Ergebnisse für: data matching
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Data matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains inc...
Data matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains inc...
Data matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains inc...
Motion estimation is likely the most crucial task in video based computer vision, as it connects the information in consecutive images.
While priors are often required for good motion estimation, matching the available data still stays the most essential part as it depends on the actual image cont...
There is more statistical data produced in today's modern society than ever before. This data is analysed and cross-referenced for innumerable reasons. However, many data sets have no shared element and are harder to combine and therefore obtain any meaningful inference from. Statistical matching al...
Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in g...
Ontologies are viewed as the silver bullet for many applications, but in open or evolving systems, different parties can adopt different ontologies. This increases heterogeneity problems rather than reducing heterogeneity. This book proposes ontology matching as a solution to the problem of semantic...
When it comes to managing data as a strategic asset, creating transparency with regard to a company's data assets and making them available to users is critical. To master this challenge, companies have started to build up and use a Data Catalog, or plan to do so. Despite the proliferation of the co...
The book focuses on Schema Matching, the task of (semi-)automatically identifying semantic correspondences between elements of metadata structures, such as, database schemas, ontologies, and XML message formats. It is of key importance for interoperability and data integration in numerous applicatio...
Data fusion or statistical file matching techniques merge data sets from different survey samples to solve the problem that exists when no single file contains all the variables of interest. Media agencies are merging television and purchasing data, statistical offices match tax information with inc...