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A kernel based method for discovering market segments in beef meat
dc.contributor.author | Díez Peláez, Jorge | |
dc.contributor.author | Coz Velasco, Juan José del | |
dc.contributor.author | Sañudo, Carlos | |
dc.contributor.author | Albertí, P. | |
dc.contributor.author | Bahamonde Rionda, Antonio | |
dc.date.accessioned | 2015-06-16T10:05:22Z | |
dc.date.available | 2015-06-16T10:05:22Z | |
dc.date.issued | 2005 | |
dc.identifier.isbn | 978-3-540-29244-9 | |
dc.identifier.uri | http://hdl.handle.net/10651/31248 | |
dc.description | 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal | spa |
dc.description.abstract | In this paper we propose a method for learning the reasons why groups of consumers prefer some food products instead of others of the same type. We emphasize the role of groups given that, from a practical point of view, they may represent market segments that demand different products. Our method starts representing people’s preferences in a metric space; there we are able to define a kernel based similarity function that allows a clustering algorithm to discover significant groups of consumers with homogeneous tastes. Finally in each cluster, we learn, with a SVM, a function that explains the tastes of the consumers grouped in the cluster. To illustrate our method, a real case of consumers of beef meat was studied. The panel was formed by 171 people who rated 303 samples of meat from 101 animals with 3 different aging periods | |
dc.format.extent | p. 462-469 | spa |
dc.language.iso | eng | spa |
dc.publisher | Springer | spa |
dc.relation.ispartof | Knowledge Discovery in Databases: PKDD 2005 | spa |
dc.rights | © 2005 Springer | |
dc.title | A kernel based method for discovering market segments in beef meat | eng |
dc.type | book part | spa |
dc.identifier.doi | 10.1007/11564126_46 | |
dc.relation.publisherversion | http://dx.doi.org/10.1007/11564126_46 | spa |
dc.rights.accessRights | open access |
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