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- research-articleAugust 2009
Keyword querying and ranking in databases
Proceedings of the VLDB Endowment (PVLDB), Volume 2, Issue 2Pages 1658–1659https://doi.org/10.14778/1687553.1687622With the proliferation of data sources exposed through web interfaces to consumers, simple ways of exploring contents of such databases are of increasing importance. Examples include users wishing to search catalogs of homes, cars, cameras, restaurants, ...
- research-articleJune 2009
Privacy preservation of aggregates in hidden databases: why and how?
SIGMOD '09: Proceedings of the 2009 ACM SIGMOD International Conference on Management of dataJune 2009, Pages 153–164https://doi.org/10.1145/1559845.1559863Many websites provide form-like interfaces which allow users to execute search queries on the underlying hidden databases. In this paper, we explain the importance of protecting sensitive aggregate information of hidden databases from being disclosed ...
- research-articleMarch 2009
Ranking objects based on relationships and fixed associations
EDBT '09: Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database TechnologyMarch 2009, Pages 910–921https://doi.org/10.1145/1516360.1516464Text corpora are often enhanced by additional metadata which relate real-world entities, with each document in which such entities are discussed. Such relationships are typically obtained through widely available Information Extraction tools. At the ...
- articleJune 2007
Optimized stratified sampling for approximate query processing
ACM Transactions on Database Systems (TODS), Volume 32, Issue 2Pages 9–eshttps://doi.org/10.1145/1242524.1242526The ability to approximately answer aggregation queries accurately and efficiently is of great benefit for decision support and data mining tools. In contrast to previous sampling-based studies, we treat the problem as an optimization problem where, ...
- articleSeptember 2006
Probabilistic information retrieval approach for ranking of database query results
ACM Transactions on Database Systems (TODS), Volume 31, Issue 3Pages 1134–1168https://doi.org/10.1145/1166074.1166085We investigate the problem of ranking the answers to a database query when many tuples are returned. In particular, we present methodologies to tackle the problem for conjunctive and range queries, by adapting and applying principles of probabilistic ...
- ArticleAugust 2004
Probabilistic ranking of database query results
VLDB '04: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30August 2004, Pages 888–899We investigate the problem of ranking answers to a database query when many tuples are returned. We adapt and apply principles of probabilistic models from Information Retrieval for structured data. Our proposed solution is domain independent. It ...
- ArticleJune 2004
Effective use of block-level sampling in statistics estimation
SIGMOD '04: Proceedings of the 2004 ACM SIGMOD international conference on Management of dataJune 2004, Pages 287–298https://doi.org/10.1145/1007568.1007602Block-level sampling is far more efficient than true uniform-random sampling over a large database, but prone to significant errors if used to create database statistics. In this paper, we develop principled approaches to overcome this limitation of ...
- ArticleJune 2003
Dynamic sample selection for approximate query processing
SIGMOD '03: Proceedings of the 2003 ACM SIGMOD international conference on Management of dataJune 2003, Pages 539–550https://doi.org/10.1145/872757.872822In decision support applications, the ability to provide fast approximate answers to aggregation queries is desirable. One commonly-used technique for approximate query answering is sampling. For many aggregation queries, appropriately constructed ...
- ArticleMay 2001
A robust, optimization-based approach for approximate answering of aggregate queries
SIGMOD '01: Proceedings of the 2001 ACM SIGMOD international conference on Management of dataMay 2001, Pages 295–306https://doi.org/10.1145/375663.375694The ability to approximately answer aggregation queries accurately and efficiently is of great benefit for decision support and data mining tools. In contrast to previous sampling-based studies, we treat the problem as an optimization problem whose goal ...
Also Published in:
ACM SIGMOD Record: Volume 30 Issue 2, June 2001