Services for connecting and integrating big numbers of linked datasets

Services for connecting and integrating big numbers of linked datasets /

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Bibliographic Details
Main Author: Mountantonakis, Michalis
Corporate Author: ProQuest (Firm)
Format: eBook
Language:English
Published: Amsterdam : IOS Press, 2021.
Series:Studies on the Semantic Web ; v. 50.
Subjects:
Linked data.
Big data.
Online Access:Connect to this title online (unlimited simultaneous users allowed; 325 uses per year)

MARC

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100 1 |a Mountantonakis, Michalis. 
245 1 0 |a Services for connecting and integrating big numbers of linked datasets /  |c Michalia Mountantonakis. 
260 |a Amsterdam :  |b IOS Press,  |c 2021. 
300 |a 1 online resource ( 314 p..) 
490 1 |a Studies on the Semantic Web ;  |v v.50 
500 |a Description based upon print version of record. 
500 |a Appendix B. Acronyms. 
505 0 0 |a Machine generated contents note:   |g ch. 1   |t Introduction --   |g 1.1.  |t Context and Motivation --   |g 1.2.  |t Related Problems --   |g 1.3.  |t Analysis of the Problems and Related Challenges --   |g 1.4.  |t Contributions of this Dissertation --   |g 1.5.  |t Publications --   |g 1.6.  |t Outline of Dissertation --   |g ch. 2   |t Large Scale Semantic Integration Of Linked Data: A Survey --   |g 2.1.  |t Background and Context --   |g 2.2.  |t Why Data Integration is Difficult --   |g 2.3.  |t Data Integration Landscape --   |g 2.4.  |t Surveying the Integration Methods --   |g 2.5.  |t Processes for Integration --   |g 2.6.  |t Evaluation of Integration --   |g 2.7.  |t Semantic Integration On a Large Scale --   |g 2.8.  |t Discussion --   |g ch. 3   |t Research Gaps & Motivating Scenarios --   |g 3.1.  |t Placement of Dissertation --   |g 3.2.  |t Task A. Object Coreference & All Facts --   |g 3.3.  |t Task B. Connectivity Analytics --   |g 3.4.  |t Task C. Dataset Search, Discovery & Selection --   |g 3.5.  |t Task D. Data Enrichment --   |g 3.6.  |t Task E. Data Quality Assessment --   |g 3.7.  |t Proposed Process --   |g ch. 4   |t Cross-Dataset Identity Reasoning & Semantics-Aware Indexes At Global Scale --   |g 4.1.  |t Background & Notations --   |g 4.2.  |t Requirements --   |g 4.3.  |t Problem Statement & Process --   |g 4.4.  |t Cross-Dataset Identity Reasoning at Global Scale --   |g 4.5.  |t Set of Semantics-Aware Indexes --   |g 4.6.  |t Comparison of Parallel Algorithms --   |g 4.7.  |t Experimental Evaluation - Efficiency --   |g 4.8.  |t Epilogue --   |g ch. 5   |t Content-Based Intersection, Union And Complement Metrics Among Several Linked Datasets --   |g 5.1.  |t Problem Statement --   |g 5.2.  |t Why Plain SPARQL Implementations are Not Enough --   |g 5.3.  |t Lattice of Measurements by Using Indexes --   |g 5.4.  |t How to Compute Content-Based Metrics --   |g 5.5.  |t Incremental Computation of Metrics --   |g 5.6.  |t Computing Lattice Measurements in Parallel --   |g 5.7.  |t Experimental Evaluation - Efficiency --   |g 5.8.  |t Connectivity Analytics over LOD Cloud Datasets --   |g 5.9.  |t Epilogue --   |g ch. 6   |t Lodsyndesis Suite Of Services --   |g 6.1.  |t LODsyndesis Services for Tasks A-E --   |g 6.2.  |t LODsyndesisML. Linked Data & Machine Learning --   |g 6.3.  |t LODVec. Knowledge Graph Embeddings --   |g 6.4.  |t LODQA. Linked Data Question Answering --   |g 6.5.  |t LODsyndesisIE: Entity Extraction and Enrichment --   |g 6.6.  |t Epilogue --   |g ch. 7   |t Conclusion --   |g 7.1.  |t Synopsis of Contributions --   |g 7.2.  |t Directions for Future Work and Research. 
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650 0 |a Linked data. 
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830 0 |a Studies on the Semantic Web ;  |v v. 50. 
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