Abstract

The standard way of reconstructing the entities will involve joining the tables. Because of the autonomous and decentralized way in which the sources are populated, they often do not have Primary Key - Foreign Key relations. To answer queries effectively, we need to integrate the information about the individual entities that are fragmented over multiple sources. For instance, a pattern-based method (PaRE) uses extracted patterns as the auxiliary information in formulating search queries. However, high-quality patterns may decrease the probability of finding suitable target entities. As an alternative, a CoRE method is proposed that uses context terms learned surrounding the expression of a relation as the auxiliary information in formulating queries. The experimental results based on several real-world web data collections demonstrate that CoRE reaches a much higher accuracy than PaRE for the purpose of RC.

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