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Building ranked mashups of unstructured sources with uncertain information
2010
Proceedings of the VLDB Endowment
Mashups are situational applications that join multiple sources to better meet the information needs of Web users. Web sources can be huge databases behind query interfaces, which triggers the need of ranking mashup results based on some user preferences. We present MashRank, a mashup authoring and processing system building on concepts from rank-aware processing, probabilistic databases, and information extraction to enable ranked mashups of (unstructured) sources with uncertain ranking
doi:10.14778/1920841.1920947
fatcat:3n2fnluwfjbsxeru2rog2am7dy