Extending the JColibri open source architecture for managing high-dimensional data and large case bases

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Abstract

CBR systems designers and developers' research can benefit from the availability of existing platforms, able to provide software design and implementation assistance. The JColibri platform [26], realized and maintained by the University of Madrid, is one of the most well known among such tools. In this work, we describe a couple of extensions we have provided to the core JColibri open source software. In particular, our extensions are meant to optimize case retrieval performances, in data-rich applications. Specifically, we focused our attention on treating (i) large case bases, in which retrieval time may become unacceptable, and (ii) cases with high-dimensional features - namely time series features - on which proper case representation and retrieval solutions need to be studied. The implemented code has been preliminarly tested, and it is now ready to be integrated with the JColibri code, and made available to the CBR research community. Additional extensions, always dealing with retrieval optimization, are foreseen as our future work.

Lingua originaleInglese
Titolo della pubblicazione ospiteICTAI 2009 - 21st IEEE International Conference on Tools with Artificial Intelligence
Pagine269-275
Numero di pagine7
DOI
Stato di pubblicazionePubblicato - 2009
Evento21st IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2009 - Newark, NJ, United States
Durata: 2 nov 20095 nov 2009

Serie di pubblicazioni

NomeProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
ISSN (stampa)1082-3409

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???event.eventtypes.event.conference???21st IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2009
Paese/TerritorioUnited States
CittàNewark, NJ
Periodo2/11/095/11/09

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