Query by Output
| dc.contributor.author | TRAN, Quoc Trung | en_US |
| dc.contributor.author | CHAN, Chee Yong | en_US |
| dc.contributor.author | PARTHASARATHY, Srinivasan | en_US |
| dc.date.accessioned | 2009-04-27T01:38:01Z | en_US |
| dc.date.accessioned | 2017-01-23T07:00:12Z | |
| dc.date.available | 2009-04-27T01:38:01Z | en_US |
| dc.date.available | 2017-01-23T07:00:12Z | |
| dc.date.issued | 2009-04-17 | en_US |
| dc.description.abstract | It has recently been asserted that the usability of a database is as important as its capability. Understanding the database schema,the hidden relationships among attributes in the data all play an important role in this context. Subscribing to this viewpoint, in this paper, we present a novel data-driven approach, called Query By Output (QBO), which can enhance the usability of database systems. The central goal of QBO is as follows: given the output of some query Q on a database D, denoted by Q(D), we wish to construct an alternative query Q0 such that Q(D) and Q0(D) are instance-equivalent. To generate instance-equivalent queries from Q(D), we devise a novel data classi¯cation-based technique that can handle the at-least-one semantics that is inherent in the query derivation. In addition to the basic framework, we design several optimization techniques to reduce processing overhead and introduce a set of criteria to rank order output queries by various notions of utility. Our framework is evaluated comprehensively on three real data sets and the results show that the instance-equivalent queries we obtain are interesting and that the approach is scalable and robust to queries of di®erent selectivities. | en_US |
| dc.format.extent | 560553 bytes | en_US |
| dc.format.mimetype | application/pdf | en_US |
| dc.identifier.uri | https://dl.comp.nus.edu.sg/xmlui/handle/1900.100/2938 | en_US |
| dc.language.iso | en | en_US |
| dc.relation.ispartofseries | TRA4/09 | en_US |
| dc.title | Query by Output | en_US |
| dc.type | Technical Report | en_US |