Although temporal regulation of gene expression during the course of infection is known to be critical for determining the outcome of host-virus interactions, systematic temporal analysis of the miRNA targetomes during productive viral infection has been technically challenging due to the large range of miRNA-mRNA cross-talks at the host-virus interface. High-confidence quantifying models of the suppression efficacy in targeting sites by integrating bioinformatics with Argonaute-crosslinking and immunoprecipitation followed by high-throughput sequencing (AGO-CLIP-seq) (Chi et al., 2009) data have been poorly developed. To accurately identify miRNA target sites and calculate the targeting efficacy of miRNA-target interactions, we developed a new bioinformatic quantitation method, AGO-CLIP-seq enrichment (ACE)-scoring algorithm (Kim et al., 2015). Inclusion of the uninfected control in our AGO-CLIP-seq analysis can significantly improve the accuracy of authentic target site identification for viral or human miRNAs and extract physiologically significant changes during productive human cytomegalovirus (HCMV) infection using our ACE-scoring method. Thus, we suggest that our new ACE-scoring-based methodology can be applied to various miRNA targetome studies, which will be performed in other kinds of temporal contexts, such as developmental stages, immune stimulation by cytokines or pathogens, and lytic infection by other viruses.