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Automatically Ordering Events and Times in Text

Leon R.A. Derczynski

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Hardback

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English
Springer International Publishing AG
26 October 2016
The book offers a detailed guide to temporal ordering, exploring open problems in the field and providing solutions and extensive analysis. It addresses the challenge of automatically ordering events and times in text. Aided by TimeML, it also describes and presents concepts relating to time in easy-to-compute terms. Working out the order that events and times happen has proven difficult for computers, since the language used to discuss time can be vague and complex. Mapping out these concepts for a computational system, which does not have its own inherent idea of time, is, unsurprisingly, tough. Solving this problem enables powerful systems that can plan, reason about events, and construct stories of their own accord, as well as understand the complex narratives that humans express and comprehend so naturally. 

This book presents a theoryand data-driven analysis of temporal ordering, leading to the identification of exactly what is difficult about the task. It then proposes and evaluates machine-learning solutions for the major difficulties.

It is a valuable resource for those working in machine learning for natural language processing as well as anyone studying time in language, or involved in annotating the structure of time in documents.
By:  
Imprint:   Springer International Publishing AG
Country of Publication:   Switzerland
Edition:   1st ed. 2017
Volume:   677
Dimensions:   Height: 235mm,  Width: 155mm,  Spine: 14mm
Weight:   4.675kg
ISBN:   9783319472409
ISBN 10:   3319472402
Series:   Studies in Computational Intelligence
Pages:   205
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Hardback
Publisher's Status:   Active
Introduction.- Events and Times.- Temporal Relations.- Relation Labelling Analysis.- Using Temporal Signals.- Using a Framework of Tense and Aspect.- Conclusion.

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