Titlebook: Discovery Science; 13th International C Bernhard Pfahringer,Geoff Holmes,Achim Hoffmann Conference proceedings 2010 Springer Berlin Heidelb

時代

Zoe J. Radnor,Hannah Noke,Tudor Rickardst to most approaches to constrained clustering, we do not constrain the way observations can be grouped into clusters, but the way candidate clusters can be combined into suitable clusterings. The constraints may concern the type of clustering (e.g., complete clusterings, overlapping or encompassing

貿(mào)易

職業(yè)

Relative Morse Theory of Nonproper Functionscorrelation rate amongst the items that constitute a given pattern since they are mainly interested in appearance frequency. In this situation, many correlation measures have been proposed in order to convey information on the dependencies within sets of items. In this work, we adopt the correlation

倫理學(xué)

observatory

Dramatis Personae and the Main Theoremnt locations from raw GPS data is the first essential step of algorithms designed for location-aware applications. Assuming that a location is significant if users spend a certain time around that area, most current algorithms compare spatial/temporal variables, such as stay duration and a roaming d

Minikin

Eigene Ergebnisse und Erfahrungen,tral area of natural science research concerns reactions: how entities in a scientific domain interact to generate new entities. Classic AI research due to Valdés-Pérez, ?ytkow, Langley and Simon has shown that many scientific discovery tasks that concern reaction models can be formalized as a matri

forebear

Rotationally Invariant Bark Recognitionrmally distributed clusters and a cluster with a uniform distribution in an axis-aligned rectangular box. The uniform component extends the practical usability of the model e.g. in the presence of noise, and using the MDL principle for the model selection makes comparing the quality of clusterings w

Expand

口訣

https://doi.org/10.1007/978-3-642-16184-1cloud computing; clustering; cognition; collaborative science; data mining; human-machine interaction; kno

翻動

978-3-642-16183-4Springer Berlin Heidelberg 2010