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- Publisher Website: 10.1145/1835804.1835841
- Scopus: eid_2-s2.0-77956206690
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Conference Paper: Mining uncertain data with probabilistic guarantees
Title | Mining uncertain data with probabilistic guarantees |
---|---|
Authors | |
Keywords | Association rule Frequent pattern Uncertain data |
Issue Date | 2010 |
Citation | Proceedings Of The Acm Sigkdd International Conference On Knowledge Discovery And Data Mining, 2010, p. 273-282 How to Cite? |
Abstract | Data uncertainty is inherent in applications such as sensor monitoring systems, location-based services, and biological databases. To manage this vast amount of imprecise information, probabilistic databases have been recently developed. In this paper, we study the discovery of frequent patterns and association rules from probabilistic data under the Possible World Semantics. This is technically challenging, since a probabilistic database can have an exponential number of possible worlds. We propose two efficient algorithms, which discover frequent patterns in bottom-up and top-down manners. Both algorithms can be easily extended to discover maximal frequent patterns. We also explain how to use these patterns to generate association rules. Extensive experiments, using real and synthetic datasets, were conducted to validate the performance of our methods. © 2010 ACM. |
Description | Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010, p. 273-282 |
Persistent Identifier | http://hdl.handle.net/10722/125710 |
ISBN | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sun, L | en_HK |
dc.contributor.author | Cheng, R | en_HK |
dc.contributor.author | Cheung, DW | en_HK |
dc.contributor.author | Cheng, J | en_HK |
dc.date.accessioned | 2010-10-31T11:47:23Z | - |
dc.date.available | 2010-10-31T11:47:23Z | - |
dc.date.issued | 2010 | en_HK |
dc.identifier.citation | Proceedings Of The Acm Sigkdd International Conference On Knowledge Discovery And Data Mining, 2010, p. 273-282 | en_HK |
dc.identifier.isbn | 9781450300551 | - |
dc.identifier.uri | http://hdl.handle.net/10722/125710 | - |
dc.description | Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010, p. 273-282 | - |
dc.description.abstract | Data uncertainty is inherent in applications such as sensor monitoring systems, location-based services, and biological databases. To manage this vast amount of imprecise information, probabilistic databases have been recently developed. In this paper, we study the discovery of frequent patterns and association rules from probabilistic data under the Possible World Semantics. This is technically challenging, since a probabilistic database can have an exponential number of possible worlds. We propose two efficient algorithms, which discover frequent patterns in bottom-up and top-down manners. Both algorithms can be easily extended to discover maximal frequent patterns. We also explain how to use these patterns to generate association rules. Extensive experiments, using real and synthetic datasets, were conducted to validate the performance of our methods. © 2010 ACM. | en_HK |
dc.language | eng | en_HK |
dc.relation.ispartof | Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining | en_HK |
dc.subject | Association rule | en_HK |
dc.subject | Frequent pattern | en_HK |
dc.subject | Uncertain data | en_HK |
dc.title | Mining uncertain data with probabilistic guarantees | en_HK |
dc.type | Conference_Paper | en_HK |
dc.identifier.openurl | http://library.hku.hk:4550/resserv?sid=HKU:IR&issn=9781450300551&volume=&spage=273&epage=282&date=2010&atitle=Mining+uncertain+data+with+probabilistic+guarantees | - |
dc.identifier.email | Cheng, R:ckcheng@cs.hku.hk | en_HK |
dc.identifier.email | Cheung, DW:dcheung@cs.hku.hk | en_HK |
dc.identifier.authority | Cheng, R=rp00074 | en_HK |
dc.identifier.authority | Cheung, DW=rp00101 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1145/1835804.1835841 | en_HK |
dc.identifier.scopus | eid_2-s2.0-77956206690 | en_HK |
dc.identifier.hkuros | 175922 | en_HK |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-77956206690&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.spage | 273 | en_HK |
dc.identifier.epage | 282 | en_HK |
dc.identifier.scopusauthorid | Sun, L=36083786800 | en_HK |
dc.identifier.scopusauthorid | Cheng, R=7201955416 | en_HK |
dc.identifier.scopusauthorid | Cheung, DW=34567902600 | en_HK |
dc.identifier.scopusauthorid | Cheng, J=23391876200 | en_HK |