Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Relevance weighting of search terms
Document retrieval systems
Building the data warehouse
Complexity of answering queries using materialized views
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Reconciling schemas of disparate data sources: a machine-learning approach
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Data integration: a theoretical perspective
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Database intergration using neural networks: implementation and experiences
Knowledge and Information Systems
Modern Information Retrieval
Enterprise Knowledge Management
Computer
Access Control: Policies, Models, and Mechanisms
FOSAD '00 Revised versions of lectures given during the IFIP WG 1.7 International School on Foundations of Security Analysis and Design on Foundations of Security Analysis and Design: Tutorial Lectures
Using JessTab to Integrate Protégé and Jess
IEEE Intelligent Systems
Answering queries using views: A survey
The VLDB Journal — The International Journal on Very Large Data Bases
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Aggregation operators: properties, classes and construction methods
Aggregation operators
Techniques and Applications of Digital Watermarking and Content Protection
Techniques and Applications of Digital Watermarking and Content Protection
Beyond data warehousing: what's next in business intelligence?
Proceedings of the 7th ACM international workshop on Data warehousing and OLAP
A framework for modeling and evaluating automatic semantic reconciliation
The VLDB Journal — The International Journal on Very Large Data Bases
Semantic-integration research in the database community
AI Magazine - Special issue on semantic integration
Real Time Business Intelligence for the Adaptive Enterprise
CEC-EEE '06 Proceedings of the The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services
A Data Mining Approach for Managing Shared Ontological Knowledge
ICALT '06 Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies
ACM SIGMOD Record
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
DR-Prolog: A System for Defeasible Reasoning with Rules and Ontologies on the Semantic Web
IEEE Transactions on Knowledge and Data Engineering
Ontology Matching
SAMBO-A system for aligning and merging biomedical ontologies
Web Semantics: Science, Services and Agents on the World Wide Web
Pellet: A practical OWL-DL reasoner
Web Semantics: Science, Services and Agents on the World Wide Web
X-SOM: A Flexible Ontology Mapper
DEXA '07 Proceedings of the 18th International Conference on Database and Expert Systems Applications
A survey on context-aware systems
International Journal of Ad Hoc and Ubiquitous Computing
WordNet: similarity - measuring the relatedness of concepts
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Using ontologies to map concept relations in a data integration system
OTM'07 Proceedings of the 2007 OTM Confederated international conference on On the move to meaningful internet systems - Volume Part II
EPICA: easy persistent identifier common architecture
OTM'10 Proceedings of the 2010 international conference on On the move to meaningful internet systems
Comparative study of classification techniques on biomedical data from hypertext documents
International Journal of Knowledge Engineering and Soft Data Paradigms
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Data integration systems are used to integrate heterogeneous data sources in a single view. Recent work on business intelligence highlights the need of on-time, reliable and sound data access systems relying on methods based on semi-automatic procedures. A crucial factor for any semi-automatic algorithm is that of the matching strategy. Different categories of matching operators carry different semantics. For this reason, combining them into a single strategy is a non-trivial process that has to take into account a variety of options. This paper presents SAMS, a matching strategy based on a semantics-aware categorisation of matching operators that allows to group similar attributes on a semantically-rich form.