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- Publisher Website: 10.1109/ICDE.2006.54
- Scopus: eid_2-s2.0-33749624867
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Conference Paper: Efficient aggregation of ranked inputs
Title | Efficient aggregation of ranked inputs |
---|---|
Authors | |
Issue Date | 2006 |
Citation | Proceedings - International Conference On Data Engineering, 2006, v. 2006, p. 72 How to Cite? |
Abstract | A top-k query combines different rankings of the same set of objects and returns the k objects with the highest combined score according to an aggregate function. We bring to light some key observations, which Impose two phases that any top-k algorithm, based on sorted accesses, should go through. Based on them, we propose a new algorithm, which Is designed to minimize the number of object accesses, the computational cost, and the memory requirements of top-k search. Adaptations of our algorithm for search variants (exact scores, on-line and Incremental search, top-k joins, other aggregate functions, etc.) are also provided. Extensive experiments with synthetic and real data show that, compared to previous techniques, our method accesses fewer objects, while being orders of magnitude faster. © 2006 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/93188 |
ISSN | 2023 SCImago Journal Rankings: 1.306 |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mamoulis, N | en_HK |
dc.contributor.author | Cheng, KH | en_HK |
dc.contributor.author | Yiu, ML | en_HK |
dc.contributor.author | Cheung, DW | en_HK |
dc.date.accessioned | 2010-09-25T14:53:33Z | - |
dc.date.available | 2010-09-25T14:53:33Z | - |
dc.date.issued | 2006 | en_HK |
dc.identifier.citation | Proceedings - International Conference On Data Engineering, 2006, v. 2006, p. 72 | en_HK |
dc.identifier.issn | 1084-4627 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/93188 | - |
dc.description.abstract | A top-k query combines different rankings of the same set of objects and returns the k objects with the highest combined score according to an aggregate function. We bring to light some key observations, which Impose two phases that any top-k algorithm, based on sorted accesses, should go through. Based on them, we propose a new algorithm, which Is designed to minimize the number of object accesses, the computational cost, and the memory requirements of top-k search. Adaptations of our algorithm for search variants (exact scores, on-line and Incremental search, top-k joins, other aggregate functions, etc.) are also provided. Extensive experiments with synthetic and real data show that, compared to previous techniques, our method accesses fewer objects, while being orders of magnitude faster. © 2006 IEEE. | en_HK |
dc.language | eng | en_HK |
dc.relation.ispartof | Proceedings - International Conference on Data Engineering | en_HK |
dc.title | Efficient aggregation of ranked inputs | en_HK |
dc.type | Conference_Paper | en_HK |
dc.identifier.email | Mamoulis, N:nikos@cs.hku.hk | en_HK |
dc.identifier.email | Cheung, DW:dcheung@cs.hku.hk | en_HK |
dc.identifier.authority | Mamoulis, N=rp00155 | en_HK |
dc.identifier.authority | Cheung, DW=rp00101 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/ICDE.2006.54 | en_HK |
dc.identifier.scopus | eid_2-s2.0-33749624867 | en_HK |
dc.identifier.hkuros | 122084 | en_HK |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-33749624867&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 2006 | en_HK |
dc.identifier.spage | 72 | en_HK |
dc.identifier.epage | 72 | en_HK |
dc.publisher.place | United States | en_HK |
dc.identifier.scopusauthorid | Mamoulis, N=6701782749 | en_HK |
dc.identifier.scopusauthorid | Cheng, KH=34467513500 | en_HK |
dc.identifier.scopusauthorid | Yiu, ML=8589889600 | en_HK |
dc.identifier.scopusauthorid | Cheung, DW=34567902600 | en_HK |
dc.identifier.issnl | 1084-4627 | - |