Institutional Repository
Technical University of Crete
Technical University of Crete
EN
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EL
| URI: | http://purl.tuc.gr/dl/dias/D4893A56-E33D-4BDB-8414-A93DDC1A06E9 | ||
| Year | 2015 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
| License |
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| Bibliographic Citation | A. Ioannou and M. Garofalakis, "Query analytics over probabilistic databases with unmerged duplicates", IEEE Trans. Knowl. Data Eng., vol. 27, no. 8, pp. 2245-2260, Aug. 2015. doi:10.1109/TKDE.2015.2405507 https://doi.org/10.1109/TKDE.2015.2405507 | ||
| Appears in Collections |
Recent entity resolution approaches exhibit benefits when addressing the problem through unmerged duplicates: instances describing real-world objects are not merged based on apriori thresholds or human intervention, instead relevant resolution information is employed for evaluating resolution decisions during query processing using “possible worlds” semantics. In this paper, we present the first known approach for efficiently handling complex analytical queries over probabilistic databases with unmerged duplicates. We propose the ENTITY-JOIN operator that allows expressing complex aggregation and iceberg/top-k queries over joins between tables with unmerged duplicates and other database tables. Our technical content includes a novel indexing structure for efficient access to the entity resolution information and novel techniques for the efficient evaluation of complex probabilistic queries that retrieve analytical and summarized information over a (potentially, huge) collection of possible resolution worlds. Our extensive experimental evaluation verifies the benefits of our approach.
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