WO2023029507A1 - Procédé et appareil de distribution de services basés sur une analyse de données, dispositif et support d'enregistrement - Google Patents

Procédé et appareil de distribution de services basés sur une analyse de données, dispositif et support d'enregistrement Download PDF

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WO2023029507A1
WO2023029507A1 PCT/CN2022/087811 CN2022087811W WO2023029507A1 WO 2023029507 A1 WO2023029507 A1 WO 2023029507A1 CN 2022087811 W CN2022087811 W CN 2022087811W WO 2023029507 A1 WO2023029507 A1 WO 2023029507A1
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text
data
policy
user
service
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PCT/CN2022/087811
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English (en)
Chinese (zh)
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刘福婷
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康键信息技术（深圳）有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08—Insurance
    • 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
    • G06F16/33—Querying
    • G06F16/3331—Query processing
    • G06F16/334—Query execution
    • G06F16/3344—Query execution using natural language analysis
    • 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
    • G06F16/33—Querying
    • G06F16/3331—Query processing
    • G06F16/334—Query execution
    • G06F16/3346—Query execution using probabilistic model
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/279—Recognition of textual entities
    • G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking

Definitions

  • the present application relates to the technical field of artificial intelligence, and in particular to a data analysis-based service distribution method, device, electronic equipment, and computer-readable storage medium.
  • a service distribution method based on data analysis provided by this application includes:
  • a service list is generated according to the policy information and the available services, and the service list is pushed to the user.
  • the present application also provides a service distribution device based on data analysis, the device includes:
  • the text conversion module is used to obtain the policy information of the user, and perform text conversion on the policy information to obtain the policy text;
  • the characteristic word extraction module is used for carrying out word segmentation to described policy text, and carries out characteristic word extraction to the text word segmentation that word segmentation obtains, obtains user characteristic word;
  • Decision tree construction module used for constructing a decision tree model using the user feature words as a decision condition
  • a service screening module configured to obtain the use authority of preset services, and use the decision tree model to screen out the services available to the user from the preset services according to the use authority;
  • a service push module configured to generate a service list according to the policy information and the available services, and push the service list to the user.
  • the present application also provides an electronic device, the electronic device comprising:
  • the memory stores a computer program executable by the at least one processor, the computer program is executed by the at least one processor to enable the at least one processor to perform data analysis based services as described below Distribution method:
  • a service list is generated according to the policy information and the available services, and the service list is pushed to the user.
  • the present application also provides a computer-readable storage medium, at least one computer program is stored in the computer-readable storage medium, and the at least one computer program is executed by a processor in an electronic device to implement data-based analysis as described below
  • a service list is generated according to the policy information and the available services, and the service list is pushed to the user.
  • FIG. 1 is a schematic flowchart of a service distribution method based on data analysis provided by an embodiment of the present application
  • FIG. 2 is a schematic flow diagram of extracting user feature words provided by an embodiment of the present application.
  • Fig. 3 is a schematic flow chart of constructing a decision tree model provided by an embodiment of the present application.
  • FIG. 4 is a functional block diagram of a service distribution device based on data analysis provided by an embodiment of the present application
  • FIG. 5 is a schematic structural diagram of an electronic device implementing the data analysis-based service distribution method provided by an embodiment of the present application.
  • An embodiment of the present application provides a service distribution method based on data analysis.
  • the execution subject of the service distribution method based on data analysis includes, but is not limited to, at least one of electronic devices such as a server end and a terminal that can be configured to execute the method provided by the embodiment of the present application.
  • the service distribution method based on data analysis can be executed by software or hardware installed on the terminal device or server device, and the software can be a block chain platform.
  • the server includes, but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
  • the server can be an independent server, or it can provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery network (Content Delivery) Network, CDN), and cloud servers for basic cloud computing services such as big data and artificial intelligence platforms.
  • cloud services cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery network (Content Delivery) Network, CDN), and cloud servers for basic cloud computing services such as big data and artificial intelligence platforms.
  • FIG. 1 it is a schematic flowchart of a service distribution method based on data analysis provided by an embodiment of the present application.
  • the service distribution method based on data analysis includes:
  • the policy information includes data related to the insurance order purchased by the user, for example, data such as the user's age, gender, policy type, and policy amount.
  • computer statements (such as Java statements, python statements, etc.) with data capture functions can be used to capture pre-stored policy information that can be obtained with user authorization from a pre-built storage area.
  • the storage area includes but Not limited to databases, blockchains, web caches.
  • the obtained policy information may include data in various forms such as text, image, audio, etc.
  • the obtained policy information can be Perform text conversion to obtain policy text.
  • the text conversion of the policy information is performed to obtain the policy text, including:
  • the text data, the image text and the audio text are assembled into a policy text.
  • the data type field is a field used to mark the data type of each data; a pre-built regular expression with a data type field extraction function can be used to extract each A data type field of data, the regular expression can be used to realize the function of extracting data with a fixed format in the data.
  • the data in the policy information is divided according to the data type field to obtain text data, image data and audio data, including:
  • the data type field of the target data can be vector-converted by using an artificial intelligence model with a vector conversion function.
  • Cove model Cove model
  • Bert model etc.
  • the distance values between the data type vector and a plurality of preset data types can be respectively calculated by an algorithm with a distance value calculation function such as a cosine distance algorithm and a Euclidean distance algorithm, and the data type with the smallest distance value is determined to be The type of the target data.
  • a distance value calculation function such as a cosine distance algorithm and a Euclidean distance algorithm
  • the distance value between the data type vector of the target data and the text type is 20
  • the distance value between the data type vector of the target data and the image type is 90
  • the distance value between the data type vector of the target data and the audio type is 25, it can be confirmed that the data type of the target data is a graph type.
  • OCR Optical Character Recognition, optical character recognition
  • ASR Automatic Speech Recognition, automatic speech recognition
  • Carrying out voice recognition on the audio data in the policy information to obtain the audio text corresponding to the audio data, and collecting the text data, the image text and the audio text to obtain the policy text.
  • the policy text contains a large amount of text information
  • it will occupy a large amount of computing resources, resulting in low analysis efficiency, and a large amount of data is mixed, which will cause The analysis results are imprecise. Therefore, word segmentation can be performed on the policy text, and feature words can be extracted from the result of the word segmentation, so as to reduce the amount of data in the subsequent analysis of the policy text and improve the efficiency and accuracy of the analysis.
  • the described policy text is segmented, and the text segmentation obtained by word segmentation is subjected to feature word extraction to obtain user feature words, including:
  • the policy text contains a large amount of text data
  • a large amount of text data can be segmented using preset sentence symbols, so as to divide the policy text into multiple A text sentence, thereby reducing the amount of data for each word segmentation and improving word segmentation efficiency.
  • the sentence symbols include but are not limited to ",”, ".”, ".".
  • the dictionary is a pre-acquired dictionary containing multiple word segmentations, each text clause can be retrieved in the dictionary according to different data lengths, and the retrieved word segmentation can be used as the text segmentation of the policy text .
  • the frequency of occurrence is the number of times each text participle appears in all text participles of the policy text;
  • the position information refers to the sequence of positions of each text participle in the policy text,
  • the text participle in the policy text can be numbered according to the order of their positions in the policy text, and the number corresponding to each text participle is the position information of the text participle.
  • the calculation of the key degree of each of the text word segmentation according to the frequency of occurrence and the position information includes:
  • the following eigenvalue algorithm is used to calculate the key degree of each of the text word segmentation according to the frequency of occurrence and the position information:
  • K i ⁇ *A i + ⁇ *B i
  • K i is the key degree of the ith participle in the described text participle
  • A is the frequency of occurrence of the ith participle in the described text participle
  • Bi is the positional information of the ith participle in the described text participle
  • ⁇ and ⁇ are preset weight coefficients.
  • the word segmentation of the text whose key degree is greater than the preset threshold may be selected, and the selected text segmentation vocabulary set is the user characteristic word of the user.
  • the user characteristic words can be used as decision conditions to construct a decision tree for subsequent use
  • the constructed decision tree screens out services that can be obtained by the user from a large number of services.
  • the construction of a decision tree model using the user characteristic words as a decision condition includes:
  • the decision function may be:
  • f(x) is an output value of the decision function
  • x is a parameter of the decision function
  • g(y) is an input value of the decision function
  • one of the characteristic words can be selected as the target characteristic word one by one from the user characteristic words, and the target characteristic word is compiled into a characteristic parameter by using a preset compiler, and the decision function of the decision function by the characteristic parameter is used Parameter x is assigned, wherein the compiler includes but not limited to Visual Studio compiler, Dev C++ compiler.
  • the following decision tree can be generated by using the assigned decision function as the decision condition:
  • the usage rights include constraints required by the user when obtaining each preset service, for example, time limit, age limit, and the like.
  • the step of obtaining the use authority of the preset service is the same as the step of obtaining the user's policy information in S1, so it will not be repeated here.
  • the decision tree can be used to screen a variety of preset services to determine whether the use authority of each preset service in the multiple preset services conforms to the characteristics of the user, and then screen out The user meets the conditions and can use the service.
  • the use of the decision tree to screen out the user's usable services from the preset services according to the usage authority includes:
  • the output result of collecting all the decision trees is that the preset service corresponding to the usage authority whose input value is the same as the parameter of the target decision tree is an available service.
  • the decision tree model includes decision tree a 1 and decision tree a 2
  • the multiple preset services include service A and service B, select decision tree a 1 as the target decision tree, and select the use authority of service A
  • input the input value into the decision tree a 1 to obtain the output result that the input value output by the decision tree a 1 is the same as the parameter of the decision tree a 1
  • input the input value into the Decision tree a 2 obtain the output result that the input value output by the decision tree a 2 is the same as the parameter of the decision tree a 2
  • select the practical authority of service B as the input value
  • input the input value into the Decision tree b 1 obtaining the output result that the input value output by the decision tree b 1 is different from the parameters of the decision tree b 1
  • inputting the input value into the decision tree b 2 obtaining the decision tree
  • the input value output by b2 is the same as the output result of the parameter of the decision tree b2 , then only the input results of
  • a service list can be generated based on the policy information and the available services, and then The service list is recommended to the user.
  • the policy information and the available services are filled into a pre-generated blank data table to generate the service list, and the service list is displayed to the user.
  • the embodiment of the present application can analyze the user's policy information to extract keywords contained in the user's policy information, and then construct a decision tree model through the extracted keywords, and use the constructed decision tree model to perform multiple preset services Accurate condition screening, and then push the selected services to users, realize the precise screening of services, and improve the accuracy of service delivery to users. Therefore, the service distribution method based on data analysis proposed in this application can solve the problem of low accuracy in product recommendation.
  • FIG. 4 it is a functional block diagram of a service distribution device based on data analysis provided by an embodiment of the present application.
  • the data analysis-based service distribution apparatus 100 described in this application can be installed in an electronic device.
  • the data analysis-based service distribution device 100 may include a text conversion module 101 , a feature word extraction module 102 , a decision tree construction module 103 , a service screening module 104 and a service push module 105 .
  • the module described in this application can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of the electronic device and can complete fixed functions, and are stored in the memory of the electronic device.
  • each module/unit is as follows:
  • the text conversion module 101 is used to obtain the policy information of the user, and perform text conversion on the policy information to obtain the policy text;
  • the feature word extraction module 102 is configured to perform word segmentation on the policy text, and perform feature word extraction on the text word segmentation obtained by word segmentation to obtain user feature words;
  • the decision tree construction module 103 is used to construct a decision tree model using the user characteristic words as a decision condition;
  • the service screening module 104 is configured to obtain the use authority of preset services, and use the decision tree model to screen out the services available to the user from the preset services according to the use authority;
  • the service pushing module 105 is configured to generate a service list according to the policy information and the available services, and push the service list to the user.
  • each module described in the data analysis-based service distribution device 100 in the embodiment of the present application uses the same technical means as the data analysis-based service distribution method described in Figures 1 to 3 above. , and can produce the same technical effect, which will not be repeated here.
  • FIG. 5 it is a schematic structural diagram of an electronic device implementing a service distribution method based on data analysis provided by an embodiment of the present application.
  • the electronic device 1 may include a processor 10, a memory 11, a communication bus 12, and a communication interface 13, and may also include a computer program stored in the memory 11 and operable on the processor 10, such as based on data analysis service dispatcher.
  • the processor 10 may be composed of integrated circuits in some embodiments, for example, may be composed of a single packaged integrated circuit, or may be composed of multiple integrated circuits with the same function or different functions packaged, including one or A combination of multiple central processing units (Central Processing unit, CPU), microprocessors, digital processing chips, graphics processors and various control chips, etc.
  • the processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect the various components of the entire electronic device, and runs or executes programs or modules stored in the memory 11 (such as executing service distribution program based on data analysis, etc.), and call the data stored in the memory 11 to execute various functions of the electronic device and process data.
  • Control Unit Control Unit
  • the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card type memory (for example: SD or DX memory, etc.), magnetic memory, magnetic disk, optical disk, etc. , the computer-readable storage medium may be non-volatile or volatile.
  • the storage 11 may be an internal storage unit of the electronic device in some embodiments, such as a mobile hard disk of the electronic device.
  • the memory 11 can also be an external storage device of an electronic device in other embodiments, such as a plug-in mobile hard disk equipped on an electronic device, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD ) card, flash card (Flash Card), etc.
  • the storage 11 may also include both an internal storage unit of the electronic device and an external storage device.
  • the memory 11 can not only be used to store application software and various data installed in electronic equipment, such as codes of service distribution programs based on data analysis, but also can be used to temporarily store data that has been output or will be output.
  • the communication bus 12 may be a peripheral component interconnect (PCI for short) bus or an extended industry standard architecture (EISA for short) bus or the like.
  • PCI peripheral component interconnect
  • EISA extended industry standard architecture
  • the bus can be divided into address bus, data bus, control bus and so on.
  • the bus is configured to realize connection and communication between the memory 11 and at least one processor 10 and the like.
  • the communication interface 13 is used for communication between the electronic device and other devices, including a network interface and a user interface.
  • the network interface may include a wired interface and/or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which are generally used to establish a communication connection between the electronic device and other electronic devices.
  • the user interface may be a display (Display) or an input unit (such as a keyboard (Keyboard)).
  • the user interface may also be a standard wired interface or a wireless interface.
  • the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, and the like.
  • the display may also be properly referred to as a display screen or a display unit, and is used for displaying information processed in the electronic device and for displaying a visualized user interface.
  • FIG. 5 only shows an electronic device with components. Those skilled in the art can understand that the structure shown in FIG. 5 does not constitute a limitation to the electronic device 1, and may include fewer or more components, or combinations of certain components, or different arrangements of components.
  • the electronic device may also include a power supply (such as a battery) for supplying power to various components.
  • the power supply may be logically connected to the at least one processor 10 through a power management device, so that Realize functions such as charge management, discharge management, and power consumption management.
  • the power supply may also include one or more DC or AC power supplies, recharging devices, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components.
  • the electronic device may also include various sensors, a Bluetooth module, a Wi-Fi module, etc., which will not be repeated here.
  • the service distribution program based on data analysis stored in the memory 11 in the electronic device 1 is a combination of multiple instructions, and when running in the processor 10, it can realize:
  • a service list is generated according to the policy information and the available services, and the service list is pushed to the user.
  • the integrated modules/units of the electronic device 1 are realized in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium.
  • the computer-readable storage medium may be volatile or non-volatile.
  • the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM, Read-Only Memory).
  • the present application also provides a computer-readable storage medium, the readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, it can realize:
  • a service list is generated according to the policy information and the available services, and the service list is pushed to the user.
  • modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
  • each functional module in each embodiment of the present application may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated units can be implemented in the form of hardware, or in the form of hardware plus software function modules.
  • Blockchain essentially a decentralized database, is a series of data blocks associated with each other using cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify its Validity of information (anti-counterfeiting) and generation of the next block.
  • the blockchain can include the underlying platform of the blockchain, the platform product service layer, and the application service layer.
  • AI artificial intelligence
  • digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

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Abstract

La présente demande concerne le domaine technique de l'intelligence artificielle et de la médecine numérique, et divulgue un procédé de distribution de services basé sur une analyse de données, comprenant les étapes comprenant : l'acquisition des informations de police d'assurance d'un utilisateur, et la conversion des informations de police d'assurance en un texte de police d'assurance; la réalisation d'une segmentation de mots sur le texte de police d'assurance, et la réalisation d'une extraction de mots de caractéristique sur des mots du texte obtenu par la segmentation de mots pour obtenir un mot de caractéristique d'utilisateur; la construction d'un modèle d'arbre de décision à l'aide du mot de caractéristique d'utilisateur comme condition de décision; l'acquisition d'une autorisation d'utilisation pour un service prédéfini, et le criblage d'un service disponible pour l'utilisateur à partir de services prédéfinis selon l'autorisation d'utilisation à l'aide du modèle d'arbre de décision; la génération d'une liste de services selon les informations de police d'assurance et le service disponible, et la poussée de la liste de services vers l'utilisateur, les informations de police d'assurance pouvant potentiellement être une police d'assurance médicale. De plus, la présente demande concerne également une technologie de chaîne de blocs, et des informations de police d'assurance peuvent être stockées sur un nœud d'une chaîne de blocs. La présente demande fournit également un appareil de distribution de services basé sur une analyse de données, un dispositif électronique et un support d'enregistrement. La présente demande peut améliorer la précision de recommandation de service médical.
PCT/CN2022/087811 2021-08-31 2022-04-20 Procédé et appareil de distribution de services basés sur une analyse de données, dispositif et support d'enregistrement WO2023029507A1 (fr)

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CN111274471A (zh) * 2018-12-04 2020-06-12 北京嘀嘀无限科技发展有限公司 信息推送方法、装置、服务器及可读存储介质
CN112581297A (zh) * 2020-12-18 2021-03-30 中国平安人寿保险股份有限公司 基于人工智能的信息推送方法、装置及计算机设备
CN113222668A (zh) * 2021-05-24 2021-08-06 中国平安财产保险股份有限公司 增值服务推送方法、装置、设备及存储介质
CN113706322A (zh) * 2021-08-31 2021-11-26 康键信息技术（深圳）有限公司 基于数据分析的服务分发方法、装置、设备及存储介质

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