Context-based Entity Description Rule for Entity Resolution

摘要

In this paper, we consider the entity resolution(ER) problem, which is to identify objects referring to the same real-world entity. Prior work of ER involves expensive similarity comparison and clustering approaches. Additionally, the quality of entity-resolution may be low due to insufficient information. To address these problems, by adopting context information of data objects, we present a novel framework of entity resolution, context-based entity description (CED), to make context information help entity-resolution. In our framework, each entity is described by a set of CEDs. During entity resolution, objects are only compared with CEDs to determine its corresponding entity. Additionally, we propose efficient algorithms for CED discovery and CED-based entity resolution. We experimentally evaluated our CED-based ER algorithm on the real DBLP datasets, and the experimental results show that our algorithm can achieve both high precision and recall as well as outperform existing methods.