The Automated Summary Engine

The Automated Summary Engine presents an accessible technical perspective on automated text summarization and the computational methods used to transform lengthy textual information into concise, meaningful summaries. The subject sits at the intersection of artificial intelligence, natural language processing, computational linguistics, machine learning, information retrieval, and text analytics. The book is designed around the central problem of extracting and organizing the most important information from large volumes of written content through automated computational processes.

The concept of an automated summary engine encompasses the analysis of source documents, identification of salient information, linguistic representation, content selection, sentence and phrase processing, and generation of coherent summaries. These processes are important in modern information systems because digital environments continuously produce documents, reports, articles, technical material, web content, and other forms of textual data that can be difficult to review manually. Automated summarization provides a computational approach for reducing this information burden while preserving the essential meaning of the original material.