, the goal being to establish fundamental techniques and methods as a basis for future research and development. Additional topics are treated at a survey level only, containing numerous pointers to the relevant literature. A roadmap for future research, based on open issues and challenges identified along the way, rounds out the book. The book is divided into three main parts, sandwiched between introductory and concluding chapters. The first two chapters introduce readers to the basic concepts, provide an overview of entity-oriented search tasks, and present the various types and sources of data that will be used throughout the book. Part I deals with the core task of entity ranking: given a textual query, possibly enriched with additional elements or structural hints, return a ranked list of entities. This core task is examined in a number of different variants, using both structured and unstructured data collections, and numerous query formulations. In turn, Part II is devoted to the role of entities in bridging unstructured and structured data. Part III explores how entities can enable search engines to understand the concepts, meaning, and intent behind the query that the user enters into the search box, and how they can provide rich and focused responses (as opposed to merely a list of documents)—a process known as semantic search. The final chapter concludes the book by discussing the limitations of current approaches, and suggesting directions for future research. Researchers and graduate students are the primary target audience of this book. A general background in information retrieval is sufficient to follow the material, including an understanding of basic probability and statistics concepts as well as a basic knowledge of machine learning concepts and supervised learning algorithms

Note: English

Language: English

URL: kostenfrei

UID:

Format: 1 Online-Ressource (xxxi, 605 Seiten) , 88 Illustrationen, 66 in Farbe

ISBN: 9783030997397

Series Statement: Lecture notes in computer science 13186

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-99738-0

Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-99740-3

Language: English

Keywords: Konferenzschrift

DOI: 10.1007/978-3-030-99739-7

URL: Volltext  (URL des Erstveröffentlichers)

Author information: Hagen, Matthias 1979-