2016 COLING COLING 2016

A Tool for Efficient Content Compilation

Abstract

AbstractWe build a tool to assist in content creation by mining the web for information relevant to a given topic. This tool imitates the process of essay writing by humans: searching for topics on the web, selecting content frag-ments from the found document, and then compiling these fragments to obtain a coherent text. The process of writing starts with automated building of a table of content by obtaining the list of key entities for the given topic extracted from web resources such as Wikipedia. Once a table of content is formed, each item forms a seed for web mining. The tool builds a full-featured structured Word document with table of content, section structure, images and captions and web references for all mined text fragments. Two linguistic technologies are employed: for relevance verification, we use similarity computed as a tree similarity between parse trees for a seed and candidate text fragment. For text coherence, we use a measure of agreement between a given and consecutive paragraph by tree kernel learning of their discourse trees. The tool is available at http://animatronica.io/submit.html.

🧭 Keyword Pioneer — content compilation
🐣 Hot Topic Early Bird — text generation
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio

Authors