  We present a web-based system called ViS-\'A-ViS aiming to assist literary
scholars in detecting repetitive patterns in an annotated textual corpus.
Pattern detection is made possible using distant reading visualizations that
highlight potentially interesting patterns. In addition, the system uses
time-series alignment algorithms, and in particular, dynamic time warping
(DTW), to detect patterns automatically. We present a case-study where an
ancient Hebrew poetry corpus was manually annotated with figurative language
devices as metaphors and similes and then loaded into the system. Preliminary
results confirm the effectiveness of the system in analyzing the annotated data
and in detecting literary patterns and similarities.
