2014Unpublished venueRequires access

A schema matching approach for structured data fusion

Bunyamin Dursun, Murat Obali

Open publisher page 1 citations

Abstract

Joint picture and fusion of data that is acquired from different data sources is a complex and difficult process. One of the basic approaches in data fusion or data integration is schema matching. In contrast doing schema matching manually in many applications, it takes long time and many matching elements and situations are missed. It is very important to make schema matching automatically, since many systems can be fused and joint picture can be constructed right and fast. In this study, we propose a schema matching approach on structured data and we applied this approach on databases of an enterprise.

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What this paper is about

Joint picture and fusion of data that is acquired from different data sources is a complex and difficult process. One of the basic approaches in data fusion or data integration is schema matching. In contrast doing schema matching manually in many applications, it takes long time and many matching elements and situations are missed. It is very important to make schema matching automatically, since many systems can be fused and joint picture can be constructed right and fast. In this study, we propose a schema matching approach on structured data and we applied this approach on databases of an enterprise.

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Available abstract

Joint picture and fusion of data that is acquired from different data sources is a complex and difficult process. One of the basic approaches in data fusion or data integration is schema matching. In contrast doing schema matching manually in many applications, it takes long time and many matching elements and situations are missed. It is very important to make schema matching automatically, since many systems can be fused and joint picture can be constructed right and fast. In this study, we propose a schema matching approach on structured data and we applied this approach on databases of an enterprise.

Key concepts: Schema matching, Computer science, Data integration, Schema (genetic algorithms), Star schema, Matching (statistics), Information schema, Conceptual schema

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