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Adaptive dissimilarity index for measuring time series proximity | SpringerLink
Source: link.springer.com
Article summary:
1. The article proposes a new dissimilarity index for measuring time series proximity, which takes into account both the closeness of values and the similarity in terms of growth behavior.
2. A comparative numerical analysis is performed between the proposed index and classical distance measures on two datasets: a synthetic dataset and a dataset from a public health study.
3. The article references 884 Accesses, 78 Citations, and 3 Altmetric metrics to support its findings.
Article analysis:
The article appears to be reliable and trustworthy as it provides evidence to support its claims through numerical analysis on two datasets, referencing 884 Accesses, 78 Citations, and 3 Altmetric metrics. Furthermore, the article references several other sources to back up its findings such as Alt H & Godau M (1992), Caiado J et al (2006), Chouakria Douzal A (2003), Eiter T & Mannila H (1994), Garcia-Escudero LA & Gordaliza A (2005), Godau M (1991), Heckman NE & Zamar RH (2000), Hennig C & Hausdorf B (2006), Kakizawa Y et al (1998), Kaslow RA & Ostrow DG (1987) and Keller K & Wittfeld K (2004).
The only potential bias that could be identified in this article is that it does not present both sides equally; however, this is not necessarily an issue since the purpose of the article is to propose a new dissimilarity index for measuring time series proximity rather than presenting both sides of an argument.