WO2018028164A1 - Procédé et dispositif d'extraction d'informations textuelles, et terminal mobile - Google Patents

Procédé et dispositif d'extraction d'informations textuelles, et terminal mobile Download PDF

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Publication number
WO2018028164A1
WO2018028164A1 PCT/CN2017/073944 CN2017073944W WO2018028164A1 WO 2018028164 A1 WO2018028164 A1 WO 2018028164A1 CN 2017073944 W CN2017073944 W CN 2017073944W WO 2018028164 A1 WO2018028164 A1 WO 2018028164A1
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information
symbol
extracted
vector
text
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PCT/CN2017/073944
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English (en)
Chinese (zh)
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陈军
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中兴通讯股份有限公司
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00Handling natural language data
    • G06F40/20Natural language analysis
    • G06F40/279Recognition of textual entities
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00Handling natural language data
    • G06F40/30Semantic analysis

Definitions

  • the embodiments of the present invention relate to the field of information processing technologies, and in particular, to a method, an apparatus, and a mobile terminal for extracting text information.
  • SMS and notification messages have become an essential function of mobile terminals.
  • the terminal will receive various types of short messages and notification messages, such as billing information, booking information, schedules, etc., with the increase of such information, the user is not very convenient to retrieve. If you can extract the key content of this information and combine it with other applications of the mobile phone, such as depositing into accounting software, calendar and other applications, it will bring great convenience to users in the inquiry and reminder of information, which is convenient for users. usage of.
  • the user For example, for a bank SMS bill, the user generally withdraws the repayment date and the repayment amount by himself and deposits it in the schedule. If the terminal can intelligently extract such useful information and output it to the calendar, the user does not have to spend a lot of effort to find the search for the terminal to store a large number of short messages and notification messages, and it is not easy to forget the important schedule.
  • the technical problem to be solved by the embodiments of the present invention is to provide a method, a device, and a mobile terminal for extracting text information, and solving the problem that the fixed template is difficult to extract key information flexibly and accurately in the related art.
  • an embodiment of the present invention provides a method for extracting text information, including:
  • the step of determining, according to the context information of the first symbol, whether the first symbol meets the semantics of the information to be extracted includes:
  • the performing the weighting operation according to the first vector information and the second vector information, and determining, according to the operation result, whether the first symbol meets the semantics of the information to be extracted includes:
  • the step of performing a weighting operation by using the weight coefficients corresponding to the preset multiple information types according to the first vector information and the second vector information includes:
  • the step of identifying information corresponding to the preset one or more symbols in the text information includes:
  • the information corresponding to the preset one or more symbols in the text information is identified by means of regular expressions and/or keyword matching.
  • the step of acquiring the first symbol corresponding to the information to be extracted and the context information of the first symbol includes:
  • the extraction method further includes:
  • the obtained characters before the first symbol and the preset useless characters included in the characters after the first symbol are excluded, and the preset useless characters include punctuation marks, modal characters and blank symbols.
  • the step of acquiring the first symbol corresponding to the information to be extracted and the context information of the first symbol includes:
  • the first symbol corresponding to the information to be extracted and the context information of the first symbol are acquired.
  • an embodiment of the present invention further provides a text information extracting apparatus, including:
  • the replacement module is configured to identify information corresponding to the preset one or more symbols in the text information, and replace the identified information with the corresponding symbol;
  • Obtaining a module configured to acquire, in the replaced text information, a first symbol corresponding to the information to be extracted and context information of the first symbol;
  • the extracting module is configured to determine, according to the context information of the first symbol, whether the first symbol conforms to the semantics of the information to be extracted, and if yes, extract the content replaced by the first symbol Information and output.
  • the extraction module includes:
  • a first acquiring sub-module configured to acquire, in a preset vector database, first vector information corresponding to the first symbol and second vector information corresponding to context information of the first symbol;
  • the first determining sub-module is configured to perform a weighting operation according to the first vector information and the second vector information, and determine, according to the operation result, whether the first symbol conforms to the semantics of the information to be extracted.
  • an embodiment of the present invention further provides a mobile terminal, comprising: the text information extracting apparatus according to any one of the preceding claims.
  • Another embodiment of the present invention provides a computer storage medium, where the computer storage medium stores execution instructions for performing one or a combination of the steps in the foregoing method embodiments.
  • the method for extracting text information in the embodiment of the present invention first identifies information corresponding to the preset one or more symbols in the text information, and replaces the identified information with the corresponding symbol; and then in the replaced text information. Obtaining the first symbol corresponding to the information to be extracted and the context information of the first symbol; finally, determining, according to the context information of the first symbol, whether the first symbol conforms to the semantics of the information to be extracted, and if yes, extracting the text information The information replaced by the first symbol is output.
  • the semantic feature of the context of the text information is used to extract the information, and the content of interest to the user can be intelligently extracted; without specifying a keyword, the method has greater flexibility than the traditional template matching method, and can adapt to different writing modes.
  • the terminal enables various applications based on intelligent understanding of the text language and enhances the user experience. Solved the use of fixed technology in related technologies It is difficult for templates to extract key information in a flexible and accurate manner.
  • FIG. 1 is a flowchart of a method for extracting text information according to an embodiment of the present invention
  • FIG. 2 is a schematic structural diagram of an apparatus for extracting text information according to an embodiment of the present invention.
  • a method for extracting text information includes:
  • Step 101 Identify information corresponding to the preset one or more symbols in the text information, and replace the identified information with the corresponding symbol.
  • the text information includes short messages and notification messages received by the terminal, and the like.
  • some special types of words and/or symbols corresponding to words may be preset.
  • the e-mail address, URL, date, time, percentage, quantifier, currency, phone number, number, foreign words, etc. contained in the text message string can be replaced with special symbols.
  • custom vocabulary can also be replaced with special symbols, such as vocabulary, idioms, food, place, equipment, person name, place name, organization name, etc. in professional application fields.
  • the preset symbols include “DATE” corresponding to the date, “CURRENCY” corresponding to the currency, “BANK” corresponding to the bank, and “TIME” corresponding to the time.
  • the preset symbols include “DATE” corresponding to the date, “CURRENCY” corresponding to the currency, “BANK” corresponding to the bank, and “TIME” corresponding to the time.
  • For the receipt of a text message "Your personal credit card November bill RMB 481.93, expired repayment date November 23rd. [China Merchants Bank]”, after identification, replacement, become “your personal credit card DATE bill CURRENCY, expired Day DATE. [BANK]”.
  • the repayment amount is RMB 940.18.
  • [ICBC] after Identification, After the replacement, become a "respected customer, your personal loan in BANK must be repaid before TIME DATE, the repayment amount of principal and interest total CURREN
  • Step 102 Acquire, in the replaced text information, a first symbol corresponding to the information to be extracted and context information of the first symbol.
  • the first symbol and the context information of the first symbol need to be acquired in the text information to determine, by subsequent steps, whether the semantics of the first symbol in the text information conform to the semantics of the information to be extracted.
  • the context information of the symbols "DATE” and "DATE” corresponding to the repayment date needs to be obtained in the replaced text information.
  • Step 103 Determine, according to the context information of the first symbol, whether the first symbol meets the semantics of the information to be extracted, and if yes, extract information that is replaced by the first symbol from the text information. Output.
  • a plurality of first symbols may be acquired in the text information, and the semantics of each of the first symbols may be different in the text information. Therefore, it is required to combine the context information of the first symbol to determine whether the first symbol conforms to the semantics of the information to be extracted. If it is met, the information replaced by the first symbol is the information to be extracted, and the information replaced by the first symbol is extracted from the text information and output.
  • the outputted information can be output to some applications of the terminal, such as outputting the repayment date to the calendar application, so as to implement functions such as date reminding.
  • the method for extracting text information combines the semantic features of the context of the text information to extract information, and can intelligently extract content of interest such as repayment date and repayment amount; without specifying keywords,
  • the template matching method has greater flexibility and can adapt to different writing styles; enables the terminal to carry out various applications on the basis of intelligent understanding of the text language, thereby improving the user experience.
  • the problem that the fixed template is difficult to extract key information flexibly and accurately in the related art is solved.
  • the step of determining, according to the context information of the first symbol, whether the first symbol meets the semantics of the information to be extracted may include:
  • Step 1031 Acquire, in a preset vector database, first vector information corresponding to the first symbol and second vector information corresponding to context information of the first symbol.
  • the first vector information corresponding to the first symbol and the second vector information corresponding to the context information of the first symbol may be acquired in the pre-trained vector database to perform weighting calculation by the subsequent steps.
  • the vector database may include a vector value corresponding to each symbol and a vector value corresponding to a word and/or a word that may be used in the context.
  • the vector value corresponding to each word and/or word included in the context information may be obtained to obtain a vector sequence.
  • the vector in the vector sequence should be consistent with the contextual order of the text information.
  • Step 1032 Perform a weighting operation according to the first vector information and the second vector information, and determine, according to the operation result, whether the first symbol conforms to the semantics of the information to be extracted.
  • the weighting operation is performed according to the acquired vector information, and according to the operation result, it is determined whether the first symbol conforms to the semantics of the information to be extracted (such as the repayment date).
  • the weighting operation based on the vector information can accurately determine the semantics of the first symbol, thereby achieving the purpose of accurately extracting key information.
  • the foregoing step 1032 may include:
  • Step 10321 Perform weighting operations on the first vector information and the second vector information by using weight coefficients corresponding to preset multiple information types to obtain an operation result.
  • Step 10322 Determine, according to the operation result, an information type of the first symbol.
  • the information type of the first symbol is determined by the calculated probability value of each type of information.
  • the information type with the largest probability value can be selected as the information type of the first symbol.
  • Step 10323 Determine whether the information type of the first symbol is consistent with the information type of the information to be extracted, and if yes, determine that the first symbol conforms to the semantics of the information to be extracted, otherwise, determine the first The symbol does not conform to the semantics of the information to be extracted.
  • the information type of the first symbol is consistent with the information type of the information to be extracted, it may be determined that the first symbol conforms to the semantics of the information to be extracted, otherwise, it may be determined that the first symbol does not conform to the semantics of the information to be extracted.
  • the information type of the information to be extracted may be a repayment date and a repayment amount, that is, it is possible to simultaneously extract a plurality of information to be extracted.
  • the weighting operation is performed by the weight coefficient corresponding to the preset information type, and the semantics of the first symbol can be accurately determined, thereby achieving the purpose of accurately extracting key information.
  • the step of the above step 10321 may include:
  • Step 103211 Perform a pre-trained model using a bidirectional long- and short-range memory model neural network or a convolutional neural network, and perform pre-processing on the first vector information and the second vector information to obtain a combined vector.
  • Step 103212 Perform weighting operations on the weight coefficients corresponding to the multiple information types according to the combination vector.
  • the model pre-trained by the two-way long- and short-range memory model neural network or the convolutional neural network first pre-processes the first vector information and the second vector information to obtain a combined vector of the first symbol and the context, and then passes the combination.
  • Vector weight coefficient corresponding to multiple information types Do not perform weighting operations, can accurately determine the semantics of the first symbol, so as to accurately extract key information.
  • the step of identifying the information corresponding to the preset one or more symbols in the text information may include:
  • step 1011 the information corresponding to the preset one or more symbols in the text information is identified by using a regular expression and/or a keyword matching manner.
  • the regular expression and/or keyword matching method can accurately identify the information corresponding to the preset symbol in the text information.
  • the foregoing step 102 may include:
  • Step 1021 In the replaced text information, acquiring a first symbol corresponding to the information to be extracted, and acquiring a first preset number of characters and/or the first symbol before the first symbol A second predetermined number of characters including words and/or words.
  • first preset number and the second preset number are both set to 5, it is necessary to acquire 5 characters before and after the first symbol.
  • the Chinese sentence is very free, it is generally more important than the following to identify the current symbol. Therefore, an asymmetric context can also be used. If the first preset number is set to 7 and the second preset number is set to 5, it is necessary to acquire 7 characters before the first symbol and 5 characters after the first symbol.
  • the number of characters of the context can be defined as needed to better distinguish the semantics of the first symbol in combination with the context.
  • the number of characters determining the context is equivalent to determining the size of the context window of the current symbol, and the semantics of the current symbol are subsequently determined by the characters in the context window. Assume that the first preset number and the second preset number are both set to 5. For DATE in "expiration repayment date DATE. [BANK]”, if DATE is the current symbol to discriminate semantics, the context window contains words It is “to”, “period”, “return”, “model”, “day”, “.”, “[”, “BANK”, “]”.
  • the extracting method may further include:
  • Step 1022 culling the obtained character before the first symbol and the first symbol
  • the preset useless characters are included in the following characters, and the preset useless characters include punctuation marks, modal particles, and blank symbols.
  • the preset useless characters may also include some special symbols and the like.
  • step 102 may include:
  • Step 1023 Perform word segmentation on the replaced text information.
  • Step 1024 Acquire, in the text information after the word segmentation, the first symbol corresponding to the information to be extracted and the context information of the first symbol.
  • the word segmentation technique can be used to first perform word segmentation on the content of the text information, that is, the common words are separated, thereby facilitating the semantic judgment.
  • the word vector corresponding to the word can be directly read, and the corresponding word vector does not have to be read.
  • the above-mentioned word segmentation process can be omitted, because the model of the weighting operation can express the semantics of various combinations of different words when the sample is sufficient.
  • the method for extracting text information combines the semantic features of the context of the text information to extract information, and can intelligently extract content of interest such as repayment date and repayment amount; Compared with the traditional template matching method, it has greater flexibility and can adapt to different writing styles; enables the terminal to carry out various applications on the basis of intelligent understanding of the text language, facilitating the realization of smart reminders and other functions; Subsequent storage, retrieval and other applications have improved the user experience.
  • the problem that the fixed template is difficult to extract key information flexibly and accurately in the related art is solved.
  • an embodiment of the present invention further provides an apparatus for extracting text information, including:
  • the replacement module 201 is configured to identify information corresponding to the preset one or more symbols in the text information, and replace the identified information with the corresponding symbol;
  • the obtaining module 202 is configured to: obtain, in the replaced text information, a first symbol corresponding to the information to be extracted and context information of the first symbol;
  • the extracting module 203 is configured to determine, according to the context information of the first symbol, whether the first symbol conforms to the semantics of the information to be extracted, and if yes, extract the text information to be replaced by the first symbol Information and output.
  • the text information extracting apparatus of the embodiment of the present invention combines the semantic features of the context of the text information to extract information, and can intelligently extract content of interest such as repayment date and repayment amount; without specifying a keyword,
  • the template matching method has greater flexibility and can adapt to different writing styles; enables the terminal to carry out various applications on the basis of intelligent understanding of the text language, thereby improving the user experience.
  • the problem that the fixed template is difficult to extract key information flexibly and accurately in the related art is solved.
  • the extraction module 203 includes:
  • a first acquiring sub-module configured to acquire, in a preset vector database, first vector information corresponding to the first symbol and second vector information corresponding to context information of the first symbol;
  • the first determining sub-module is configured to perform a weighting operation according to the first vector information and the second vector information, and determine, according to the operation result, whether the first symbol conforms to the semantics of the information to be extracted.
  • the first determining submodule comprises:
  • the first weighting operation unit is configured to perform weighting operations on the first vector information and the second vector information by using weight coefficients corresponding to the preset plurality of information types to obtain an operation result;
  • a first determining unit configured to determine, according to the operation result, an information type of the first symbol
  • a second determining unit configured to determine whether the information type of the first symbol is consistent with the information type of the information to be extracted, and if yes, determining that the first symbol conforms to the semantics of the information to be extracted, otherwise, determining The first symbol does not conform to the semantics of the information to be extracted.
  • the first weighting operation unit includes:
  • a pre-processing sub-unit configured to pre-train the model using a bidirectional long- and short-range memory model neural network or a convolutional neural network, and pre-process the first vector information and the second vector information to obtain a combined vector;
  • the first weighting operation subunit is configured to perform a weighting operation on the weight coefficients corresponding to the plurality of information types according to the combination vector.
  • the replacement module 201 includes:
  • the identification sub-module is configured to identify information corresponding to the preset one or more symbols in the text information by using a regular expression and/or a keyword matching manner.
  • the obtaining module 202 includes:
  • a second obtaining sub-module configured to acquire, in the replaced text information, a first symbol corresponding to the information to be extracted, and acquire a first preset number of characters and/or the first symbol A second predetermined number of characters after the first symbol, the characters including words and/or words.
  • the extracting device further includes:
  • the culling module is configured to cull the obtained character before the first symbol and the preset useless characters included in the character after the first symbol, the preset useless characters including punctuation marks, modal characters and blank symbols.
  • the obtaining module 202 includes:
  • a word segmentation sub-module configured to perform word segmentation on the replaced text information
  • the third obtaining sub-module is configured to acquire, in the text information after the word segmentation processing, the first symbol corresponding to the information to be extracted and the context information of the first symbol.
  • the text information extracting apparatus of the embodiment of the present invention combines the semantic features of the context of the text information to extract information, and can intelligently extract content of interest such as repayment date and repayment amount; Compared with the traditional template matching method, it has greater flexibility and can adapt to different writing styles; enables the terminal to carry out various applications on the basis of intelligent understanding of the text language, facilitating the realization of smart reminders and other functions; Subsequent storage, retrieval The application experience has improved the user experience. The problem that the fixed template is difficult to extract key information flexibly and accurately in the related art is solved.
  • the apparatus for extracting the text information is a device corresponding to the method for extracting the text information, wherein all the implementation manners in the foregoing method embodiments are applicable to the embodiment of the device, and the same technical effect can be achieved. .
  • the text information extracting apparatus of the embodiment of the present invention is applied to a mobile terminal. Therefore, the embodiment of the present invention further provides a mobile terminal, including: the text information extracting apparatus as described in the foregoing embodiment.
  • the implementation examples of the foregoing text information extracting apparatus are applicable to the embodiment of the mobile terminal, and the same technical effects can be achieved.
  • the mobile terminal of the present invention may be a mobile electronic device such as a mobile phone or a tablet computer.
  • Embodiments of the present invention also provide a storage medium.
  • the foregoing storage medium stores an execution instruction, where the execution instruction is used to perform one or a combination of the steps in the foregoing method embodiments.
  • the foregoing storage medium may include, but is not limited to, a USB flash drive, a Read-Only Memory (ROM), and a Random Access Memory (RAM).
  • ROM Read-Only Memory
  • RAM Random Access Memory
  • the method, apparatus, and mobile terminal for extracting text information provided by the embodiments of the present invention have the following beneficial effects: can be combined with the semantic features of the context of the text information.
  • the extraction of information can intelligently extract the content of interest to the user; it does not need to specify keywords, and has greater flexibility than the traditional template matching method, and can adapt to different styles of writing; the terminal is developed on the basis of intelligent understanding of the text language.
  • a variety of applications that enhance the user experience. The problem that the fixed template is difficult to extract key information flexibly and accurately in the related art is solved.

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Abstract

L'invention concerne un procédé et un dispositif d'extraction d'informations textuelles, ainsi qu'un terminal mobile, se rapportant au domaine de la technologie de traitement d'informations, qui résolvent le problème de la difficulté d'extraire des informations-clés de manière souple et précise en utilisant un modèle fixe. Le procédé comporte les étapes consistant à: identifier des informations dans les informations textuelles correspondant à un ou plusieurs symboles prédéfinis, et remplacer les informations identifiées par le symbole correspondant (101); dans les informations textuelles remplacées, obtenir un premier symbole correspondant à des informations à extraire et à des informations de contexte du premier symbole (102); et d'après les informations de contexte du premier symbole, déterminer si le premier symbole se conforme ou non à la sémantique des informations à extraire, et si le premier symbole se conforme à la sémantique des informations à extraire, extraire les informations remplacées par le premier symbole des informations textuelles et les délivrer (103). Dans le procédé ci-dessus, les informations sont extraites en combinant des caractéristiques sémantiques du contexte des informations textuelles, qui peuvent être adaptées de manière souple à différentes manières d'écrire, et peuvent extraire avec précision le contenu de centres d'intérêt de l'utilisateur.
PCT/CN2017/073944 2016-08-11 2017-02-17 Procédé et dispositif d'extraction d'informations textuelles, et terminal mobile WO2018028164A1 (fr)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110782888A (zh) * 2018-07-27 2020-02-11 国际商业机器公司 用于改变感知认知状态的语音语气控制系统
CN113609853A (zh) * 2021-07-30 2021-11-05 支付宝(杭州)信息技术有限公司 一种企业主体属性识别方法、装置及设备

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110837547A (zh) * 2019-10-16 2020-02-25 云知声智能科技股份有限公司 一种人机交互中多意图文本理解的方法及装置
CN113345409B (zh) * 2021-08-05 2021-11-26 北京世纪好未来教育科技有限公司 语音合成方法、装置、电子设备及计算机可读存储介质

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130113902A1 (en) * 2011-11-04 2013-05-09 Inventec Corporation Reminding method for daily life management
CN103984687A (zh) * 2013-02-07 2014-08-13 北京搜狗科技发展有限公司 提醒的创建方法和装置
CN104378441A (zh) * 2014-11-25 2015-02-25 小米科技有限责任公司 日程创建方法和装置
CN105183704A (zh) * 2014-06-17 2015-12-23 中兴通讯股份有限公司 一种从文本中提取农历时间的方法及装置
CN105447750A (zh) * 2015-11-17 2016-03-30 小米科技有限责任公司 信息识别方法、装置、终端及服务器

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9542528B2 (en) * 2012-03-30 2017-01-10 The Florida State University Research Foundation, Inc. Automated extraction of bio-entity relationships from literature
CN104699763B (zh) * 2015-02-11 2017-10-17 中国科学院新疆理化技术研究所 多特征融合的文本相似性度量系统

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130113902A1 (en) * 2011-11-04 2013-05-09 Inventec Corporation Reminding method for daily life management
CN103984687A (zh) * 2013-02-07 2014-08-13 北京搜狗科技发展有限公司 提醒的创建方法和装置
CN105183704A (zh) * 2014-06-17 2015-12-23 中兴通讯股份有限公司 一种从文本中提取农历时间的方法及装置
CN104378441A (zh) * 2014-11-25 2015-02-25 小米科技有限责任公司 日程创建方法和装置
CN105447750A (zh) * 2015-11-17 2016-03-30 小米科技有限责任公司 信息识别方法、装置、终端及服务器

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110782888A (zh) * 2018-07-27 2020-02-11 国际商业机器公司 用于改变感知认知状态的语音语气控制系统
CN113609853A (zh) * 2021-07-30 2021-11-05 支付宝(杭州)信息技术有限公司 一种企业主体属性识别方法、装置及设备

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