| 期刊全稱(chēng) | Automatically Ordering Events and Times in Text | | 影響因子2023 | Leon R.A. Derczynski | | 視頻video | http://file.papertrans.cn/167/166463/166463.mp4 | | 發(fā)行地址 | Includes recent research on temporal information extraction.Is devoted to information extraction, spatiotemporal semantics, and handling noisy linguistic data.Presents methods to automatically order e | | 學(xué)科分類(lèi) | Studies in Computational Intelligence | | 圖書(shū)封面 |  | | 影響因子 | .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 | | Pindex | Book 2017 |
The information of publication is updating
|
|
|Archiver|手機(jī)版|小黑屋|
派博傳思國(guó)際
( 京公網(wǎng)安備110108008328)
GMT+8, 2025-10-9 18:57
發(fā)表于 2025-3-21 18:01:27
