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dc.date.accessioned | 2012-11-08T15:09:30Z | |
dc.date.available | 2012-11-08T15:09:30Z | |
dc.date.issued | 2006-08 | |
dc.identifier.uri | http://sedici.unlp.edu.ar/handle/10915/23890 | |
dc.description.abstract | This paper introduces an automatic procedure to assist on the interpretation of a large dataset when a similarity metric is available. We propose a visualization approach based on a graph layout method- ology that uses a Quadratic Assignment Problem (QAP) formulation. The methodology is presented using as testbed a time series dataset of the Standard & Poor’s 100, one the leading stock market indicators in the United States. A weighted graph is created with the stocks repre- sented by the nodes and the edges’ weights are related to the correlation between the stocks’ time series. A heuristic for clustering is then pro- posed; it is based on the graph partition into disconnected subgraphs allowing the identification of clusters of highly-correlated stocks. The final layout corresponds well with the perceived market notion of the different industrial sectors. We compare the output of this procedure with a traditional dendogram approach of hierarchical clustering | en |
dc.language | en | es |
dc.subject | Quadratic Assignment Problem (QAP) | en |
dc.subject | Similarity measures | es |
dc.subject | Heuristic methods | es |
dc.subject | hierarchical clustering | en |
dc.title | An automatic graph layout procedure to visualize correlated data | en |
dc.type | Objeto de conferencia | es |
sedici.identifier.isbn | 0-387-34654-6 | es |
sedici.creator.person | Moscato, Pablo | es |
sedici.creator.person | Inostroza-Ponta, Mario | es |
sedici.creator.person | Berretta, Regina | es |
sedici.creator.person | Mendes, Alexandre | es |
sedici.description.note | IFIP International Conference on Artificial Intelligence in Theory and Practice - Knowledge Acquisition and Data Mining | es |
sedici.subject.materias | Ciencias Informáticas | es |
sedici.description.fulltext | true | es |
mods.originInfo.place | Red de Universidades con Carreras en Informática (RedUNCI) | es |
sedici.subtype | Objeto de conferencia | es |
sedici.rights.license | Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) | |
sedici.rights.uri | http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ | |
sedici.date.exposure | 2006-08 | |
sedici.relation.event | 19 th IFIP World Computer Congress - WCC 2006 | es |
sedici.description.peerReview | peer-review | es |