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- Publisher Website: 10.1145/1401890.1401940
- Scopus: eid_2-s2.0-65449132475
Conference Paper: Mining preferences from superior and inferior examples
Title | Mining preferences from superior and inferior examples |
---|---|
Authors | |
Keywords | Inferior examples Preferences Skyline Superior examples |
Issue Date | 2008 |
Citation | Proceedings Of The Acm Sigkdd International Conference On Knowledge Discovery And Data Mining, 2008, p. 390-398 How to Cite? |
Abstract | Mining user preferences plays a critical role in many important applications such as customer relationship management (CRM), product and service recommendation, and marketing campaigns. In this paper, we identify an interesting and practical problem of mining user preferences: in a multidimensional space where the user preferences on some categorical attributes are unknown, from some superior and inferior examples provided by a user, can we learn about the user's preferences on those categorical attributes? We model the problem systematically and show that mining user preferences from superior and inferior examples is challenging. Although the problem has great potential in practice, to the best of our knowledge, it has not been explored systematically before. As the first attempt to tackle the problem, we propose a greedy method and show that our method is practical using real data sets and synthetic data sets. Copyright 2008 ACM. |
Description | The 14th ACM SIGKDD conference (KDD 2008) |
Persistent Identifier | http://hdl.handle.net/10722/61144 |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jiang, B | en_HK |
dc.contributor.author | Pei, J | en_HK |
dc.contributor.author | Lin, X | en_HK |
dc.contributor.author | Cheung, DW | en_HK |
dc.contributor.author | Han, J | en_HK |
dc.date.accessioned | 2010-07-13T03:31:36Z | - |
dc.date.available | 2010-07-13T03:31:36Z | - |
dc.date.issued | 2008 | en_HK |
dc.identifier.citation | Proceedings Of The Acm Sigkdd International Conference On Knowledge Discovery And Data Mining, 2008, p. 390-398 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/61144 | - |
dc.description | The 14th ACM SIGKDD conference (KDD 2008) | en_HK |
dc.description.abstract | Mining user preferences plays a critical role in many important applications such as customer relationship management (CRM), product and service recommendation, and marketing campaigns. In this paper, we identify an interesting and practical problem of mining user preferences: in a multidimensional space where the user preferences on some categorical attributes are unknown, from some superior and inferior examples provided by a user, can we learn about the user's preferences on those categorical attributes? We model the problem systematically and show that mining user preferences from superior and inferior examples is challenging. Although the problem has great potential in practice, to the best of our knowledge, it has not been explored systematically before. As the first attempt to tackle the problem, we propose a greedy method and show that our method is practical using real data sets and synthetic data sets. Copyright 2008 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 | Inferior examples | en_HK |
dc.subject | Preferences | en_HK |
dc.subject | Skyline | en_HK |
dc.subject | Superior examples | en_HK |
dc.title | Mining preferences from superior and inferior examples | en_HK |
dc.type | Conference_Paper | en_HK |
dc.identifier.email | Cheung, DW:dcheung@cs.hku.hk | en_HK |
dc.identifier.authority | Cheung, DW=rp00101 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1145/1401890.1401940 | en_HK |
dc.identifier.scopus | eid_2-s2.0-65449132475 | en_HK |
dc.identifier.hkuros | 149704 | en_HK |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-65449132475&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.spage | 390 | en_HK |
dc.identifier.epage | 398 | en_HK |
dc.identifier.scopusauthorid | Jiang, B=54887688500 | en_HK |
dc.identifier.scopusauthorid | Pei, J=35273378100 | en_HK |
dc.identifier.scopusauthorid | Lin, X=7404513092 | en_HK |
dc.identifier.scopusauthorid | Cheung, DW=34567902600 | en_HK |
dc.identifier.scopusauthorid | Han, J=27170191900 | en_HK |
dc.identifier.citeulike | 3367657 | - |