Leveraging the Storage Layer to Support XML Similarity Joins in XDBMSs

Abstract

XML is widely applied to describe semi-structured data commonly generated and used by modern information systems. XML database management systems (XDBMSs) are thus essential platforms in this context. Most XDBMS architectures proposed so far aim at reproducing functionalities found in relational systems. As such, these architectures inherit the same deficiency of traditional systems in dealing with less-structured data. What is badly needed is efficient support of common database operations under the similarity matching paradigm. In this paper, we present an engineering approach to incorporating similarity joins into XDBMSs, which exploits XDBMS components--the storage layer in particular--to design efficient algorithms. We experimentally confirm the accuracy, performance, and scalability of our approach.