Integration of semistructured data with partial and inconsistent information
Mengchi Liu, Tok Wang Ling, Tao Guan · 2003
Data integration from several sources has gained considerable attention with the recent popularity of the World Wide Web. In the real world, some information may be missing (i.e. partial) and some may be inconsistent from several sources. How to obtain information that is as complete as possible and how to detect inconsistency from these sources is thus an interesting question. Most existing work uses a simple graph-based or tree-based semistructured data model to represent heterogeneous data coming from various sites, which fails to account for the existence of partial and inconsistent information. In this paper, we redefine the notion of semistructured objects to reflect the existence of partial and inconsistent information and study how to integrate such objects spread over various sources and check their consistency in the meantime. We propose a new integration operator for this purpose and discuss its semantic properties.