EP0968478A1 - Procede de generation automatique d'un resume d'un texte par un ordinateur - Google Patents

Procede de generation automatique d'un resume d'un texte par un ordinateur

Info

Publication number
EP0968478A1
EP0968478A1 EP98914784A EP98914784A EP0968478A1 EP 0968478 A1 EP0968478 A1 EP 0968478A1 EP 98914784 A EP98914784 A EP 98914784A EP 98914784 A EP98914784 A EP 98914784A EP 0968478 A1 EP0968478 A1 EP 0968478A1
Authority
EP
European Patent Office
Prior art keywords
sentence
text
word
words
probability
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP98914784A
Other languages
German (de)
English (en)
Inventor
Thomas BRÜCKNER
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Siemens AG
Siemens Corp
Original Assignee
Siemens AG
Siemens Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Siemens AG, Siemens Corp filed Critical Siemens AG
Publication of EP0968478A1 publication Critical patent/EP0968478A1/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/30—Semantic analysis
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G06F16/34—Browsing; Visualisation therefor
    • G06F16/345—Summarisation for human users
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/205—Parsing
    • G06F40/216—Parsing using statistical methods
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/279—Recognition of textual entities
    • G06F40/284—Lexical analysis, e.g. tokenisation or collocates
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/30—Semantic analysis
    • G06F40/35—Discourse or dialogue representation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99933—Query processing, i.e. searching
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99933—Query processing, i.e. searching
    • Y10S707/99934—Query formulation, input preparation, or translation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99933—Query processing, i.e. searching
    • Y10S707/99935—Query augmenting and refining, e.g. inexact access

Definitions

  • the invention relates to a method for the automatic generation of a summary of a text by a computer.
  • a special type of information reduction consists in the merging of texts.
  • a method for summarizing texts is known from [1] which uses heuristic features with a discrete range of values.
  • the probability that a sentence from the text belongs to the summary on the condition that a heuristic feature has a certain value is estimated from a training set of summaries.
  • the object of the invention is to automatically generate a summary from a given text, which summary is intended to represent the essential contents of the text in short form.
  • the method according to the invention enables a text to be summarized by determining for each sentence of this text a probability that the sentence belongs to the summary.
  • the relevance measure is determined for each word m in the sentence from a lexicon which contains all relevant words with a predefined relevance measure for each of these words.
  • the accumulation of all relevance measures gives the probability of the sentence belonging to the summary. All records are then sorted according to their probability.
  • a predeterminable reduction measure which indicates what percentage of the original text is shown in the summary, serves for the selection of the number of sentences given by this reduction measure from the sorted representation. If the most important x-percent sentences are selected, they are displayed as a summary of the text in its original order given by this text.
  • An advantageous further development of the method according to the invention consists in introducing an frequency of Emzelworth in addition to the relevance measure. This level of detail indicates how often the word in question appears in the entire text to be summarized. Taking into account the relevance measure and this newly introduced
  • N is the total number of words in the
  • a further development of the method according to the invention consists in using an application-specific lexicon.
  • a lexicon specified for sports contributions will rate sports-related words with a higher relevance for a text to be summarized than a lexicon that specializes in summaries of economic contributions. It is therefore advantageously possible to provide specific knowledge about predefinable categories by means of lexica corresponding to the respective categories.
  • a text is also advantageous to assign a text to one or more categories. This can be done automatically by using specific, predefinable words in the subject-related lexica as a selection criterion for an assignment to the respective subject area. If several categories (subject areas), i.e. different perspectives or filters, are possible for the summary of a text, different summaries, one for each category, can be created automatically.
  • FIG. 1 is a sketch illustrating a system for automatically generating a summary
  • Fig. 2 is a block diagram illustrating the steps of the method according to the invention.
  • FIG. 1 shows a system with which an automatic generation of a summary of text by a
  • a text to be summarized can either be written TXT, e.g. on paper, or in digital form DIGTXT, e.g. as the result of a database query.
  • the text TXT is read in by the scanner SC and stored as an image file BD.
  • a text recognition software OCR converts the text TXT m present as an image file BD into a machine-readable format, e.g. ASCII format to.
  • the digital text DIGTXT is already available in machine-readable format.
  • the summary according to the invention is created using the corresponding lexicon (in the KatSel block).
  • step 2a the first sentence is selected at the beginning of the method according to the invention and the probability that this sentence belongs to the summary is set to 0.
  • step 2b the first word of this sentence is selected. Since the probability that this sentence belongs to the summary is derived from the
  • step 2e If the probabilities of the individual words are put together, for each word in the sentence in the loop from step 2c to step 2e, the respective probability is cumulated to the overall probability for the entire sentence. Once all the words in the sentence have been processed, the probability for the individual sentence is normalized by the number of words. The steps described are carried out for all sentences in the text (step 2g, 2h, 2 ⁇ ). If the last sentence in the text has been processed, the sentences are after their
  • step 2j Probability sorted (step 2j). According to a predeterminable reduction measure, the n best sentences corresponding to the reduction measure are selected in step 2k and then their original sequence is displayed in step 2m.

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Computational Linguistics (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Probability & Statistics with Applications (AREA)
  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Document Processing Apparatus (AREA)

Abstract

Le procédé selon l'invention permet la rédaction automatique, fondée sur les phrases, d'un texte, sur un ordinateur. A cet effet, sont utilisés des lexiques thématiques qui confèrent à chacun des mots qu'ils contiennent une grandeur de pertinence. Chaque phrase ou texte à résumer est traité mot par mot et, pour chaque mot, une fréquence de mot individuel est cumulée tout en étant pondérée avec la grandeur de pertinence. Pour la rédaction du résumé, sont assemblées les n phrases présentant la plus grande probabilité d'appartenir au résumé, n étant une grandeur de réduction prédéfinissable.
EP98914784A 1997-03-18 1998-02-18 Procede de generation automatique d'un resume d'un texte par un ordinateur Withdrawn EP0968478A1 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
DE19711284 1997-03-18
DE19711284 1997-03-18
PCT/DE1998/000485 WO1998041930A1 (fr) 1997-03-18 1998-02-18 Procede de generation automatique d'un resume d'un texte par un ordinateur

Publications (1)

Publication Number Publication Date
EP0968478A1 true EP0968478A1 (fr) 2000-01-05

Family

ID=7823794

Family Applications (1)

Application Number Title Priority Date Filing Date
EP98914784A Withdrawn EP0968478A1 (fr) 1997-03-18 1998-02-18 Procede de generation automatique d'un resume d'un texte par un ordinateur

Country Status (4)

Country Link
US (1) US6401086B1 (fr)
EP (1) EP0968478A1 (fr)
JP (1) JP2001515623A (fr)
WO (1) WO1998041930A1 (fr)

Families Citing this family (46)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6789230B2 (en) * 1998-10-09 2004-09-07 Microsoft Corporation Creating a summary having sentences with the highest weight, and lowest length
US7475334B1 (en) * 2000-01-19 2009-01-06 Alcatel-Lucent Usa Inc. Method and system for abstracting electronic documents
JP2004514350A (ja) * 2000-11-14 2004-05-13 コーニンクレッカ　フィリップス　エレクトロニクス　エヌ　ヴィ 番組の要約と索引付け
WO2003012661A1 (fr) * 2001-07-31 2003-02-13 Invention Machine Corporation Recapitulation informatique de documents en langage naturel
US8799776B2 (en) * 2001-07-31 2014-08-05 Invention Machine Corporation Semantic processor for recognition of whole-part relations in natural language documents
US9009590B2 (en) * 2001-07-31 2015-04-14 Invention Machines Corporation Semantic processor for recognition of cause-effect relations in natural language documents
US6904564B1 (en) * 2002-01-14 2005-06-07 The United States Of America As Represented By The National Security Agency Method of summarizing text using just the text
US7549114B2 (en) * 2002-02-21 2009-06-16 Xerox Corporation Methods and systems for incrementally changing text representation
US7650562B2 (en) * 2002-02-21 2010-01-19 Xerox Corporation Methods and systems for incrementally changing text representation
US20040199408A1 (en) * 2003-04-01 2004-10-07 Johnson Tolbert R. Medical information card
US9275052B2 (en) 2005-01-19 2016-03-01 Amazon Technologies, Inc. Providing annotations of a digital work
US8131647B2 (en) 2005-01-19 2012-03-06 Amazon Technologies, Inc. Method and system for providing annotations of a digital work
US8234279B2 (en) * 2005-10-11 2012-07-31 The Boeing Company Streaming text data mining method and apparatus using multidimensional subspaces
US7752204B2 (en) * 2005-11-18 2010-07-06 The Boeing Company Query-based text summarization
US7831597B2 (en) * 2005-11-18 2010-11-09 The Boeing Company Text summarization method and apparatus using a multidimensional subspace
US8352449B1 (en) 2006-03-29 2013-01-08 Amazon Technologies, Inc. Reader device content indexing
US20080005284A1 (en) * 2006-06-29 2008-01-03 The Trustees Of The University Of Pennsylvania Method and Apparatus For Publishing Textual Information To A Web Page
US8725565B1 (en) 2006-09-29 2014-05-13 Amazon Technologies, Inc. Expedited acquisition of a digital item following a sample presentation of the item
US9672533B1 (en) 2006-09-29 2017-06-06 Amazon Technologies, Inc. Acquisition of an item based on a catalog presentation of items
US7865817B2 (en) 2006-12-29 2011-01-04 Amazon Technologies, Inc. Invariant referencing in digital works
US8024400B2 (en) 2007-09-26 2011-09-20 Oomble, Inc. Method and system for transferring content from the web to mobile devices
US7751807B2 (en) 2007-02-12 2010-07-06 Oomble, Inc. Method and system for a hosted mobile management service architecture
US9031947B2 (en) * 2007-03-27 2015-05-12 Invention Machine Corporation System and method for model element identification
US9665529B1 (en) 2007-03-29 2017-05-30 Amazon Technologies, Inc. Relative progress and event indicators
US7716224B2 (en) 2007-03-29 2010-05-11 Amazon Technologies, Inc. Search and indexing on a user device
US20080288488A1 (en) * 2007-05-15 2008-11-20 Iprm Intellectual Property Rights Management Ag C/O Dr. Hans Durrer Method and system for determining trend potentials
US20080293450A1 (en) 2007-05-21 2008-11-27 Ryan Thomas A Consumption of Items via a User Device
US20080301579A1 (en) * 2007-06-04 2008-12-04 Yahoo! Inc. Interactive interface for navigating, previewing, and accessing multimedia content
US9087032B1 (en) * 2009-01-26 2015-07-21 Amazon Technologies, Inc. Aggregation of highlights
US8378979B2 (en) 2009-01-27 2013-02-19 Amazon Technologies, Inc. Electronic device with haptic feedback
JP2012520529A (ja) * 2009-03-13 2012-09-06 インベンション マシーン コーポレーション 知識調査のためのシステム及び方法
CN102439590A (zh) * 2009-03-13 2012-05-02 发明机器公司 用于自然语言文本的自动语义标注的系统和方法
US8832584B1 (en) 2009-03-31 2014-09-09 Amazon Technologies, Inc. Questions on highlighted passages
US8692763B1 (en) 2009-09-28 2014-04-08 John T. Kim Last screen rendering for electronic book reader
US9495322B1 (en) 2010-09-21 2016-11-15 Amazon Technologies, Inc. Cover display
US9298287B2 (en) 2011-03-31 2016-03-29 Microsoft Technology Licensing, Llc Combined activation for natural user interface systems
US9244984B2 (en) 2011-03-31 2016-01-26 Microsoft Technology Licensing, Llc Location based conversational understanding
US9858343B2 (en) 2011-03-31 2018-01-02 Microsoft Technology Licensing Llc Personalization of queries, conversations, and searches
US9842168B2 (en) 2011-03-31 2017-12-12 Microsoft Technology Licensing, Llc Task driven user intents
US9760566B2 (en) 2011-03-31 2017-09-12 Microsoft Technology Licensing, Llc Augmented conversational understanding agent to identify conversation context between two humans and taking an agent action thereof
US10642934B2 (en) 2011-03-31 2020-05-05 Microsoft Technology Licensing, Llc Augmented conversational understanding architecture
US9454962B2 (en) * 2011-05-12 2016-09-27 Microsoft Technology Licensing, Llc Sentence simplification for spoken language understanding
US9064006B2 (en) 2012-08-23 2015-06-23 Microsoft Technology Licensing, Llc Translating natural language utterances to keyword search queries
US9158741B1 (en) 2011-10-28 2015-10-13 Amazon Technologies, Inc. Indicators for navigating digital works
CN108090094A (zh) * 2016-11-23 2018-05-29 北京国双科技有限公司 一种文本信息分类方法及系统
CN110162778B (zh) * 2019-04-02 2023-05-26 创新先进技术有限公司 文本摘要的生成方法及装置

Family Cites Families (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4965763A (en) * 1987-03-03 1990-10-23 International Business Machines Corporation Computer method for automatic extraction of commonly specified information from business correspondence
US4930077A (en) * 1987-04-06 1990-05-29 Fan David P Information processing expert system for text analysis and predicting public opinion based information available to the public
JP2783558B2 (ja) * 1988-09-30 1998-08-06 株式会社東芝 要約生成方法および要約生成装置
JP2790466B2 (ja) * 1988-10-18 1998-08-27 株式会社日立製作所 文字列検索方法及び装置
JPH03278270A (ja) * 1990-03-28 1991-12-09 Ricoh Co Ltd 抄録文作成装置
US5317507A (en) * 1990-11-07 1994-05-31 Gallant Stephen I Method for document retrieval and for word sense disambiguation using neural networks
US5325298A (en) * 1990-11-07 1994-06-28 Hnc, Inc. Methods for generating or revising context vectors for a plurality of word stems
EP0601666B1 (fr) 1992-12-09 1999-04-21 Koninklijke Philips Electronics N.V. Dispositif d'affichage séquentiel couleur à valve optique
US5799299A (en) * 1994-09-14 1998-08-25 Kabushiki Kaisha Toshiba Data processing system, data retrieval system, data processing method and data retrieval method
JPH08305695A (ja) * 1995-04-28 1996-11-22 Fujitsu Ltd 文書処理装置
US5887120A (en) * 1995-05-31 1999-03-23 Oracle Corporation Method and apparatus for determining theme for discourse
US5778397A (en) 1995-06-28 1998-07-07 Xerox Corporation Automatic method of generating feature probabilities for automatic extracting summarization
US6006221A (en) * 1995-08-16 1999-12-21 Syracuse University Multilingual document retrieval system and method using semantic vector matching
US5963940A (en) * 1995-08-16 1999-10-05 Syracuse University Natural language information retrieval system and method
US6026388A (en) * 1995-08-16 2000-02-15 Textwise, Llc User interface and other enhancements for natural language information retrieval system and method
US5963893A (en) * 1996-06-28 1999-10-05 Microsoft Corporation Identification of words in Japanese text by a computer system

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See references of WO9841930A1 *

Also Published As

Publication number Publication date
US6401086B1 (en) 2002-06-04
WO1998041930A1 (fr) 1998-09-24
JP2001515623A (ja) 2001-09-18

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