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tokens: to apply to large amounts of spectroscopic data even in the presence of large redshift errors in the standard pipeline. This algorithm selects a relatively small number of candidates from the large data set for visual inspection to confirm the correctness of the identification. While the false negative rate is very small based on a small test sample of known post-starburst galaxies, the false positive rate to be removed by visual inspection is between 100% and 300%. At this point, the amount of visual inspection required is still manageable, but a more optimized algorithm with a lower false positive rate will be critical when the next generation of surveys generate significantly larger samples. Examples of such surveys are the fourth phase of the SDSS-IV (Dawson et al. 2015 ), the Dark Energy Spectroscopic Instrument (Levi et al. 2013 ), and the Prime Focus Spectrograph (Takada et al. 2014 ). For SDSS and BOSS data in particular, it was found in retrospect that the redshift determination by the spectroscopic pipeline is very robust, with less than 5% incorrect redshifts even for this rare class of objects. Therefore, selecting the post-starburst galaxies from SDSS and BOSS assuming the pipeline redshifts to be reliable would have simplified the process and reduced the number of false positives significantly. In light of this, there are some improvements to incorporate the future work selecting post-starburst galaxies from large spectroscopic surveys. One such data set in the near future would be the entire BOSS (SDSS DR12). This phase of SDSS contains twice as many spectra than what we used in this paper, and it is now public (Alam et al. 2015 ). The first improvement might be to do the selection based on the stellar population properties, rather than empirical cuts on parameters such as A/Total or equivalent widths. Ideally, this approach is more preferable since it would lead to selection based on physically meaningful properties of the galaxy population such as stellar population age and metallicity. For example, one might define post-starburst galaxies to be populations that are older than 300 Myr but younger than 1 Gyr. Yesuf et al. ( 2014 ) fit stellar population models using multiwavelength data while taking AGNs and dust obscuration into account. Selection of these objects from the next generation of multiband photometric surveys is another possibility. Doing so requires distinguishing between the 3600 Å Balmer break and the 4000 Å break at slightly different redshifts. One can potentially resolve this ambiguity using multiwavelength information, for example, in near-UV (NUV) and near-IR (NIR), since the old population would have almost no flux in NUV but large flux in NIR, and conversely for the young population. Wild et al. ( 2014 ) studied galaxy SEDs in optical and NIR and found that post-starburst galaxies have unique, identifiable colors. However, the presence of dust and AGNs would make this task challenging. 7. CONCLUSION The