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Partial symbol ordering distance
dc.contributor.author | Herranz Sotoca, Javier |
dc.contributor.author | Nin Guerrero, Jordi |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors |
dc.date.accessioned | 2010-07-27T08:02:58Z |
dc.date.available | 2010-07-27T08:02:58Z |
dc.date.created | 2009 |
dc.date.issued | 2009 |
dc.identifier.citation | Herranz, J.; Nin, J. Partial symbol ordering distance. A: International Conference on Modeling Decisions for Artificial Intelligence. "6th International Conference on Modeling Decisions for Artificial Intelligence". Awaji Isl (Japan): Springer Verlag, 2009, p. 293-302. |
dc.identifier.isbn | 978-3-642-04819-7 |
dc.identifier.uri | http://hdl.handle.net/2117/8407 |
dc.description.abstract | Nowadays sequences of symbols are becoming more important, as they are the standard format for representing information in a large variety of domains such as ontologies, sequential patterns or non numerical attributes in databases. Therefore, the development of new distances for this kind of data is a crucial need. Recently, many similarity functions have been proposed for managing sequences of symbols; however, such functions do not always hold the triangular inequality. This property is a mandatory requirement in many data mining algorithms like clustering or k-nearest neighbors algorithms, where the presence of a metric space is a must. In this paper, we propose a new distance for sequences of (non-repeated) symbols based on the partial distances between the positions of the common symbols. We prove that this Partial Symbol Ordering distance satisfies the triangular inequality property, and we finally describe a set of experiments supporting that the new distance outperforms the Edit distance in those ecenarios where sequence similarity is related to the positions occupied by the symbols. |
dc.format.extent | 10 p. |
dc.language.iso | eng |
dc.publisher | Springer Verlag |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial |
dc.subject.lcsh | Artificial intelligence --Data processing |
dc.subject.lcsh | Artificial intelligence --Mathematical models |
dc.subject.other | Sequences of symbols Distances Triangular inequality |
dc.title | Partial symbol ordering distance |
dc.type | Conference report |
dc.subject.lemac | Intel·ligència artificial -- Processament de dades -- Congressos |
dc.subject.lemac | Intel·ligència artificial -- Models matemàtics |
dc.contributor.group | Universitat Politècnica de Catalunya. MAK - Matemàtica Aplicada a la Criptografia |
dc.identifier.doi | 10.1007/978-3-642-04820-3_27 |
dc.subject.inspec | Classificació INSPEC::Cybernetics::Artificial intelligence |
dc.relation.publisherversion | http://www.springerlink.com/content/g0w1m6v4u2851407/ |
dc.rights.access | Restricted access - publisher's policy |
local.identifier.drac | 2524303 |
dc.description.version | Postprint (published version) |
local.citation.author | Herranz, J.; Nin, J. |
local.citation.contributor | International Conference on Modeling Decisions for Artificial Intelligence |
local.citation.pubplace | Awaji Isl (Japan) |
local.citation.publicationName | 6th International Conference on Modeling Decisions for Artificial Intelligence |
local.citation.startingPage | 293 |
local.citation.endingPage | 302 |