Pair-Wise entity resolution: overview and challenges
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Duplicate Record Detection: A Survey
IEEE Transactions on Knowledge and Data Engineering
Ontology Matching
Entity Data Management in OKKAM
DEXA '08 Proceedings of the 2008 19th International Conference on Database and Expert Systems Application
Entity Name System: The Back-Bone of an Open and Scalable Web of Data
ICSC '08 Proceedings of the 2008 IEEE International Conference on Semantic Computing
Towards a general entity representation model
IRI'09 Proceedings of the 10th IEEE international conference on Information Reuse & Integration
Feature-based entity matching: the FBEM model, implementation, evaluation
CAiSE'10 Proceedings of the 22nd international conference on Advanced information systems engineering
A Bayesian model for entity type disambiguation
AIMSA'10 Proceedings of the 14th international conference on Artificial intelligence: methodology, systems, and applications
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The problem of Data Linkage in the SemanticWeb can be divided in two lines of action: schema and ontology matching/mapping, which allows us to draw conclusions about sets of individuals through concept relations, and entitylevel linkage, where more information can be reached from distributed sources because of the fact that the information is about the same entity. While the area of schema and ontology matching is traditionally much addressed, it appears that today the Semantic Web looks very much like a collection of "information islands" that are very poorly integrated with each other, especially on the individual level; and when some of these islands are linked, this is often the result of a lot of hard and time-consuming manual work. The general problem we are working on is to provide a structured approach of how to improve the situation of data linkage at the level of individuals in the Web of Data. As a specific contribution, in this article we describe a novel algorithm for entity linkage - called Name Feature Match - based on a recent empirical investigation about how humans describe individuals (or entities). We show in a first experimental evaluation that such an approach, which takes into account the cognitive point of view of entity representation by humans, can provide an improvement over other relevant approaches.