Schema Matching and Integration When schemas are in thousands
Matching Schemas for integration and create mappings between source schemas and integrated schema
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In literature one can find numerous works on the subject of schema matching and integration. Under normal circumstances the methods employed are ideal for matching two schemas. But with the Web scale data sources availability, these techniques need to be enhanced. Querying schemas over web requires more robust and performance oriented techniques which have the capacity to cope with the large scale scenarios, where hundreds and thousands of schemas need to be matched for integration or data exchange. For a single query on the web, hundreds of schemas in the subject domain need to be scrutinized...
In literature one can find numerous works on the subject of schema matching and integration. Under normal circumstances the methods employed are ideal for matching two schemas. But with the Web scale data sources availability, these techniques need to be enhanced. Querying schemas over web requires more robust and performance oriented techniques which have the capacity to cope with the large scale scenarios, where hundreds and thousands of schemas need to be matched for integration or data exchange. For a single query on the web, hundreds of schemas in the subject domain need to be scrutinized, to get the right information stored against them. The dynamic nature of web makes the scenario very difficult to comprehend by humans as well as software systems, for retrieval of good results. The work presented in this book is motivated by these large scale schema matching and integration applications. The book gives a detail explanation of research done in this domain. A hybrid approachutilizing tree mining technique is explained, to tackle the large scale scenario. Further, the same tree mining algorithm is extended to compute complex schema matching.
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