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Semantic search for novel information
~
Farber, Michael,
Semantic search for novel information
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Semantic search for novel information/ Michael Farber.
Author:
Farber, Michael,
Published:
Amsterdam, Netherlands :IOS Press, : 2017.,
Description:
1 online resource (xviii, 193 p.)
Subject:
Semantic Web. -
Online resource:
http://ebooks.windeal.com.tw/ios/cover.asp?isbn=9781614997740
ISBN:
9781614997757 (e-book)
Semantic search for novel information
Farber, Michael,
Semantic search for novel information
[electronic resource] /Michael Farber. - Amsterdam, Netherlands :IOS Press,2017. - 1 online resource (xviii, 193 p.) - Studies on the semantic web ;v. 031. - Studies on the Semantic Web ;v. 019..
Includes bibliographical references.
Title Page ; Abstract; Acknowledgements; Contents; List of Figures; List of Tables; List of Listings; Introduction; Motivation; Problem Statement; Research Questions; Contribution of the Thesis; Published Results; Readers' Guide; Foundations; Semantic Web Technologies; The Vision of the Semantic Web; RDF and SPARQL; Knowledge Graph; Information Extraction, Machine Learning, Information Retrieval, and Data Quality; Information Extraction; Machine Learning; Information Retrieval; Data Quality; State-of-the-Art; Statistical Search for Relevant Information; Temporal Information Retrieval
ISBN: 9781614997757 (e-book)Subjects--Topical Terms:
408078
Semantic Web.
LC Class. No.: QA76.5913 / .F865 2017
Dewey Class. No.: 006
Semantic search for novel information
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Semantic search for novel information
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[electronic resource] /
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Michael Farber.
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Amsterdam, Netherlands :
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IOS Press,
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2017.
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1 online resource (xviii, 193 p.)
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Studies on the semantic web ;
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v. 031
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Includes bibliographical references.
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Title Page ; Abstract; Acknowledgements; Contents; List of Figures; List of Tables; List of Listings; Introduction; Motivation; Problem Statement; Research Questions; Contribution of the Thesis; Published Results; Readers' Guide; Foundations; Semantic Web Technologies; The Vision of the Semantic Web; RDF and SPARQL; Knowledge Graph; Information Extraction, Machine Learning, Information Retrieval, and Data Quality; Information Extraction; Machine Learning; Information Retrieval; Data Quality; State-of-the-Art; Statistical Search for Relevant Information; Temporal Information Retrieval
505
8
$a
Trend DetectionSemantic Search for Relevant Information; Semantic Search for Relevant Entities; Semantic Search for Relevant Statements; Semantic Search for Relevant Events; Statistical Search for Relevant, Novel Information; Characteristics of Statistical Search for Relevant, Novel Information; Evaluations and Data Sets; Approaches to the Statistical Search for Relevant, Novel Information; Semantic Search for Relevant, Novel Information; Semantic Search for Novel Entities; Semantic Search for Novel Statements; Semantic Search for Novel Events
505
8
$a
The Suitability of Knowledge Graphs for Semantic Novelty DetectionSelection of Knowledge Graphs; Key Statistics of Selected Knowledge Graphs; Related Work; Number of Triples and Statements; Classes and Domains; Relations and Predicates; Instances and Entities; Subjects and Objects; Summary of Key Statistics; Completeness and Timeliness of Selected Knowledge Graphs; Gold Standard; Completeness; Timeliness; Discussion; Conclusions; Emerging Entity Detection; Motivation; Entity Linking Challenges Arising from Missing Entities and Missing Surface Forms; Overview of Entity Linking Challenges
505
8
$a
Challenges in the WildSummary of Findings; Approach: Emerging Entity Detection; The Approach; Evaluation Results; Related Work; Challenge 1: Linking to in-KG Entities via Known Surface Forms; Challenge 2: Linking to in-KG Entities via Unknown Surface Forms; Challenge 3: Linking to Out-of-KG Entities via Known Surface Forms; Challenge 4: Linking to Out-of-KG Entities via Unkown Surface Forms; Conclusions; Novel Statement Extraction; Motivation; Measuring Semantic Novelty of Statements; The Novel Statement Extraction System; Textual Triple Extraction; KG Linking; Novelty Detection
505
8
$a
Evaluation 1: CrunchBaseData Used; Evaluation Setting; Evaluation Results; Evaluation 2: DBpedia; Data Used; The Baseline Approach and its Evaluation Results; Evaluation Results of Our Approach; Discussion; Related Work; Conclusions; Conclusions; Summary; Limitations; Outlook; Appendix; Supplementary Material; Emerging Entity Detection; Bibliography
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Semantic Web.
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408078
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Semantic computing.
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Studies on the Semantic Web ;
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v. 019.
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http://ebooks.windeal.com.tw/ios/cover.asp?isbn=9781614997740
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