Associated index for big structured and unstructured data

Abstract

In big data epoch, one of the major challenges is the large volume of mixed structured and unstructured data. Because of different form, structured and unstructured data are often considered apart from each other. However, they may speak about the same entities of the world. If a query involves both structured data and its unstructured counterpart, it is inefficient to execute it separately. The paper presents a novel index structure tailored towards associations between structured and unstructured data, based on entity co-occurrences. It is also a semantic index represented as RDF graphs which describes the semantic relationships among entities. Experiments show that the associated index can not only provide apposite information but also execute queries efficiently.