Interpreting Motion presents an integrated perspective on how language structures constrain concepts of motion and how the world shapes the way motion is linguistically expressed. Natural language allows for efficient communication of elaborate descriptions of movement without requiring a precise specification of the motion. Interpreting Motion is the first book to analyze the semantics of motion expressions in terms of the formalisms of qualitative spatial reasoning. It shows how motion descriptions in language are mapped to trajectories of moving entities based on qualitative spatio-temporal relationships. The authors provide an extensive discussion of prior research on spatial prepositions and motion verbs, devoting chapters to the compositional semantics of motion sentences, the formal representations needed for computers to reason qualitatively about time, space, and motion, and the methodology for annotating corpora with linguistic information in order to train computer programs to reproduce the annotation. The applications they illustrate include route navigation, the mapping of travel narratives, question-answering, image and video tagging, and graphical rendering of scenes from textual descriptions. The book is written accessibly for a broad scientific audience of linguists, cognitive scientists, computer scientists, and those working in fields such as artificial intelligence and geographic information systems.

Interpreting Motion: Grounded Representations for Spatial Language (Explorations in Language and Space)

Reference

Pustejovsky, James

Mani, Inderjeet

Words, Language & Grammar

Oxford University Press

Time is a key aspect of narrative. It can advance a story, illuminate its role in our daily lives, and help us understand how events unfold. In this groundbreaking interdisciplinary work, Inderjeet Mani uses recent developments in linguistics and computer science to analyze the use of time in narrative form. The Imagined Moment outlines directions for an emerging discipline of “corpus narratology,” an approach involving the computer analysis and interpretation of multimillion-word collections of narrative text. This approach, Mani explains, could alter the very foundations of narrative theory. Accordingly, he develops a computer representation for timelines and applies it to a variety of literary works. Among these are such classics as One Hundred Years of Solitude, “A Hunger Artist,” Swann’s Way, Jealousy, Candide, and “The Short Happy Life of Francis Macomber.” Along the way, Mani considers stories embedded in temporal cycles; the cognitive processes involved in the construal of events in time; the modeling of narrative progression in terms of changes in readers’ evaluation of characters; the study of variations of tempo in fiction; and time in computer-mediated forms of storytelling.

The Imagined Moment: Time, Narrative, and Computation (Frontiers of Narrative)

Literature & Fiction

History & Criticism

University Of Nebraska Press

Automatic Summarization (Natural Language Processing)

With the explosion in the quantity of on-line text and multimedia information in recent years, there has been a renewed interest in automatic summarization. This book provides a systematic introduction to the field, explaining basic definitions, the strategies used by human summarizers, and automatic methods that leverage linguistic and statistical knowledge to produce extracts and abstracts. Drawing from a wealth of research in artificial intelligence, natural language processing, and information retrieval, the book also includes detailed assessments of evaluation methods and new topics such as multi-document and multimedia summarization. Previous automatic summarization books have been either collections of specialized papers, or else authored books with only a chapter or two devoted to the field as a whole. This is the first textbook on the subject, developed based on teaching materials used in two one-semester courses. To further help the student reader, the book includes detailed case studies, accompanied by end-of-chapter reviews and an extensive glossary.Audience: students and researchers, as well as information technology managers, librarians, and anyone else interested in the subject.

Computers & Technology

Programming Languages

John Benjamins Publishing Company

The field of narrative (or story) understanding and generation is one of the oldest in natural language processing (NLP) and artificial intelligence (AI), which is hardly surprising, since storytelling is such a fundamental and familiar intellectual and social activity. In recent years, the demands of interactive entertainment and interest in the creation of engaging narratives with life-like characters have provided a fresh impetus to this field. This book provides an overview of the principal problems, approaches, and challenges faced today in modeling the narrative structure of stories. The book introduces classical narratological concepts from literary theory and their mapping to computational approaches. It demonstrates how research in AI and NLP has modeled character goals, causality, and time using formalisms from planning, case-based reasoning, and temporal reasoning, and discusses fundamental limitations in such approaches. It proposes new representations for embedded narratives and fictional entities, for assessing the pace of a narrative, and offers an empirical theory of audience response. These notions are incorporated into an annotation scheme called NarrativeML. The book identifies key issues that need to be addressed, including annotation methods for long literary narratives, the representation of modality and habituality, and characterizing the goals of narrators. It also suggests a future characterized by advanced text mining of narrative structure from large-scale corpora and the development of a variety of useful authoring aids. This is the first book to provide a systematic foundation that integrates together narratology, AI, and computational linguistics. It can serve as a narratology primer for computer scientists and an elucidation of computational narratology for literary theorists. It is written in a highly accessible manner and is intended for use by a broad scientific audience that includes linguists (computational and formal semanticists), AI researchers, cognitive scientists, computer scientists, game developers, and narrative theorists. Table of Contents: List of Figures / List of Tables / Narratological Background / Characters as Intentional Agents / Time / Plot / Summary and Future Directions

Computational Modeling of Narrative (Synthesis Lectures on Human Language Technologies)

Computer Science

Morgan & Claypool Publishers

Springer

Foreign Language Study & Reference

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