  The task of identifying high-quality content becomes increasingly important,
and it can improve overall reading time and CTR(click-through rate estimates).
Generalizes quality analysis only focused on single Modal,such as image or
text,but in today's mainstream media sites a lot of information is presented in
graphic form.In this paper we propose a MultiModal quality recognition approach
for the quality score. First we use two feature extractors,one for image and
another for the text. After that we use an Siamese Network with the rank loss
as the optimization objective.Compare with other approach,our approach get a
more accuracy result.
