  Multimodal contents have become commonplace on the Internet today, manifested
as news articles, social media posts, and personal or business blog posts.
Among the various kinds of media (images, videos, graphics, icons, audio) used
in such multimodal stories, images are the most popular. The selection of
images from a collection - either author's personal photo album, or web
repositories - and their meticulous placement within a text, builds a succinct
multimodal commentary for digital consumption. In this paper we present a
system that automates the process of selecting relevant images for a story and
placing them at contextual paragraphs within the story for a multimodal
narration. We leverage automatic object recognition, user-provided tags, and
commonsense knowledge, and use an unsupervised combinatorial optimization to
solve the selection and placement problems seamlessly as a single unit.
