  We present a generalization of the Giant Molecular Cloud (GMC) identification
problem based on cluster analysis. The method we designed, SCIMES (Spectral
Clustering for Interstellar Molecular Emission Segmentation) considers the
dendrogram of emission in the broader framework of graph theory and utilizes
spectral clustering to find discrete regions with similar emission properties.
For Galactic molecular cloud structures, we show that the characteristic volume
and/or integrated CO luminosity are useful criteria to define the clustering,
yielding emission structures that closely reproduce "by-eye" identification
results. SCIMES performs best on well-resolved, high-resolution data, making it
complementary to other available algorithms. Using 12CO(1-0) data for the
Orion-Monoceros complex, we demonstrate that SCIMES provides robust results
against changes of the dendrogram-construction parameters, noise realizations
and degraded resolution. By comparing SCIMES with other cloud decomposition
approaches, we show that our method is able to identify all canonical clouds of
the Orion-Monoceros region, avoiding the over-division within high resolution
survey data that represents a common limitation of several decomposition
algorithms. The Orion-Monoceros objects exhibit hierarchies and size-line width
relationships typical to the turbulent gas in molecular clouds, although "the
Scissors" region deviates from this common description. SCIMES represents a
significant step forward in moving away from pixel-based cloud segmentation
towards a more physical-oriented approach, where virtually all properties of
the ISM can be used for the segmentation of discrete objects.
