  [Abridged] We exploit the clustering of massive galaxies to perform a high
efficiency imaging search for gravitational lenses. Our dataset comprises 44
fields imaged by the Hubble Space Telescope (HST) Advanced Camera for Surveys
(ACS), each of which is centered on a lens discovered by the Strong Lens ACS
Survey (SLACS). We compare four different search methods: 1) automated
detection with the HST Archive Galaxy-scale Gravitational Lens Survey (HAGGLeS)
robot, 2) examining cutout images of bright galaxies (BGs) after subtraction of
a smooth galaxy light distribution, 3) examining the unsubtracted BG cutouts,
and 4) performing a full-frame visual inspection of the ACS images. We compute
purity and completeness and consider investigator time for the four algorithms,
using the main SLACS lenses as a testbed. The first and second algorithms
perform the best. We present the four new lens systems discovered during this
comprehensive search, as well as one other likely candidate. For each new lens
we use the fundamental plane to estimate the lens velocity dispersion and
predict, from the resulting lens geometry, the redshifts of the lensed sources.
Two of these new systems are found in galaxy clusters, which include the SLACS
lenses in the two respective fields. Overall we find that the enhanced lens
abundance (30^{+24}_{-8} lenses/degree^2) is higher than expected for random
fields (12^{+4}_{-2} lenses/degree^2 for the COSMOS survey). Additionally, we
find that the gravitational lenses we detect are qualitatively different from
those in the parent SLACS sample: this imaging survey is largely probing
higher-redshift, and lower-mass, early-type galaxies.
