Big Data Integration
Big Data Integration
Big data challenges existing integration methods due to the volume, velocity, variety, and veracity characteristics. The research group of Prof. Avigdor Gal aims at proposing novel models and algorithms for data integration in the big data era.
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SCHEMA MATCHING
Solving matching problems in computer science entails generating alignments between structured data. Well known examples are schema matching, process model matching, ontology alignment, and Web service composition. Design of software systems aimed at solving these problems, and reļ¬nement of interim results, are aided by solution quality evaluation measures.
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Entity Resolution
integration of data has been the focus of research for many years now. At the data level, entity resolution (also known as record deduplication) aims at "cleaning'' a database by identifying tuples that represent the same entity
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big data integration
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SCHEMA MATCHING
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Entity Resolution
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