  Searches for gravitational waves (GWs) traditionally focus on persistent
sources (e.g., pulsars or the stochastic background) or on transients sources
(e.g., compact binary inspirals or core-collapse supernovae), which last for
timescales of milliseconds to seconds. We explore the possibility of long GW
transients with unknown waveforms lasting from many seconds to weeks. We
propose a novel analysis technique to bridge the gap between short O(s) burst
analyses and persistent stochastic analyses. Our technique utilizes
frequency-time maps of GW strain cross-power between two spatially separated
terrestrial GW detectors. The application of our cross-power statistic to
searches for GW transients is framed as a pattern recognition problem, and we
discuss several pattern-recognition techniques. We demonstrate these techniques
by recovering simulated GW signals in simulated detector noise. We also recover
environmental noise artifacts, thereby demonstrating a novel technique for the
identification of such artifacts in GW interferometers. We compare the
efficiency of this framework to other techniques such as matched filtering.
