Title
A time series retrieval tool for sub-series matching
Abstract
The problem of retrieving time series similar to a specified query pattern has been recently addressed within the case based reasoning (CBR) literature. Providing a flexible and efficient way of dealing with such an issue is of paramount importance in many domains (e.g., medical), where the evolution of specific parameters is collected in the form of time series. In the past, we have developed a framework for retrieving time series, applying temporal abstractions. With respect to more classical (mathematical) approaches, our framework provides significant advantages. In particular, multi-level abstraction mechanisms and proper indexing techniques allow for flexible query issuing, and for efficient and interactive query answering. In this paper, we present an extension to such a framework, which aims to support sub-series matching as well. Indeed, sub-series retrieval may be crucial when the whole time series evolution is not of interest, while critical patterns to be searched for are only “local”. Moreover, sometimes the relative order of patterns, but not their precise location in time, may be known. Finally, an interactive search, at different abstraction levels, may be required by the decision maker. Our extended framework (which is currently being applied in haemodialysis, but is domain independent) deals with all these issues.
Year
DOI
Venue
2015
10.1007/s10489-014-0628-8
Applied Intelligence
Keywords
Field
DocType
Time series retrieval,Sub-series matching,Temporal abstractions,Case based reasoning,Hemodialysis
Abstraction,Computer science,Search engine indexing,Artificial intelligence,Case-based reasoning,Machine learning,Interactive search,Decision maker
Journal
Volume
Issue
ISSN
43
1
0924-669X
Citations 
PageRank 
References 
1
0.36
26
Authors
5
Name
Order
Citations
PageRank
A. Bottrighi124724.69
Giorgio Leonardi217920.36
Stefania Montani390181.42
Luigi Portinale4806155.06
Paolo Terenziani5924112.83