Storytelling with signal injection: Focusing stories with domain knowledge

Abstract

Given a beginning and ending document, automated storytelling attempts to fill in intermediary documents to form a coherent story. This is a common problem for analysts; they often have two snippets of information and want to find the other pieces that relate them. The goal of storytelling is to help the analysts limit the number of documents that must be sifted through and show connections between events, people, organizations, and places. But existing algorithms fail to allow for the insertion of analyst knowledge into the story generation process. Often times, analysts have an understanding of the situation or prior knowledge that could be used to focus the story in a better way. A storytelling algorithm is proposed as a multi-criteria optimization problem that allows for signal injection by the analyst while maintaining good story flow and content.