In this study,we investigate the potential of mark-weighted angular correlation functions,which integrate β-cosmic-web classification with angular correlation function analysis to improve cosmological constraints. Using SDSS DR12 CMASS-NGC galaxies and mock catalogs with Ωm varying from 0.25 to 0.40,we assess the discriminative power of different statistics via the average improvement in chi-squared, , across six redshift bins. This metric quantifies how effectively each statistic distinguishes between different cosmological models. Incorporating cosmic-web weights leads to substantial improvements. Using statistics weighted by the mean neighbor distance () increases  by approximately 40%–130%, while applying inverse mean neighbor distance weighting () yields even larger gains, boosting  by a factor of 2–3 compared to traditional unweighted angular statistics. These enhancements are consistent with previous 3D clustering results, demonstrating the superior sensitivity of the β-weighted approaches. Our method, based on thin redshift slices, is particularly suitable for slitless surveys (e.g., Euclid, CSST) where redshift uncertainties limit 3D analyses. This study also offers a framework for applying marked statistics to 2D angular clustering.

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