The problem of creating mappings between schemas is an unavoidable and time-consuming step in the design of many types of large-scale commercial applications: in transaction processing and enterprise application integration, to help map messages between different XML formats; in data warehouses, to map data sources into warehouse schemas; and in web portals, to identify points of integration be...

Schema heterogeneity issues often represent an obstacle for discovering coreference links between individuals in semantic data repositories. In this paper we present an approach, which performs ontology schema matching in order to improve instance coreference resolution performance. A novel feature of the approach is its use of existing instancelevel coreference links defined in third-party rep...

The access to heterogeneous data through their metadata needs a matching process of the metadata schemas. This process identifies the correspondence relations called “Mappings” between the schemas to identify a global schema. This latter allows a uniform access to heterogeneous data. In this context, several works are proposed. However, the obtained mappings and the global schema are identified...

Schema heterogeneity issues often represent an obstacle for discovering coreference links between individuals in semantic data repositories. In this paper we present an approach, which performs ontology schema matching in order to improve instance coreference resolution performance. A novel feature of the approach is its use of existing instancelevel coreference links defined in third-party rep...

Schema integration is the process of consolidating several source schemas to generate a unified view, called the mediated schema, so that information scattered in the sources can be served uniformly from the mediated schema. Schema integration occurs in many scenarios such as data integration, logical database design, data warehousing and schema evolution. To make the mediated schema useful for...

In this paper, we present a new method for database schema matching, the problem of identifying elements of two given schemas that correspond to each other. We use two methods based on a large text corpus: one method for determining the semantic similarity of two target words and the other for automatic word segmentation. We present a name-based element-level database schema matching method tha...

Schema and ontology matching have attracted a great deal of interest among researchers. Despite the advances achieved, the large matching problem still presents a real challenge, such as it is a timeconsuming and memory-intensive process. We therefore propose a scalable, clustering-based matching approach that breaks up the large matching problem into smaller matching problems. In particular, w...

Current schema matching approaches still have to improve for large and complex Schemas. The large search space increases the likelihood for false matches as well as execution times. Further difficulties for Schema matching are posed by the high expressive power and versatility of modern schema languages, in particular user-defined types and classes, component reuse capabilities, and support for...

Schema heterogeneity issues often represent an obstacle for discovering coreference links between individuals in semantic data repositories. In this paper we present an approach, which performs ontology schema matching in order to improve instance coreference resolution performance. A novel feature of the approach is its use of existing instancelevel coreference links defined in third-party rep...

Purpose – Most digital libraries (DLs) are now available online. They also provide the Z39.50 standard protocol which allows computer-based systems to effectively retrieve information stored in the DLs. The major difficulty lies in inconsistency between database schemas of multiple DLs. This paper presents a system known as Argumentation-based Digital Library Search (or ADLSearch) which facilit...