It takes the average reader 2 hours and 5 minutes to read Computational Modeling of Narrative by Inderjeet Mani
Assuming a reading speed of 250 words per minute. Learn more
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 by Inderjeet Mani is 124 pages long, and a total of 31,496 words.
This makes it 42% the length of the average book. It also has 38% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 2 hours and 52 minutes to read Computational Modeling of Narrative aloud.
Computational Modeling of Narrative is suitable for students ages 10 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
Computational Modeling of Narrative by Inderjeet Mani is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.
To buy Computational Modeling of Narrative by Inderjeet Mani on Amazon click the button below.
Buy Computational Modeling of Narrative on Amazon