Multi-level abstractions and multi-dimensional retrieval of cases with time series features

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Abstract

Time series retrieval is a critical issue in all domains in which the observed phenomenon dynamics have to be dealt with. In this paper, we propose a novel, domain independent time series retrieval framework, based on Temporal Abstractions (TA). Our framework allows for multi-level abstractions, according to two dimensions, namely a taxonomy of (trend or state) symbols, and a variety of time granularities. Moreover, we allow for flexible querying, where queries can be expressed at any level of detail in both dimensions, also in an interactive fashion, and ground cases as well as generalized ones can be retrieved. We also take advantage of multi-dimensional orthogonal index structures, which can be refined progressively and on demand. The framework in practice is illustrated by means of a case study in hemodialysis.

Lingua originaleInglese
Titolo della pubblicazione ospiteCase-Based Reasoning Research and Development - 8th International Conference on Case-Based Reasoning, ICCBR 2009, Proceedings
Pagine225-239
Numero di pagine15
DOI
Stato di pubblicazionePubblicato - 2009
Evento8th International Conference on Case-Based Reasoning, ICCBR 2009 - Seattle, WA, United States
Durata: 20 lug 200923 lug 2009

Serie di pubblicazioni

NomeLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5650 LNAI
ISSN (stampa)0302-9743
ISSN (elettronico)1611-3349

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???event.eventtypes.event.conference???8th International Conference on Case-Based Reasoning, ICCBR 2009
Paese/TerritorioUnited States
CittàSeattle, WA
Periodo20/07/0923/07/09

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