Semantic search for novel information /:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam, Netherlands :
IOS Press,
[2017]
|
| Schriftenreihe: | Studies on the Semantic Web ;
v. 031. |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | 1 online resource (xviii, 193 pages) |
| Bibliographie: | Includes bibliographical references. |
| ISBN: | 9781614997757 1614997756 |
| ISSN: | 2215-0870 ; |
Internformat
MARC
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| 100 | 1 | |a Färber, Michael, |e author. | |
| 245 | 1 | 0 | |a Semantic search for novel information / |c Michael Färber. |
| 264 | 1 | |a Amsterdam, Netherlands : |b IOS Press, |c [2017] | |
| 300 | |a 1 online resource (xviii, 193 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 490 | 1 | |a Studies on the semantic web, |x 2215-0870 ; |v vol. 031 | |
| 504 | |a Includes bibliographical references. | ||
| 588 | 0 | |a Online resource; title from PDF title page (IOS Press, viewed September 22, 2017). | |
| 505 | 0 | |a 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 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 650 | 0 | |a Semantic computing. |0 http://id.loc.gov/authorities/subjects/sh2009007899 | |
| 650 | 0 | |a Semantic Web. |0 http://id.loc.gov/authorities/subjects/sh2002000569 | |
| 650 | 6 | |a Informatique sémantique. | |
| 650 | 6 | |a Web sémantique. | |
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| 650 | 7 | |a Semantic computing |2 fast | |
| 650 | 7 | |a Semantic Web |2 fast | |
| 758 | |i has work: |a Semantic search for novel information (Text) |1 https://id.oclc.org/worldcat/entity/E39PCFMP3qPWfTWXrWRtKF4j83 |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Färber, Michael. |t Semantic search for novel information. |d Amsterdam, The Netherlands : IOS Press BV, [2017] |z 9781614997740 |w (OCoLC)1002024505 |
| 830 | 0 | |a Studies on the Semantic Web ; |v v. 031. |0 http://id.loc.gov/authorities/names/no2009156151 | |
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| contents | 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. |
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| dewey-search | 006 |
| dewey-sort | 16 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
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| id | ZDB-4-EBA-on1004378038 |
| illustrated | Not Illustrated |
| indexdate | 2024-11-27T13:28:01Z |
| institution | BVB |
| isbn | 9781614997757 1614997756 |
| issn | 2215-0870 ; |
| language | English |
| oclc_num | 1004378038 |
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| physical | 1 online resource (xviii, 193 pages) |
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| series | Studies on the Semantic Web ; |
| series2 | Studies on the semantic web, |
| spelling | Färber, Michael, author. Semantic search for novel information / Michael Färber. Amsterdam, Netherlands : IOS Press, [2017] 1 online resource (xviii, 193 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Studies on the semantic web, 2215-0870 ; vol. 031 Includes bibliographical references. Online resource; title from PDF title page (IOS Press, viewed September 22, 2017). 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. Semantic computing. http://id.loc.gov/authorities/subjects/sh2009007899 Semantic Web. http://id.loc.gov/authorities/subjects/sh2002000569 Informatique sémantique. Web sémantique. COMPUTERS General. bisacsh Semantic computing fast Semantic Web fast has work: Semantic search for novel information (Text) https://id.oclc.org/worldcat/entity/E39PCFMP3qPWfTWXrWRtKF4j83 https://id.oclc.org/worldcat/ontology/hasWork Print version: Färber, Michael. Semantic search for novel information. Amsterdam, The Netherlands : IOS Press BV, [2017] 9781614997740 (OCoLC)1002024505 Studies on the Semantic Web ; v. 031. http://id.loc.gov/authorities/names/no2009156151 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1595323 Volltext |
| spellingShingle | Färber, Michael Semantic search for novel information / Studies on the Semantic Web ; 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. Semantic computing. http://id.loc.gov/authorities/subjects/sh2009007899 Semantic Web. http://id.loc.gov/authorities/subjects/sh2002000569 Informatique sémantique. Web sémantique. COMPUTERS General. bisacsh Semantic computing fast Semantic Web fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh2009007899 http://id.loc.gov/authorities/subjects/sh2002000569 |
| title | Semantic search for novel information / |
| title_auth | Semantic search for novel information / |
| title_exact_search | Semantic search for novel information / |
| title_full | Semantic search for novel information / Michael Färber. |
| title_fullStr | Semantic search for novel information / Michael Färber. |
| title_full_unstemmed | Semantic search for novel information / Michael Färber. |
| title_short | Semantic search for novel information / |
| title_sort | semantic search for novel information |
| topic | Semantic computing. http://id.loc.gov/authorities/subjects/sh2009007899 Semantic Web. http://id.loc.gov/authorities/subjects/sh2002000569 Informatique sémantique. Web sémantique. COMPUTERS General. bisacsh Semantic computing fast Semantic Web fast |
| topic_facet | Semantic computing. Semantic Web. Informatique sémantique. Web sémantique. COMPUTERS General. Semantic computing Semantic Web |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1595323 |
| work_keys_str_mv | AT farbermichael semanticsearchfornovelinformation |