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DATAMINE
2008

Two heads better than one: pattern discovery in time-evolving multi-aspect data

10 years 1 months ago
Two heads better than one: pattern discovery in time-evolving multi-aspect data
Abstract. Data stream values are often associated with multiple aspects. For example, each value observed at a given time-stamp from environmental sensors may have an associated type (e.g., temperature, humidity, etc) as well as location. Time-stamp, type and location are the three aspects, which can be modeled using a tensor (high-order array). However, the time aspect is special, with a natural ordering, and with successive time-ticks having usually correlated values. Standard multiway analysis ignores this structure. To capture it, we propose 2 Heads Tensor Analysis (2-heads), which provides a qualitatively different treatment on time. Unlike most existing approaches that use a PCA-like summarization scheme for all aspects, 2-heads treats the time aspect carefully. 2-heads combines the power of classic multilinear analysis (PARAFAC [6], Tucker [13], DTA/STA [11], WTA [10]) with wavelets, leading to a powerful mining tool. Furthermore, 2-heads has several other advantages as well: (a...
Jimeng Sun, Charalampos E. Tsourakakis, Evan Hoke,
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2008
Where DATAMINE
Authors Jimeng Sun, Charalampos E. Tsourakakis, Evan Hoke, Christos Faloutsos, Tina Eliassi-Rad
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