How Well Does Your Instance Matching System Perform? Experimental Evaluation with LANCE
نویسندگان
چکیده
Identifying duplicate instances in the Data Web is most commonly performed (semi-)automatically using instance matching frameworks. However, current instance matching benchmarks fail to provide end users and developers with the necessary insights pertaining to how current frameworks behave when dealing with real data. In this paper, we present the results of the evaluation of instance matching systems using Lance, a domain-independent, schema agnostic instance matching benchmark generator for Linked Data. Lance is the first benchmark generator for Linked Data to support semantics-aware test cases that take into account complex OWL constructs in addition to the standard test cases related to structure and value transformations. We provide a comparative analysis with benchmarks produced using the Lance framework for different domains to assess and identify the capabilities of state of the art instance matching systems.
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