자료유형 | 단행본 |
---|---|
서명/저자사항 | Semantic search for novel information/ Michael F?rber. |
개인저자 | F?rber, Michael,author. |
형태사항 | 1 online resource (xviii, 193 pages). |
총서사항 | Studies on the semantic web,2215-0870; vol. 031 |
기타형태 저록 | Print version: F?rber, Michael. Semantic search for novel information. Amsterdam, The Netherlands : IOS Press BV, [2017] 9781614997740 |
ISBN | 9781614997757 1614997756 |
서지주기 | Includes bibliographical references. |
내용주기 | 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 Trend Detection; Semantic 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 The Suitability of Knowledge Graphs for Semantic Novelty Detection; Selection 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 Challenges in the Wild; Summary 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 Evaluation 1: CrunchBase; Data 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 |
일반주제명 | Semantic computing. Semantic Web. COMPUTERS / General Semantic computing. Semantic Web. |
언어 | 영어 |
바로가기 |