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Automatically ordering events and times in text

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...

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Detalles Bibliográficos
Autor principal: Derczynski, Leon R A
Lenguaje:eng
Publicado: Springer 2017
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-47241-6
http://cds.cern.ch/record/2240470
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author Derczynski, Leon R A
author_facet Derczynski, Leon R A
author_sort Derczynski, Leon R A
collection CERN
description 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 theory and 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.
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spelling cern-22404702021-04-21T19:24:03Zdoi:10.1007/978-3-319-47241-6http://cds.cern.ch/record/2240470engDerczynski, Leon R AAutomatically ordering events and times in textEngineeringThe 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 theory and 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.Springeroai:cds.cern.ch:22404702017
spellingShingle Engineering
Derczynski, Leon R A
Automatically ordering events and times in text
title Automatically ordering events and times in text
title_full Automatically ordering events and times in text
title_fullStr Automatically ordering events and times in text
title_full_unstemmed Automatically ordering events and times in text
title_short Automatically ordering events and times in text
title_sort automatically ordering events and times in text
topic Engineering
url https://dx.doi.org/10.1007/978-3-319-47241-6
http://cds.cern.ch/record/2240470
work_keys_str_mv AT derczynskileonra automaticallyorderingeventsandtimesintext