CA2917153A1 - Procede et systeme permettant de simplifier une prediction de relations rhetoriques implicites dans un corpus annote a grande echelle - Google Patents

Procede et systeme permettant de simplifier une prediction de relations rhetoriques implicites dans un corpus annote a grande echelle Download PDF

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CA2917153A1
CA2917153A1 CA2917153A CA2917153A CA2917153A1 CA 2917153 A1 CA2917153 A1 CA 2917153A1 CA 2917153 A CA2917153 A CA 2917153A CA 2917153 A CA2917153 A CA 2917153A CA 2917153 A1 CA2917153 A1 CA 2917153A1
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computer
text
corpus
relation
discourse
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CA2917153C (fr
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Blake HOWALD
Andrew NYSTROM
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Thomson Reuters Enterprise Centre GmbH
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Thomson Reuters Global Resources ULC
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/35—Clustering; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/31—Indexing; Data structures therefor; Storage structures

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • Machine Translation (AREA)
  • Document Processing Apparatus (AREA)

Abstract

La présente invention se rapporte à un procédé et à un système permettant de prédire des relations rhétoriques implicites entre deux fragments d'un texte, par exemple dans un important corpus annoté, tel que le Penn Discourse Treebank (« PDTB »), le Rhetorical Structure Theory corpus et le Discourse Graph Bank, et permettent, en particulier, de déterminer une relation rhétorique en l'absence d'un marqueur de discours explicite. Des caractéristiques de niveau de surface peuvent être utilisées pour capturer des informations pragmatiques codées dans le marqueur absent. Selon une manière, une caractéristique simplifiée déterminée sur la base seulement d'un texte brut et de fonctions sémantiques est utilisée pour améliorer la performance de toutes les relations. En utilisant des caractéristiques de niveau de surface pour prédire des relations rhétoriques implicites pour l'important corpus annoté, l'invention se rapproche d'une performance maximale théorique, suggérant que davantage de données n'amélioreront pas nécessairement la performance sur la base de ces caractéristiques et de caractéristiques similaires.
CA2917153A 2013-07-03 2014-07-03 Procede et systeme permettant de simplifier une prediction de relations rhetoriques implicites dans un corpus annote a grande echelle Active CA2917153C (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201361842635P 2013-07-03 2013-07-03
US61/842,635 2013-07-03
PCT/US2014/045432 WO2015003143A2 (fr) 2013-07-03 2014-07-03 Procédé et système permettant de simplifier une prédiction de relations rhétoriques implicites dans un corpus annoté à grande échelle

Publications (2)

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CA2917153A1 true CA2917153A1 (fr) 2015-01-08
CA2917153C CA2917153C (fr) 2022-05-17

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CA2917153A Active CA2917153C (fr) 2013-07-03 2014-07-03 Procede et systeme permettant de simplifier une prediction de relations rhetoriques implicites dans un corpus annote a grande echelle

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AU (1) AU2014285073B9 (fr)
CA (1) CA2917153C (fr)
WO (1) WO2015003143A2 (fr)

Cited By (2)

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CN111209366A (zh) * 2019-10-10 2020-05-29 天津大学 基于TransS驱动的互激励神经网络的隐式篇章关系识别方法
CN112257460A (zh) * 2020-09-25 2021-01-22 昆明理工大学 基于枢轴的汉越联合训练神经机器翻译方法

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JP7187545B2 (ja) * 2017-09-28 2022-12-12 オラクル・インターナショナル・コーポレイション 名前付きエンティティの構文解析および識別に基づくクロスドキュメントの修辞的つながりの判断
US11809825B2 (en) 2017-09-28 2023-11-07 Oracle International Corporation Management of a focused information sharing dialogue based on discourse trees
EP3791292A1 (fr) 2018-05-09 2021-03-17 Oracle International Corporation Constructions d'arbres de discours imaginaires pour améliorer la réponse à des questions convergentes
US11580298B2 (en) 2019-11-14 2023-02-14 Oracle International Corporation Detecting hypocrisy in text
CN113407713B (zh) * 2020-10-22 2024-04-05 腾讯科技（深圳）有限公司 基于主动学习的语料挖掘方法、装置及电子设备
CN113535973B (zh) * 2021-06-07 2023-06-23 中国科学院软件研究所 基于知识映射的事件关系抽取、语篇关系分析方法及装置
CN113377915B (zh) * 2021-06-22 2022-07-19 厦门大学 对话篇章解析方法
CN113553830B (zh) * 2021-08-11 2023-01-03 桂林电子科技大学 一种基于图的英语文本句子语篇连贯分析方法

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5659766A (en) * 1994-09-16 1997-08-19 Xerox Corporation Method and apparatus for inferring the topical content of a document based upon its lexical content without supervision
AU2001261506A1 (en) * 2000-05-11 2001-11-20 University Of Southern California Discourse parsing and summarization
US7062561B1 (en) * 2000-05-23 2006-06-13 Richard Reisman Method and apparatus for utilizing the social usage learned from multi-user feedback to improve resource identity signifier mapping
US7127208B2 (en) * 2002-01-23 2006-10-24 Educational Testing Service Automated annotation
US7305336B2 (en) * 2002-08-30 2007-12-04 Fuji Xerox Co., Ltd. System and method for summarization combining natural language generation with structural analysis

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111209366A (zh) * 2019-10-10 2020-05-29 天津大学 基于TransS驱动的互激励神经网络的隐式篇章关系识别方法
CN111209366B (zh) * 2019-10-10 2023-04-21 天津大学 基于TransS驱动的互激励神经网络的隐式篇章关系识别方法
CN112257460A (zh) * 2020-09-25 2021-01-22 昆明理工大学 基于枢轴的汉越联合训练神经机器翻译方法
CN112257460B (zh) * 2020-09-25 2022-06-21 昆明理工大学 基于枢轴的汉越联合训练神经机器翻译方法

Also Published As

Publication number Publication date
CA2917153C (fr) 2022-05-17
WO2015003143A3 (fr) 2015-05-14
WO2015003143A2 (fr) 2015-01-08
AU2014285073B2 (en) 2016-11-03
AU2014285073B9 (en) 2017-04-06
AU2014285073A1 (en) 2016-02-04

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