Optimised search strategies to improve structural pattern recognition techniques
by Augusto Pereira, Jesus Vega, Ana Portas, Rodrigo Castro, Andrea Murari, JET-EFDA contributors
International Journal of Nuclear Knowledge Management (IJNKM), Vol. 4, No. 1, 2010

Abstract: Data retrieval methods are based on three essential aspects: feature extraction (to reduce signal dimensionality), the classification system (to index objects according to some criteria) and similarity measures (to compare how similar two objects are); but there is not a single solution to handle these key elements. This paper provides a new solution to the localisation and extraction of similar patterns in time-series data. Alternative searches are proposed to objectively increase the recognition of similar patterns so as to achieve better results on the data retrieval. These search strategies have been studied with excellent results in the detection of long subpatterns. Long subpatterns are not very easy to identify since even a single mismatch in one character can compromise similarity between two patterns. Identifying long patterns in a fast, fault-tolerant and intelligent way is the aim of the analysed strategies, which are formally based on statistical criteria and some aspects of probability theory.

Online publication date: Fri, 22-Jan-2010

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Nuclear Knowledge Management (IJNKM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com