Computational Analysis of Storylines
Making Sense of Events
Published on 10. November 2021
978-1-108-84813-8 (ISBN)
Description
Event structures are central in Linguistics and Artificial Intelligence research: people can easily refer to changes in the world, identify their participants, distinguish relevant information, and have expectations of what can happen next. Part of this process is based on mechanisms similar to narratives, which are at the heart of information sharing. But it remains difficult to automatically detect events or automatically construct stories from such event representations. This book explores how to handle today's massive news streams and provides multidimensional, multimodal, and distributed approaches, like automated deep learning, to capture events and narrative structures involved in a 'story'. This overview of the current state-of-the-art on event extraction, temporal and casual relations, and storyline extraction aims to establish a new multidisciplinary research community with a common terminology and research agenda. Graduate students and researchers in natural language processing, computational linguistics, and media studies will benefit from this book.
Reviews / Votes
'Events are a key aspect of language meaning and the storylines underlying discourse. This book presents an accessible and comprehensive examination of events in language - from the philosophical and linguistic foundations to state of the art computational techniques for identifying, representing and reasoning about events and storylines.' James Allen, University of Rochester and Institute of Human and Machine Cognition 'There is no technology with more potential to revolutionise digital media than the computational processing of stories. This comprehensive guide covers the field of event and storyline analysis from first principles to the state of the art. Anyone doing technical work in news innovation or future media should read this.' David Caswell, Executive Product Manager, BBC News Labs 'Finally, a compendium of key, state-of-the-art ideas in narrative understanding, allowing researchers to see the big picture. Caselli, Hovy, Palmer, and Vossen have not only assembled key papers, but also created a beautiful conceptual overview of the field - a must-read for any researcher interested in narratives and storylines.' Peter Clark, Allen Institute for AIMore details
Series
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
Illustrations
Worked examples or Exercises
File size
3,39 MB
ISBN-13
978-1-108-84813-8 (9781108848138)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Tommaso Caselli | Eduard Hovy | Martha Palmer
Computational Analysis of Storylines
Making Sense of Events
Book
11/2021
Cambridge University Press
€80.20
Shipment within 15-20 days
Persons
Content
Introduction and Overview Tommaso Caselli, Martha Palmer, Ed Hovy, and Piek Vossen; Part I. Foundational Components of Storylines: 1. The Role of Event-Based Representations and Reasoning in Language James Pustejovsky; 2. The Rich Event Ontology - Ontological Hub for Event Representations Claire Bonial, Susan W. Brown, Martha Palmer, and Ghazaleh Kazeminejad; 3. Decomposing Events and Storylines William Croft, Pavlina Kalm and Michael Regan; 4. Extracting and Aligning Timelines Mark Finalyson, Andres Cremisini, and Mustafa Ocal; 5. Event Causality Paramita Mirza; 6. A Narratology-Based Framework for Storyline Extraction Piek Vossen, Tommaso Caselli, and Roxane Segers; Part II. Connecting the Dots: 7. The Richer Event Description Corpus for Event-Event Relations Tim O'Gorman, Kristin Wright-Bettner, and Martha Palmer; 8. Low-Resource Event Extraction via Share-and-Transfer and Remaining Challenges Heng Ji and Clare Voss; 9. Reading Certainty across Sources Ben Miller; 10. Narrative Homogeneity and Heterogeneity in Document Categories Dan Simonson and Tony Davis; 11. Exploring Machine-Learning Techniques for Linking Event Templates Jakub Piskorski, Fredi Saric, Vanni Zavarella, and Martin Atkinson; 12. Semantic Storytelling - from Experiments and Prototypes to a Technical Solution Georg Rehm, Karolina Zaczynska, Peter Bourgonje, Malte Ostendorff, Julian Moreno-Schneider, Maria Berger, Jens Rauenbusch, Andre Schmidt, Mikka Wild, Joachim Boettger, Joachim Quantz, Jan Thomsen, and Rolf Fricke.
