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  1. Journal of Ambient Intelligence and Humanized Computing
  2. Journal of Ambient Intelligence and Humanized Computing : Volume 4
  3. Journal of Ambient Intelligence and Humanized Computing : Volume 4, Issue 4, August 2013
  4. Semantics-aware data integration for heterogeneous data sources
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Journal of Ambient Intelligence and Humanized Computing : Volume 8
Journal of Ambient Intelligence and Humanized Computing : Volume 7
Journal of Ambient Intelligence and Humanized Computing : Volume 6
Journal of Ambient Intelligence and Humanized Computing : Volume 5
Journal of Ambient Intelligence and Humanized Computing : Volume 4
Journal of Ambient Intelligence and Humanized Computing : Volume 4, Issue 6, December 2013
Journal of Ambient Intelligence and Humanized Computing : Volume 4, Issue 5, October 2013
Journal of Ambient Intelligence and Humanized Computing : Volume 4, Issue 4, August 2013
Special issue on knowledge-intensive fusion for context awareness
From logic descriptors to granular logic descriptors: a study in allocation of information granularity
A collaborative situation-aware scheme based on an emergent paradigm for mobile resource recommenders
An efficient language pipeline for flexible rule-based context representation
An inference engine toolkit for computing with words
Semantics-aware data integration for heterogeneous data sources
Apply fuzzy ontology and FML to knowledge extraction for university governance and management
Context-aware similarity assessment within semantic space formed in linked data
Journal of Ambient Intelligence and Humanized Computing : Volume 4, Issue 3, June 2013
Journal of Ambient Intelligence and Humanized Computing : Volume 4, Issue 2, April 2013
Journal of Ambient Intelligence and Humanized Computing : Volume 4, Issue 1, February 2013
Journal of Ambient Intelligence and Humanized Computing : Volume 3
Journal of Ambient Intelligence and Humanized Computing : Volume 2
Journal of Ambient Intelligence and Humanized Computing : Volume 1

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Semantics-aware data integration for heterogeneous data sources

Content Provider Springer Nature Link
Author Leida, Marcello Gusmini, Alex Davies, John
Copyright Year 2012
Abstract This article presents a novel definition of a declarative mapping language, which is able to map precisely and unambiguously the semantics of a domain conceptualization (defined as an ontology) into queries to a set of data sources, where the data is residing. In this way, a system making use of this mapping language is able to access the data actually stored in the data sources thought a semantically rich representation. The mapping model proposed in this paper is also an ontology and therefore is machine understandable: it can be shared with other users or systems, processed by external tools for consistency checking, or collaboratively created and so on. Besides the contributions of the mapping model itself, this paper introduces the concepts of Semantic Join and Semantic Identifiers: a declarative approach to semantic data fusion and entity resolution over multiple unrelated databases, which allow to define extremely expressive mapping.
Starting Page 471
Ending Page 491
Page Count 21
File Format PDF
ISSN 18685137
Journal Journal of Ambient Intelligence and Humanized Computing
Volume Number 4
Issue Number 4
e-ISSN 18685145
Language English
Publisher Springer Berlin Heidelberg
Publisher Date 2012-09-27
Publisher Place Berlin, Heidelberg
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Data integration Ontologies Data semantics Data fusion Record linkage Entity resolution Mapping Computational Intelligence Artificial Intelligence (incl. Robotics) Robotics and Automation User Interfaces and Human Computer Interaction
Content Type Text
Resource Type Article
Subject Computer Science
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