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https://infolab.usc.edu/csci599/Fall2003/Time%20Series/Indexing%20MultiDimensional%20TimeSeries.pdf
Indexing Multi›Dimensional Time›Series with Support for Multiple Distance Measures Michail Vlachos Marios Hadjieleftheriou Dimitrios Gunopulos y Eamonn Keogh UC Riverside, fmvlachos, marioh, dg, [email protected]
https://dl.acm.org/citation.cfm?id=956777
Although most time-series data mining research has concentrated on providing solutions for a single distance function, in this work we motivate the need for a single index structure that can support multiple distance measures.Cited by: 490
https://dl.acm.org/doi/10.1007/s00778-004-0144-2
While most time series data mining research has concentrated on providing solutions for a single distance function, in this work we motivate the need for an index structure that …
https://www.researchgate.net/publication/2472922_Indexing_Multi-Dimensional_Time-Series_with_Support_for_Multiple_Distance_Measures
Indexing Multi-Dimensional Time-Series with Support for Multiple Distance Measures. ... b een used so far for one-dimensional time series. ... for indexing Time W arping, by using suffix trees.
https://www.researchgate.net/publication/220473543_Indexing_Multidimensional_Time-Series
Indexing Multidimensional Time-Series. ... a major contribution of our work is the ability to support all these measures without the need to restructure the index. ... Indexing Multi-Dimensional ...
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.8.7551
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Although most time-series data mining research has concentrated on providing solutions for a single distance function, in this work we motivate the need for a single index structure that can support multiple distance measures. Our specific area of interest is the e#cient retrieval and analysis of trajectory similarities.
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.1275
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Although most time-series data mining research has concentrated on providing solutions for a single distance function, in this work we motivate the need for a single index structure that can support multiple distance measures. Our specific area of interest is the efficient retrieval and analysis of trajectory ...
https://link.springer.com/article/10.1007/s00778-004-0144-2
Jul 22, 2005 · Abstract. While most time series data mining research has concentrated on providing solutions for a single distance function, in this work we motivate the need for an index structure that can support multiple distance measures.Cited by: 170
https://github.com/pandas-dev/pandas/issues/30867
Deprecate it in Series.__getitem__ as well, ... Support for multi-dimensional indexing (e.g. `index[:, None]`) on an Index is deprecated and will be removed in a future version. Convert to a numpy array before indexing instead. ... You can’t perform that action at this time.
http://core.ac.uk/display/24595817
Although most time-series data mining research has concentrated on providing solutions for a single distance function, in this work we motivate the need for a single index structure that can support multiple distance measures. Our specific area of interest is the e#cient …
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