Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Principles of dataspace systems
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Duplicate Record Detection: A Survey
IEEE Transactions on Knowledge and Data Engineering
Pay-as-you-go user feedback for dataspace systems
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Dependencies revisited for improving data quality
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
ACM Computing Surveys (CSUR)
Proactive learning: cost-sensitive active learning with multiple imperfect oracles
Proceedings of the 17th ACM conference on Information and knowledge management
Quality-driven information filtering using the WIQA policy framework
Web Semantics: Science, Services and Agents on the World Wide Web
Advances in Web Semantics I
Querying Trust in RDF Data with tSPARQL
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
Proceedings of the VLDB Endowment
Linked Data
Dynamic constraints for record matching
The VLDB Journal — The International Journal on Very Large Data Bases
Querying Heterogeneous Datasets on the Linked Data Web: Challenges, Approaches, and Trends
IEEE Internet Computing
Linking building data in the cloud: Integrating cross-domain building data using linked data
Advanced Engineering Informatics
Editorial: Efficient discovery of similarity constraints for matching dependencies
Data & Knowledge Engineering
Hi-index | 0.00 |
This paper presents a new approach for managing integration quality and user feedback, for entity consolidation, within applications consuming Linked Open Data. The quality of a dataspace containing multiple linked datasets is defined in term of a utility measure, based on domain specific matching dependencies. Furthermore, the user is involved in the consolidation process through soliciting feedback about identity resolution links, where each candidate link is ranked according to its benefit to the dataspace; calculated by approximating the improvement in the utility of dataspace utility. The approach evaluated on real world and synthetic datasets demonstrates the effectiveness of utility measure; through dataspace integration quality improvement that requires less overall user feedback iterations.