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2010

Building Ranked Mashups of Unstructured Sources with Uncertain Information

8 years 10 months ago
Building Ranked Mashups of Unstructured Sources with Uncertain Information
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 attributes. MashRank is based on new semantics, formulations and processing techniques to handle uncertain preference scores, represented as intervals enclosing possible score values. MashRank integrates information extraction with query processing by asynchronously pushing extracted data on-the-fly into pipelined rank-aware query plans, and using ranking early-out requirements to limit extraction cost. To the best of our knowledge, both the technical problems and target applications of MashRank have...
Mohamed A. Soliman, Ihab F. Ilyas, Mina Saleeb
Added 30 Jan 2011
Updated 30 Jan 2011
Type Journal
Year 2010
Where PVLDB
Authors Mohamed A. Soliman, Ihab F. Ilyas, Mina Saleeb
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