Instance Coreference Resolution in Multi-ontology Linked Data Resources

Web of linked data is one of the main principles for realization of semantic web ideals. In recent years, different data providers have produced many data sources in the Linking Open Data (LOD) cloud upon different schemas. Isolated published linked data sources are not themselves so beneficial for intelligent applications and agents in the context of semantic web. It is not possible to take advantage of the linked data potential capacity without integrating various data sources. The challenge of integration is not limited to instances; rather, schema heterogeneity affects discovering instances with the same identity. In this paper we propose a novel approach, SBUEI, for instance co-reference resolution between various linked data sources even with heterogeneous schemas. For this purpose, SBUEI considers the entity co-reference resolution problem in both schema and instance levels. The process of matching is applied in both levels consecutively to let the system discover identical instances. SBUEI also applies a new approach for consolidation of linked data in instance level. After finding identical instances, SBUEI searches locally around them in order to find more instances that are equal. Experiments show that SBUEI obtains promising results with high precision and recall.

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