File Download
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1109/ICDE.2012.14
- Scopus: eid_2-s2.0-84864204535
- WOS: WOS:000309122100096
- Find via
Supplementary
- Citations:
- Appears in Collections:
Conference Paper: Evaluating probabilistic queries over uncertain matching
Title | Evaluating probabilistic queries over uncertain matching |
---|---|
Authors | |
Keywords | Database schemas Fast algorithms Machine learning techniques Query evaluation Query performance |
Issue Date | 2012 |
Publisher | IEEE Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000178 |
Citation | The IEEE 28th International Conference on Data Engineering (ICDE 2012), Washington, D.C., 1-5 April 2012. In International Conference on Data Engineering Proceedings, 2012, p. 1096-1107 How to Cite? |
Abstract | A matching between two database schemas, generated by machine learning techniques (e.g., COMA++), is often uncertain. Handling the uncertainty of schema matching has recently raised a lot of research interest, because the quality of applications rely on the matching result. We study query evaluation over an inexact schema matching, which is represented as a set of 'possible mappings', as well as the probabilities that they are correct. Since the number of possible mappings can be large, evaluating queries through these mappings can be expensive. By observing the fact that the possible mappings between two schemas often exhibit a high degree of overlap, we develop two efficient solutions. We also present a fast algorithm to compute answers with the k highest probabilities. An extensive evaluation on real schemas shows that our approaches improve the query performance by almost an order of magnitude. © 2012 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/164909 |
ISSN | 2023 SCImago Journal Rankings: 1.306 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cheng, R | en_US |
dc.contributor.author | Gong, J | en_US |
dc.contributor.author | Cheung, DWL | en_US |
dc.contributor.author | Cheng, J | en_US |
dc.date.accessioned | 2012-09-20T08:12:20Z | - |
dc.date.available | 2012-09-20T08:12:20Z | - |
dc.date.issued | 2012 | en_US |
dc.identifier.citation | The IEEE 28th International Conference on Data Engineering (ICDE 2012), Washington, D.C., 1-5 April 2012. In International Conference on Data Engineering Proceedings, 2012, p. 1096-1107 | en_US |
dc.identifier.issn | 1084-4627 | - |
dc.identifier.uri | http://hdl.handle.net/10722/164909 | - |
dc.description.abstract | A matching between two database schemas, generated by machine learning techniques (e.g., COMA++), is often uncertain. Handling the uncertainty of schema matching has recently raised a lot of research interest, because the quality of applications rely on the matching result. We study query evaluation over an inexact schema matching, which is represented as a set of 'possible mappings', as well as the probabilities that they are correct. Since the number of possible mappings can be large, evaluating queries through these mappings can be expensive. By observing the fact that the possible mappings between two schemas often exhibit a high degree of overlap, we develop two efficient solutions. We also present a fast algorithm to compute answers with the k highest probabilities. An extensive evaluation on real schemas shows that our approaches improve the query performance by almost an order of magnitude. © 2012 IEEE. | - |
dc.language | eng | en_US |
dc.publisher | IEEE Computer Society. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000178 | - |
dc.relation.ispartof | International Conference on Data Engineering Proceedings | en_US |
dc.subject | Database schemas | - |
dc.subject | Fast algorithms | - |
dc.subject | Machine learning techniques | - |
dc.subject | Query evaluation | - |
dc.subject | Query performance | - |
dc.title | Evaluating probabilistic queries over uncertain matching | en_US |
dc.type | Conference_Paper | en_US |
dc.identifier.email | Cheng, R: ckcheng@cs.hku.hk | en_US |
dc.identifier.email | Gong, J: jgong@cs.hku.hk | en_US |
dc.identifier.email | Cheung, DWL: dcheung@cs.hku.hk | en_US |
dc.identifier.email | Cheng, J: jf.cheng@siat.ac.cn | - |
dc.identifier.authority | Cheng, R=rp00074 | en_US |
dc.identifier.authority | Cheung, DWL=rp00101 | en_US |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/ICDE.2012.14 | - |
dc.identifier.scopus | eid_2-s2.0-84864204535 | - |
dc.identifier.hkuros | 206213 | en_US |
dc.identifier.spage | 1096 | - |
dc.identifier.epage | 1107 | - |
dc.identifier.isi | WOS:000309122100096 | - |
dc.publisher.place | United States | - |
dc.description.other | The IEEE 28th International Conference on Data Engineering (ICDE 2012), Washington, D.C., 1-5 April 2012. In International Conference on Data Engineering Proceedings, 2012, p. 1096-1107 | - |
dc.identifier.issnl | 1084-4627 | - |