DocumentCode
1954381
Title
Notice of Retraction
Order, duration and gap — Take them all
Author
Aihua Zheng ; Jixin Ma ; Petridis, M. ; Bai Xiao
Author_Institution
Sch. of Comput. & Math. Sci., Univ. of Greenwich, London, UK
Volume
2
fYear
2010
fDate
9-11 July 2010
Firstpage
647
Lastpage
651
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Based on a formal characterization of time-series and state-sequences, a new distance measurement dealing with both non-temporal and temporal distances for state-sequence matching is proposed in this paper. In addition to formulating the temporal order over state-sequences, it also takes into account of temporal distances in terms of both the temporal duration of each state and the temporal gaps between adjacent pairs of states, which are neglected in most existing approaches to time-series and state-sequence matching. In particular, when specialized as a real-penalty-style measurement by means of reifying the cost functions, it is more flexible with regards to real-life applications than binary-value-style distance measurements. In addition, it is more robust than those existing real-penalty-style distance measurements since it can filter out noise during the matching procedure. Experimental results on reconstructed time-series data from UCI KDD Archive demonstrate that it can tackle the most general problems in matching time-series data with rich temporal information.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Based on a formal characterization of time-series and state-sequences, a new distance measurement dealing with both non-temporal and temporal distances for state-sequence matching is proposed in this paper. In addition to formulating the temporal order over state-sequences, it also takes into account of temporal distances in terms of both the temporal duration of each state and the temporal gaps between adjacent pairs of states, which are neglected in most existing approaches to time-series and state-sequence matching. In particular, when specialized as a real-penalty-style measurement by means of reifying the cost functions, it is more flexible with regards to real-life applications than binary-value-style distance measurements. In addition, it is more robust than those existing real-penalty-style distance measurements since it can filter out noise during the matching procedure. Experimental results on reconstructed time-series data from UCI KDD Archive demonstrate that it can tackle the most general problems in matching time-series data with rich temporal information.
Keywords
pattern recognition; time series; distance measurement; real-penalty-style measurement; state-sequence matching; temporal distances; time-series; Atmospheric measurements; Iron; Noise; Noise measurement; Particle measurements; Pattern matching; Q measurement; Pattern Recongition; State-sequence; Time-series;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-5537-9
Type
conf
DOI
10.1109/ICCSIT.2010.5564860
Filename
5564860
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