WO2017050188A1 - 一种交易数据处理方法及装置 - Google Patents

一种交易数据处理方法及装置 Download PDF

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Publication number
WO2017050188A1
WO2017050188A1 PCT/CN2016/099224 CN2016099224W WO2017050188A1 WO 2017050188 A1 WO2017050188 A1 WO 2017050188A1 CN 2016099224 W CN2016099224 W CN 2016099224W WO 2017050188 A1 WO2017050188 A1 WO 2017050188A1
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Prior art keywords
transaction
user
determining
information
database node
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PCT/CN2016/099224
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English (en)
French (fr)
Inventor
王文柏
冯哲
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中国银联股份有限公司
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Publication of WO2017050188A1 publication Critical patent/WO2017050188A1/zh

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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
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising

Definitions

  • the present invention relates to the field of data processing technologies, and in particular, to a transaction data processing method and apparatus.
  • Some e-commerce platforms build consumer behavior models based on consumers' online search and consumer behavior consumers, and push corresponding product information for consumers.
  • the consumer behavior model based on the consumer's consumption line in the network does not reflect the true consumption behavior of the consumer.
  • Embodiments of the present invention provide a transaction data processing method and apparatus for implementing an accurate consumer behavior model.
  • the embodiment of the invention provides a transaction data processing method, including:
  • the historical transaction information includes a transaction amount, a transaction commodity type; determining an average value of the transaction amount of the user according to the transaction amount, and determining according to the average value of the transaction amount of the user and the type of the transaction commodity The average value of the user's weighted transaction amount, And determining, according to the average value of the weighted transaction amount, a consumption level of the user; determining, from the transaction commodity type of the user, a characteristic transaction commodity type of the user, where the characteristic transaction commodity type is a transaction corresponding to the transaction commodity type The number of times is greater than a threshold corresponding to the transaction commodity type, and the transaction commodity type belongs to a transaction commodity type preset in the consumption phase; determining, according to the characteristic transaction commodity type of the user, the consumption phase of the user; The consumption level and the consumption phase in which the user is located determine the item information that matches the user.
  • the obtaining the historical transaction information of the user includes: determining, in the distributed storage system, a database node storing the historical transaction information of the user; determining, according to the status identifier of the database node, the historical transaction storing the user a database node in an active state in the database node of the information; obtaining historical transaction information of the user through the database node in the active state.
  • the status identifier of the database node is determined by: sending a detection packet to the database node, and if the response packet of the database node is not received within a preset time period, determining that the database node is in a failed state And determining a status identifier of the database node as a failed state, otherwise determining a status identifier of the database node as an active state.
  • the method further includes: determining a database node that is the same as the data stored in the database node in the failed state and is in an active state; The data stored in the database node that is the same as the data stored in the database node in the failed state and is in an active state is backed up to other database nodes that are in an active state.
  • M represents the average value of the user's weighted transaction amount
  • D represents the average value of the transaction amount of the user
  • C e represents the weighted value of the transaction commodity type of the e-th transaction
  • e is greater than or equal to 1 and less than or equal to N
  • N represents the number of transactions
  • a ranking corresponding to the user's weighted transaction amount average is determined as the user's consumption level.
  • determining the product information that matches the user according to the consumption level of the user and the consumption phase of the user including: determining other users that are consistent with the user's consumption level; determining a transaction commodity type in the historical transaction information of the other user; in the transaction commodity type in the historical transaction information of the other user, determining a transaction commodity type that matches the consumption phase of the user, and The transaction commodity information corresponding to the transaction commodity type matched by the consumption phase of the user is determined as the commodity information matching the user.
  • determining the product information that matches the user according to the consumption level of the user and the consumption phase of the user including: acquiring the merchant attribute information of the merchant and historical transaction information of the merchant, where The merchant attribute information includes a transaction commodity type, and the historical transaction information of the merchant includes a transaction amount; the merchant whose transaction amount of the merchant is averaged within the same range, and the merchant has the same transaction commodity type as a merchant cluster; a merchant cluster that matches an average of the transaction amount of the merchant with the consumption level of the user, and the transaction commodity type of the merchant belongs to the consumption phase in which the user is located, and is determined to be a cluster of merchants that match the user; The item information corresponding to the merchant cluster matching the user is determined as the item information matching the user.
  • the method further includes: acquiring real-time transaction information of the user; determining, in a transaction commodity type corresponding to the commodity information matched by the user, a transaction commodity type that matches a transaction commodity type of the real-time transaction, and Transaction commodity information corresponding to the transaction commodity type matching the transaction commodity type of the real-time transaction is pushed to the user.
  • the embodiment of the invention provides a transaction data processing device, and the device includes:
  • An obtaining unit configured to acquire historical transaction information of the user, where the historical transaction information includes a transaction amount and a transaction commodity type;
  • a determining unit configured to determine an average value of the transaction amount of the user according to the transaction amount, and determine an average value of the weighted transaction amount of the user according to an average value of the transaction amount of the user and a transaction commodity type, and according to the weighting
  • the transaction amount average determines the user's consumption level; determines the user's characteristic transaction item type from the user's transaction item type, and the feature is paid
  • the easy commodity type is that the transaction number corresponding to the transaction commodity type is greater than a threshold corresponding to the transaction commodity type, and the transaction commodity type belongs to a transaction commodity type preset in the consumption phase; determining the user according to the characteristic transaction commodity type of the user The stage of consumption;
  • a matching unit configured to determine product information that matches the user according to the consumption level of the user and the consumption phase of the user.
  • the acquiring unit is specifically configured to: determine, in a distributed storage system, a database node that stores historical transaction information of the user; and determine, according to a status identifier of the database node, the database that stores historical transaction information of the user. a database node in an active state in the node; obtaining historical transaction information of the user through the database node in an active state.
  • the device further includes a detecting unit, where the detecting unit determines the status identifier of the database node by: sending a detection message to the database node, if the response message of the database node is not received within a preset time period And determining that the database node is in a failed state, and determining a status identifier of the database node as a failed state, otherwise determining a status identifier of the database node as an active state.
  • the device further includes a backup unit, wherein the backup unit is configured to:
  • the determining unit is specifically configured to: determine a weighted transaction amount average value of the user according to the following formula:
  • M represents the average value of the user's weighted transaction amount
  • D represents the average value of the transaction amount of the user
  • C e represents the weighted value of the transaction commodity type of the e-th transaction
  • e is greater than or equal to 1 and less than or equal to N
  • N represents the number of transactions
  • a ranking corresponding to the user's weighted transaction amount average is determined as the user's consumption level.
  • the matching unit is specifically configured to: determine other users that are consistent with the user's consumption level; determine a transaction product type in the historical transaction information of the other user; in the historical transaction information of the other user In the transaction commodity type, determining a transaction commodity type matching the consumption phase in which the user is located, and determining transaction commodity information corresponding to the transaction commodity type matching the consumption phase in which the user is located as Product information that matches the user.
  • the matching unit is specifically configured to: obtain the merchant attribute information of the merchant and historical transaction information of the merchant, where the merchant property information includes a transaction commodity type, and the historical transaction information of the merchant includes a transaction amount;
  • the average transaction amount is in the same range, and the merchants with the same transaction commodity type are divided into one merchant cluster; the average transaction amount of the merchant is matched with the consumption grade of the user, and the transaction commodity type of the merchant belongs to
  • the merchant cluster of the consumption stage in which the user is located is determined to be a cluster of merchants matching the user; and the commodity information corresponding to the merchant cluster matching the user is determined to be related to the user Matching product information.
  • the device further includes: a pushing unit; the pushing unit is specifically configured to: acquire real-time transaction information of the user; and determine, in the transaction product type corresponding to the product information matched by the user, the transaction with the real-time transaction The transaction item type whose item type matches, and the transaction item information corresponding to the transaction item type matching the transaction item type of the real-time transaction is pushed to the user.
  • a pushing unit is specifically configured to: acquire real-time transaction information of the user; and determine, in the transaction product type corresponding to the product information matched by the user, the transaction with the real-time transaction The transaction item type whose item type matches, and the transaction item information corresponding to the transaction item type matching the transaction item type of the real-time transaction is pushed to the user.
  • the embodiment of the invention provides a transaction data processing device, and the device includes:
  • a memory for storing programs and instructions
  • processor for executing by calling a program and an instruction stored in the memory:
  • the historical transaction information includes a transaction amount, a transaction commodity type; determining an average value of the transaction amount of the user according to the transaction amount, and determining according to the average value of the transaction amount of the user and the type of the transaction commodity An average value of the weighted transaction amount of the user, and determining a consumption level of the user according to the average value of the weighted transaction amount; determining a characteristic transaction commodity type of the user from a transaction commodity type of the user; The characteristic transaction commodity type determines a consumption phase in which the user is located; and determines product information that matches the user according to the consumption level of the user and the consumption phase in which the user is located;
  • the feature transaction commodity type is that the transaction number corresponding to the transaction commodity type is greater than a threshold corresponding to the transaction commodity type, and the transaction commodity type belongs to a transaction commodity type preset in the consumption phase.
  • the processor is specifically configured to: determine, in a distributed storage system, a database node that stores historical transaction information of the user; and determine, according to a status identifier of the database node, the historical transaction information that stores the user a database node in an active state in the database node; obtaining historical transaction information of the user through the database node in an active state.
  • the processor is further configured to determine a status identifier of the database node by:
  • the state identifier of the database node is determined to be an active state.
  • the processor is further configured to: determine a database node that is the same as the data stored in the database node in the failed state and is in an active state; and in the database node that is in the failed state The data stored in the database nodes with the same stored data and in the active state is backed up to other active database nodes.
  • the processor is specifically configured to determine an average value of the weighted transaction amount of the user according to the following formula:
  • M represents the average value of the user's weighted transaction amount
  • D represents the average value of the transaction amount of the user
  • C e represents the weighted value of the transaction commodity type of the e-th transaction
  • e is greater than or equal to 1 and less than or equal to N
  • N represents the number of transactions
  • a ranking corresponding to the user's weighted transaction amount average is determined as the user's consumption level.
  • the processor is specifically configured to: determine other users that are consistent with the user's consumption level; determine a transaction product type in the historical transaction information of the other user; and historical transaction information in the other user In the transaction commodity type, determine the consumption phase with the user Matching the transaction item type, and determining the transaction item information corresponding to the transaction item type matching the consumption stage in which the user is located as the item information matching the user.
  • the processor is specifically configured to: obtain merchant attribute information of the merchant and historical transaction information of the merchant, where the merchant attribute information includes a transaction commodity type, and the historical transaction information of the merchant includes a transaction amount;
  • the merchant's transaction amount average is in the same range, and the merchant's transaction commodity type is the same as the merchant cluster; the merchant's transaction amount average matches the user's consumption grade, and the merchant's transaction commodity type a cluster of merchants belonging to a consumption stage in which the user is located, determined as a cluster of merchants matching the user; determining product information corresponding to the cluster of merchants matching the user as the user Matching product information.
  • the processor is further configured to: acquire real-time transaction information of the user; and determine, in the transaction commodity type corresponding to the commodity information matched by the user, a transaction that matches a transaction commodity type of the real-time transaction.
  • the commodity type, and the transaction commodity information corresponding to the transaction commodity type matching the transaction commodity type of the real-time transaction is pushed to the user.
  • the embodiment of the present invention has the following beneficial effects: in the embodiment of the present invention, the user's offline transaction record is used to determine the user's transaction amount average value and the transaction commodity type, thereby determining the user's consumption level and consumption stage, and finally determining the user's consumption. Behavioral model. Since offline transaction records better reflect the true behavior of consumers, the resulting consumer behavior model is more accurate.
  • FIG. 1 is a schematic flowchart of a transaction data processing method according to an embodiment of the present invention
  • FIG. 2 is a schematic structural diagram of a transaction data processing apparatus according to an embodiment of the present invention.
  • FIG. 3 is a schematic structural diagram of a transaction data processing apparatus according to an embodiment of the present invention.
  • a schematic flowchart of a transaction data processing method according to an embodiment of the present invention includes:
  • Step 101 Acquire historical transaction information of the user, where the historical transaction information includes a transaction amount and a transaction commodity type;
  • Step 102 Determine an average value of the transaction amount of the user according to the transaction amount, and determine an average value of the weighted transaction amount of the user according to the average value of the transaction amount of the user and the type of the transaction commodity, and according to the weighted transaction amount.
  • the average value determines the consumption level of the user
  • Step 103 Determine a feature transaction commodity type of the user from a transaction commodity type of the user, where the feature transaction commodity type is that the transaction number corresponding to the transaction commodity type is greater than a threshold corresponding to the transaction commodity type, and the transaction commodity The type belongs to the type of transaction commodity preset in the consumption phase;
  • Step 104 Determine, according to the characteristic transaction commodity type of the user, a consumption phase in which the user is located;
  • Step 105 Determine product information that matches the user according to the consumption level of the user and the consumption stage of the user.
  • the type of the transaction commodity in the historical transaction information may specifically be a catering, clothing, home appliance, consumer electronics, etc., indicating the type of the commodity being traded, or indicating the transaction type.
  • the historical transaction information of the user may be stored in the distributed storage system.
  • Distributed storage systems distribute data across multiple independent database nodes.
  • the traditional network storage system uses a centralized database node to store all data.
  • the distributed network storage system adopts a scalable system structure, and utilizes multiple database nodes to share the storage load, which not only improves the reliability, availability, and access efficiency of the system. It is also easy to expand.
  • the distributed data storage system has the following features:
  • the data has more than 2 redundancy and can be configured as multi-point redundancy
  • the database node in the failed state can be automatically isolated
  • the data of the database node in the invalid state can be automatically backed up to other active database nodes;
  • Database nodes can be dynamically reduced in real time.
  • the database node in the failed state is marked, and the data stored in the database node in the failed state is determined to be the same and active.
  • a database node of the state backing up data stored in the database node that is the same as the data stored in the database node in the failed state and in an active state to other active database nodes.
  • the database node mainly includes two types of key information: location information and status identifier.
  • the location information may be composed of an IP (Internet Protocol) address and a port number indicating the location when the database node is accessed.
  • the status indicator indicates that the database node is active or invalid.
  • the IP address and port number of the database node are determined to determine the location of the database node, and the data is read from the determined database node.
  • the status identifier of the database node needs to be determined first, and the historical transaction information of the user is obtained through the database node whose status identifier is active in the distributed storage system.
  • a database node that stores historical transaction information of the user is determined in a distributed storage system; and a database node that is in an active state in a database node that stores historical transaction information of the user is determined according to a state identifier of the database node; The historical transaction information of the user is obtained by the database node in an active state.
  • the status identifier of the database node can be determined by:
  • the status identifier of the database node can also be determined by other detection methods, and details are not described herein again.
  • the database node After determining that the database node is in a failed state, it may also be necessary to back up the data in the database node of the failed state. Specifically, first determine a database node that is the same as the data stored in the database node in the failed state and is in an active state; and is the same as the data stored in the database node in the failed state, and is in an active state. The data stored in the database node is backed up to other active database nodes.
  • the average value of the transaction amount of the user may be determined according to the transaction amount in the historical transaction information of the user, and determined according to the average value of the transaction amount of the user and the type of the transaction commodity. The user's level of consumption.
  • the average value of the user's weighted transaction amount can be determined according to the following formula:
  • M represents the average value of the user's weighted transaction amount
  • D represents the average value of the transaction amount of the user
  • C e represents the weighted value of the transaction commodity type of the e-th transaction
  • e is greater than or equal to 1 and less than or equal to N
  • N represents the number of transactions.
  • weighted value of the transaction commodity type can be set according to the actual situation.
  • the weighted value of the traded item type is a number greater than zero. The larger the value of the transaction amount corresponding to the transaction type, the larger the weighting value of the transaction type.
  • the user's level of consumption is then determined by the level corresponding to the user's weighted transaction amount average.
  • the consumption level of all users ranked first 1% of the average value of the weighted transaction amounts of all the acquired users may be determined as a first level; the weighted transaction amount of all the users obtained is averaged
  • the consumption level of all users ranked in the top 1% of the value determines the first level; the consumption level of all users ranked between the top 3% and 1% of the average of the weighted transaction amounts of all the acquired users a second level; determining a third level of consumption levels of all users between the top 15% and 3% of the average of the weighted transaction amounts of all the acquired users; the weighting of all the users that will be located
  • the consumer level of all users between the top 47% and 15% of the transaction amount average determines the fourth level; will rank between the top 85% and 47% of the average of the weighted transaction amounts of all the acquired users.
  • the consumer level of all users determines the fifth level; the ranking will be between the top 94% and 85% of the average of the weighted transaction amounts of all the acquired users.
  • the user's level of consumption determines a sixth level; the level of consumption for all users ranked the last 6% of the average of the weighted transaction amounts of all of the acquired users is determined to be a seventh level.
  • a seventh level there may be other types of users' weighted transaction amount average rankings and consumption levels, and will not be described here.
  • the user's consumption level After determining the average value of a user's weighted transaction amount, the user's consumption level can be determined according to the above mapping relationship.
  • the user's level of consumption can indicate the user's spending power or indicate the user's social class.
  • the user's consumption phase can be determined by the user's historical transaction record.
  • trading commodity types There are a variety of trading commodity types that can be preset in the consumption phase.
  • the user's consumption stage can be divided into the following stages: single stage, marriage stage, new marriage stage, baby stage, child care stage, and unstaged stage (unstaged means that the child has become adult, But not yet married), empty nest stage, widowed stage.
  • the default types of traded goods are mainly food, books, movies, etc.
  • the default types of traded goods are mainly high-end fashion, wedding supplies and other items; during the wedding stage, the default types of traded goods are mainly entertainment, tourism and other items;
  • the types of traded goods are mainly milk powder, diaper and other items; in the parenting stage, the default types of traded goods are mainly education expenditures; when not in stages, the default types of traded goods are mainly social items and other items;
  • the default trading commodity type is mainly health care products and other items; when the widowed stage, the default trading commodity type is mainly medical and other items.
  • step 104 according to different characteristics of different stages of life, it is possible to determine the type of transaction products that the user will have different preferences at different stages of life.
  • the user frequently purchases baby products such as milk powder and diaper, it can be determined that the user's characteristic transaction commodity type is a childcare product, thereby determining that the consumption phase of the user is the nursery stage.
  • step 105 the product information matched by the user is determined according to the user's consumption level and the consumption stage, and the product information is pushed for the user when needed.
  • One possible implementation of determining the product information that the user matches is:
  • the transaction commodity type in the historical transaction information of the other users determining a transaction commodity type that matches the consumption phase in which the user is located, and matching the transaction commodity type with the consumption phase in which the user is located
  • the corresponding transaction item information is determined as the item information that matches the user.
  • user A and user B belong to the same consumption level, and user A likes to go to the first brand of Sichuan cuisine, and user B likes to go to the second brand of Sichuan cuisine.
  • the product information of the second restaurant of the second brand that the user B likes can be matched with the user A.
  • the product information of the Sichuan brand of the second brand that the user A likes can be matched with the user B.
  • the product information of the second brand of the Sichuan restaurant can be pushed to the user A, thereby achieving accurate marketing.
  • Another possible implementation for determining the product information that the user matches is:
  • the merchants whose transaction amount averages are within the same range and the merchants have the same transaction product type are classified into one merchant cluster;
  • a merchant cluster that matches an average of the transaction amount of the merchant with the consumption level of the user, and the transaction commodity type of the merchant belongs to the consumption phase in which the user is located, and is determined to be a cluster of merchants that match the user;
  • the item information corresponding to the merchant cluster matching the user is determined as the item information matching the user.
  • the user A belongs to the third consumption level, and the user A is in the single-stage phase, and the merchants corresponding to the user A can be clustered at this time.
  • user A purchases a high-end mobile phone user A can push a high-end digital camera that belongs to the same merchant cluster as the high-end mobile phone, thereby achieving accurate marketing.
  • the user can push the product information that matches the type of the transaction commodity that the user is trading in real time.
  • the transaction item information pushed to the user may be printed on the user's bill or in the electronic ticket at the time of the user's transaction, thereby obtaining the user's attention.
  • an embodiment of the present invention further provides a transaction data processing apparatus, which can perform the foregoing method embodiments.
  • the device provided by the embodiment of the invention is shown in FIG. 2 .
  • a transaction data processing apparatus includes:
  • the obtaining unit 201 is configured to acquire historical transaction information of the user, where the historical transaction information includes a transaction amount and a transaction commodity type, and the determining unit 202 is configured to determine an average value of the transaction amount of the user according to the transaction amount, and Determining an average value of the transaction amount of the user and a transaction commodity type determining an average value of the weighted transaction amount of the user, and determining a consumption level of the user according to the average value of the weighted transaction amount; determining the location from the transaction commodity type of the user a feature transaction commodity type of the user, the feature transaction commodity type is that the transaction number corresponding to the transaction commodity type is greater than a threshold corresponding to the transaction commodity type, and the transaction commodity type belongs to a transaction commodity type preset in the consumption phase; Determining the consumption stage of the user, the matching unit 203 is configured to determine the product information that matches the user according to the consumption level of the user and the consumption stage of the user. .
  • the obtaining unit 201 is specifically configured to: determine, in the distributed storage system, a database node that stores historical transaction information of the user;
  • the device further includes a detecting unit 204, where the detecting unit 204 determines a status identifier of the database node by sending a detection message to the database node, if the database node is not received within a preset time period. And responding to the message, determining that the database node is in a failed state, and determining a status identifier of the database node as a failed state; otherwise determining a status identifier of the database node as an active state.
  • the detecting unit 204 determines a status identifier of the database node by sending a detection message to the database node, if the database node is not received within a preset time period. And responding to the message, determining that the database node is in a failed state, and determining a status identifier of the database node as a failed state; otherwise determining a status identifier of the database node as an active state.
  • the device further includes a backup unit 205, configured to: determine a database that is the same as the data stored in the database node in the failed state and is in an active state a node; backing up data stored in the database node that is the same as the data stored in the database node in the failed state and in an active state to other active database nodes.
  • a backup unit 205 configured to: determine a database that is the same as the data stored in the database node in the failed state and is in an active state a node; backing up data stored in the database node that is the same as the data stored in the database node in the failed state and in an active state to other active database nodes.
  • the determining unit 202 is specifically configured to determine an average value of the weighted transaction amount of the user according to the following formula:
  • M represents the average value of the user's weighted transaction amount
  • D represents the average value of the transaction amount of the user
  • C e represents the weighted value of the transaction commodity type of the e-th transaction
  • e is greater than or equal to 1 and less than or equal to N
  • N represents the number of transactions
  • a ranking corresponding to the user's weighted transaction amount average is determined as the user's consumption level.
  • the matching unit 203 is specifically configured to: determine other users consistent with the user's consumption level; determine a transaction commodity type in the historical transaction information of the other users; and historical transaction information in the other user In the transaction commodity type, determining a transaction commodity type that matches the consumption phase in which the user is located, and determining the transaction commodity information corresponding to the transaction commodity type that matches the consumption phase of the user as the The product information that the user matches.
  • the matching unit 203 is specifically configured to: obtain merchant attribute information of the merchant and historical transaction information of the merchant, where the merchant attribute information includes a transaction commodity type, and the historical transaction information of the merchant includes a transaction amount;
  • the merchant's transaction amount average is in the same range, and the merchant's transaction commodity type is the same as the merchant cluster; the merchant's transaction amount average matches the user's consumption grade, and the merchant's transaction commodity type a cluster of merchants belonging to a consumption stage in which the user is located, determined as a cluster of merchants matching the user; determining product information corresponding to the cluster of merchants matching the user as the user Matching product information.
  • the device further includes: a pushing unit; the pushing unit 206 is specifically configured to: acquire real-time transaction information of the user; and determine, in the transaction commodity type corresponding to the product information matched by the user, the real-time transaction Transaction commodity type matching the transaction commodity type, and pushing the transaction commodity information corresponding to the transaction commodity type matching the transaction commodity type of the real-time transaction User.
  • a pushing unit the pushing unit 206 is specifically configured to: acquire real-time transaction information of the user; and determine, in the transaction commodity type corresponding to the product information matched by the user, the real-time transaction Transaction commodity type matching the transaction commodity type, and pushing the transaction commodity information corresponding to the transaction commodity type matching the transaction commodity type of the real-time transaction User.
  • the user's offline transaction record is used to determine the user's transaction amount average value and the transaction product type, thereby determining the user's consumption level and the consumption stage, and finally determining the user's consumption behavior model. Since offline transaction records better reflect the true behavior of consumers, the resulting consumer behavior model is more accurate.
  • an embodiment of the present invention further provides a transaction data processing apparatus, which can perform the foregoing method embodiments.
  • the device provided by the embodiment of the invention is shown in FIG.
  • a transaction data processing apparatus includes a memory 301 and a processor 302 and a bus 303:
  • the bus 303 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus.
  • PCI peripheral component interconnect
  • EISA extended industry standard architecture
  • the bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, only one thick line is shown in Figure 3, but it does not mean that there is only one bus or one type of bus.
  • the memory 301 may include a volatile memory such as a random-access memory (RAM); the memory may also include a non-volatile memory such as a flash memory (flash) A hard disk drive (HDD) or a solid-state drive (SSD); the memory 301 may also include a combination of the above types of memories.
  • RAM random-access memory
  • flash non-volatile memory
  • HDD hard disk drive
  • SSD solid-state drive
  • the processor 302 can be a central processing unit (CPU), a network processor (NP) or a combination of a CPU and an NP.
  • CPU central processing unit
  • NP network processor
  • Processor 302 can also further include a hardware chip.
  • the hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD) or a combination thereof.
  • ASIC application-specific integrated circuit
  • PLD programmable logic device
  • the above PLD can be a complex programmable logic device (CPLD), which can be edited on site.
  • CPLD complex programmable logic device
  • FPGA field-programmable gate array
  • GAL general array logic
  • a memory 301 configured to store programs and instructions
  • the processor 302 is configured to execute by calling a program and an instruction stored in the memory:
  • the historical transaction information includes a transaction amount, a transaction commodity type; determining an average value of the transaction amount of the user according to the transaction amount, and determining according to the average value of the transaction amount of the user and the type of the transaction commodity An average value of the weighted transaction amount of the user, and determining a consumption level of the user according to the average value of the weighted transaction amount; determining a characteristic transaction commodity type of the user from a transaction commodity type of the user; The characteristic transaction commodity type determines a consumption phase in which the user is located; and determines product information that matches the user according to the consumption level of the user and the consumption phase in which the user is located;
  • the feature transaction commodity type is that the transaction number corresponding to the transaction commodity type is greater than a threshold corresponding to the transaction commodity type, and the transaction commodity type belongs to a transaction commodity type preset in the consumption phase.
  • the processor 302 is specifically configured to: determine, in a distributed storage system, a database node that stores historical transaction information of the user; and determine, according to a status identifier of the database node, the historical transaction information that stores the user.
  • the processor 302 is further configured to determine a status identifier of the database node by:
  • the state identifier of the database node is determined to be an active state.
  • the processor 302 is further configured to: determine a database node that is the same as the data stored in the database node in the failed state, and is in an active state; and the database node that is in the failed state Stored in the same database and in an active database node The stored data is backed up to other active database nodes.
  • the processor 302 is specifically configured to determine an average value of the weighted transaction amount of the user according to the following formula:
  • M represents the average value of the user's weighted transaction amount
  • D represents the average value of the transaction amount of the user
  • C e represents the weighted value of the transaction commodity type of the e-th transaction
  • e is greater than or equal to 1 and less than or equal to N
  • N represents the number of transactions
  • a ranking corresponding to the user's weighted transaction amount average is determined as the user's consumption level.
  • the processor 302 is specifically configured to: determine other users that are consistent with the user's consumption level; determine a transaction commodity type in the historical transaction information of the other users; and perform historical transactions in the other users.
  • determine the transaction commodity type in the information determining the transaction commodity type that matches the consumption phase in which the user is located, and determining the transaction commodity information corresponding to the transaction commodity type matching the consumption phase of the user as The product information matched by the user.
  • the processor 302 is configured to: obtain the merchant attribute information of the merchant and the historical transaction information of the merchant, where the merchant property information includes a transaction commodity type, and the historical transaction information of the merchant includes a transaction amount;
  • the merchants whose transaction amount average value is within the same range and the merchant's transaction commodity type is the same are divided into one merchant cluster; the merchant transaction amount average value is matched with the user's consumption grade, and the merchant's transaction commodity is a merchant cluster of a type belonging to a consumption stage in which the user is located, determined as a merchant cluster matching the user; determining, by the commodity information corresponding to the merchant cluster that matches the user, Product information that matches the user.
  • the processor 302 is further configured to: acquire real-time transaction information of the user; and determine, in a transaction commodity type corresponding to the commodity information matched by the user, a transaction commodity type that matches the real-time transaction.
  • Transaction commodity type, and the transaction commodity information corresponding to the transaction commodity type matching the transaction commodity type of the real-time transaction is pushed to the user.
  • the user's offline transaction record is used to determine the average value of the transaction amount of the user and the type of the transaction commodity, thereby determining the user's consumption level and the consumption stage, and finally determining the use.
  • Household consumption behavior model Since offline transaction records better reflect the true behavior of consumers, the resulting consumer behavior model is more accurate.
  • the present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (system), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or FIG.
  • the computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine instruction for generating instructions executed by a processor of a computer or other programmable data processing device Means for implementing the functions specified in one or more flows of the flowchart or in a block or blocks of the flowchart.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

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Abstract

一种交易数据处理方法及装置，包括：获取用户的历史交易信息，所述历史交易信息包括交易金额、交易商品类型；根据所述交易金额确定所述用户的交易金额平均值，并根据所述用户的交易金额平均值以及交易商品类型确定所述用户的加权交易金额平均值，并根据加权交易金额平均值确定所述用户的消费等级；从用户的交易商品类型中确定所述用户的特征交易商品类型，特征交易商品类型为该交易商品类型对应的交易次数大于该交易商品类型对应的阈值且该交易商品类型属于消费阶段中预设的交易商品类型；根据用户的特征交易商品类型确定用户所处的消费阶段；根据用户的消费等级和所述用户所处的消费阶段，确定与用户相匹配的商品信息。

Description

一种交易数据处理方法及装置
本申请要求在2015年09月24日提交中国专利局、申请号为201510617766.9、发明名称为“一种交易数据处理方法及装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本发明涉及数据处理技术领域，尤其涉及一种交易数据处理方法及装置。
背景技术
随着网络支付业务的安全性越来越高，越来越多的消费行为是通过网络完成的。一些电商平台便根据消费者的网络搜索以及消费行为消费者建立消费行为模型，并为消费者推送相应的商品信息。
但是，由于网络环境的局限性，有些商品消费者并不会在网络中购买，例如，汽车，同时，消费者的消费账号可以被多个人同时使用。因此，基于消费者在网络中的消费行建立的消费行为模型为并不能体现消费者的真正的消费行为。
因此，根据消费者在网络中的消费行建立的消费模型去推送商品信息的效果不是很好。
发明内容
本发明实施例提供一种交易数据处理方法及装置，用以实现建立准确的消费行为模型。
本发明实施例提供一种交易数据处理方法，包括：
获取用户的历史交易信息，所述历史交易信息包括交易金额、交易商品类型；根据所述交易金额确定所述用户的交易金额平均值，并根据所述用户的交易金额平均值以及交易商品类型确定所述用户的加权交易金额平均值， 并根据所述加权交易金额平均值确定所述用户的消费等级；从所述用户的交易商品类型中确定所述用户的特征交易商品类型，所述特征交易商品类型为该交易商品类型对应的交易次数大于该交易商品类型对应的阈值、且该交易商品类型属于消费阶段中预设的交易商品类型；根据所述用户的特征交易商品类型确定所述用户所处的消费阶段；根据所述用户的消费等级和所述用户所处的消费阶段，确定与所述用户相匹配的商品信息。
可选地，所述获取用户的历史交易信息，包括：在分布式存储系统中确定存储所述用户的历史交易信息的数据库节点；根据数据库节点的状态标识确定所述存储所述用户的历史交易信息的数据库节点中处于活跃状态的数据库节点；通过所述处于活跃状态的数据库节点获取所述用户的历史交易信息。
可选地，通过以下方式确定数据库节点的状态标识：向数据库节点发送检测报文，若在预设时间段内未接收到所述数据库节点的响应报文，则确定所述数据库节点处于失效状态，并将所述数据库节点的状态标识确定为失效状态，否则将所述数据库节点的状态标识确定为活跃状态。
可选地，所述将所述数据库节点的状态标识确定为失效状态之后，还包括：确定与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点；对所述与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点中存储的数据备份至其他处于活跃状态的数据库节点。
可选地，所述根据所述交易金额确定所述用户的交易金额平均值，并根据所述用户的交易金额平均值以及交易商品类型确定所述用户的加权交易金额平均值，并根据所述加权交易金额平均值确定所述用户的消费等级，包括：根据以下公式确定用户的加权交易金额平均值：
Figure PCTCN2016099224-appb-000001
其中，M表示用户的加权交易金额平均值，D表示用户的交易金额平均值，Ce表示第e次交易的交易商品类型的加权值，e大于等于1且小于等于N， N表示交易次数；将所述用户的加权交易金额平均值对应的等级确定所述用户的消费等级。
可选地，所述根据所述用户的消费等级和所述用户所处的消费阶段，确定与所述用户相匹配的商品信息，包括：确定与所述用户的消费等级一致的其他用户；确定所述其他用户的历史交易信息中的交易商品类型；在所述其他用户的历史交易信息中的交易商品类型中，确定与所述用户所处的消费阶段相匹配的交易商品类型，并将与所述用户所处的消费阶段相匹配的交易商品类型对应的交易商品信息确定为与所述用户相匹配的商品信息。
可选地，所述根据所述用户的消费等级和所述用户所处的消费阶段，确定与所述用户相匹配的商品信息，包括：获取商家的商家属性信息以及商家的历史交易信息，所述商家属性信息中包括交易商品类型，所述商家的历史交易信息中包括交易金额；将商家的交易金额平均值在同一范围内、且商家的交易商品类型相同的商家划分为一个商家聚类；将商家的交易金额平均值与所述用户的消费等级相匹配、且商家的交易商品类型属于所述用户所处的消费阶段的商家聚类，确定为与所述用户相匹配的商家聚类；将所述与所述用户相匹配的商家聚类对应的商品信息确定为与所述用户相匹配的商品信息。
可选地，该方法还包括：获取用户的实时交易信息；在所述用户相匹配的商品信息对应的交易商品类型中，确定与所述实时交易的交易商品类型相匹配的交易商品类型，并将与所述实时交易的交易商品类型相匹配的交易商品类型对应的交易商品信息推送给所述用户。
本发明实施例提供一种交易数据处理装置，该装置包括：
获取单元，用于获取用户的历史交易信息，所述历史交易信息包括交易金额、交易商品类型；
确定单元，用于根据所述交易金额确定所述用户的交易金额平均值，并根据所述用户的交易金额平均值以及交易商品类型确定所述用户的加权交易金额平均值，并根据所述加权交易金额平均值确定所述用户的消费等级；从所述用户的交易商品类型中确定所述用户的特征交易商品类型，所述特征交 易商品类型为该交易商品类型对应的交易次数大于该交易商品类型对应的阈值、且该交易商品类型属于消费阶段中预设的交易商品类型；根据所述用户的特征交易商品类型确定所述用户所处的消费阶段；
匹配单元，用于根据所述用户的消费等级和所述用户所处的消费阶段，确定与所述用户相匹配的商品信息。
可选地，所述获取单元具体用于：在分布式存储系统中确定存储所述用户的历史交易信息的数据库节点；根据数据库节点的状态标识确定所述存储所述用户的历史交易信息的数据库节点中处于活跃状态的数据库节点；通过所述处于活跃状态的数据库节点获取所述用户的历史交易信息。
可选地，该装置还包括检测单元，所述检测单元通过以下方式确定数据库节点的状态标识：向数据库节点发送检测报文，若在预设时间段内未接收到所述数据库节点的响应报文，则确定所述数据库节点处于失效状态，并将所述数据库节点的状态标识确定为失效状态，否则将所述数据库节点的状态标识确定为活跃状态。
可选地，该装置还包括备份单元，所述备份单元用于：
确定与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点；
对所述与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点中存储的数据备份至其他处于活跃状态的数据库节点。
可选地，所述确定单元具体用于：根据以下公式确定用户的加权交易金额平均值：
Figure PCTCN2016099224-appb-000002
其中，M表示用户的加权交易金额平均值，D表示用户的交易金额平均值，Ce表示第e次交易的交易商品类型的加权值，e大于等于1且小于等于N，N表示交易次数；将所述用户的加权交易金额平均值对应的等级确定所述用户的消费等级。
可选地，所述匹配单元具体用于：确定与所述用户的消费等级一致的其他用户；确定所述其他用户的历史交易信息中的交易商品类型；在所述其他用户的历史交易信息中的交易商品类型中，确定与所述用户所处的消费阶段相匹配的交易商品类型，并将与所述用户所处的消费阶段相匹配的交易商品类型对应的交易商品信息确定为与所述用户相匹配的商品信息。
可选地，所述匹配单元具体用于：获取商家的商家属性信息以及商家的历史交易信息，所述商家属性信息中包括交易商品类型，所述商家的历史交易信息中包括交易金额；将商家的交易金额平均值在同一范围内、且商家的交易商品类型相同的商家划分为一个商家聚类；将商家的交易金额平均值与所述用户的消费等级相匹配、且商家的交易商品类型属于所述用户所处的消费阶段的商家聚类，确定为与所述用户相匹配的商家聚类；将所述与所述用户相匹配的商家聚类对应的商品信息确定为与所述用户相匹配的商品信息。
可选地，该装置还包括推送单元；所述推送单元具体用于：获取用户的实时交易信息；在所述用户相匹配的商品信息对应的交易商品类型中，确定与所述实时交易的交易商品类型相匹配的交易商品类型，并将与所述实时交易的交易商品类型相匹配的交易商品类型对应的交易商品信息推送给所述用户。
本发明实施例提供一种交易数据处理装置，该装置包括：
存储器，用于存储程序和指令；
处理器，用于通过调用所述存储器中存储的程序和指令，执行：
获取用户的历史交易信息，所述历史交易信息包括交易金额、交易商品类型；根据所述交易金额确定所述用户的交易金额平均值，并根据所述用户的交易金额平均值以及交易商品类型确定所述用户的加权交易金额平均值，并根据所述加权交易金额平均值确定所述用户的消费等级；从所述用户的交易商品类型中确定所述用户的特征交易商品类型；根据所述用户的特征交易商品类型确定所述用户所处的消费阶段；根据所述用户的消费等级和所述用户所处的消费阶段，确定与所述用户相匹配的商品信息；
其中，所述特征交易商品类型为该交易商品类型对应的交易次数大于该交易商品类型对应的阈值、且该交易商品类型属于消费阶段中预设的交易商品类型。
可选地，所述处理器，具体用于：在分布式存储系统中确定存储所述用户的历史交易信息的数据库节点；根据数据库节点的状态标识确定所述存储所述用户的历史交易信息的数据库节点中处于活跃状态的数据库节点；通过所述处于活跃状态的数据库节点获取所述用户的历史交易信息。
可选地，所述处理器，还用于通过以下方式确定数据库节点的状态标识：
向数据库节点发送检测报文，若在预设时间段内未接收到所述数据库节点的响应报文，则确定所述数据库节点处于失效状态，并将所述数据库节点的状态标识确定为失效状态，否则将所述数据库节点的状态标识确定为活跃状态。
可选地，所述处理器，还用于：确定与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点；对所述与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点中存储的数据备份至其他处于活跃状态的数据库节点。
可选地，所述处理器，具体用于：根据以下公式确定用户的加权交易金额平均值：
Figure PCTCN2016099224-appb-000003
其中，M表示用户的加权交易金额平均值，D表示用户的交易金额平均值，Ce表示第e次交易的交易商品类型的加权值，e大于等于1且小于等于N，N表示交易次数；将所述用户的加权交易金额平均值对应的等级确定所述用户的消费等级。
可选地，所述处理器，具体用于：确定与所述用户的消费等级一致的其他用户；确定所述其他用户的历史交易信息中的交易商品类型；在所述其他用户的历史交易信息中的交易商品类型中，确定与所述用户所处的消费阶段 相匹配的交易商品类型，并将与所述用户所处的消费阶段相匹配的交易商品类型对应的交易商品信息确定为与所述用户相匹配的商品信息。
可选地，所述处理器，具体用于：获取商家的商家属性信息以及商家的历史交易信息，所述商家属性信息中包括交易商品类型，所述商家的历史交易信息中包括交易金额；将商家的交易金额平均值在同一范围内、且商家的交易商品类型相同的商家划分为一个商家聚类；将商家的交易金额平均值与所述用户的消费等级相匹配、且商家的交易商品类型属于所述用户所处的消费阶段的商家聚类，确定为与所述用户相匹配的商家聚类；将所述与所述用户相匹配的商家聚类对应的商品信息确定为与所述用户相匹配的商品信息。
可选地，所述处理器，还用于：获取用户的实时交易信息；在所述用户相匹配的商品信息对应的交易商品类型中，确定与所述实时交易的交易商品类型相匹配的交易商品类型，并将与所述实时交易的交易商品类型相匹配的交易商品类型对应的交易商品信息推送给所述用户。
本发明实施例具有如下有益效果：本发明实施例中，是通过用户的线下交易记录确定用户的交易金额平均值以及交易商品类型，从而确定用户的消费等级以及消费阶段，最终确定用户的消费行为模型。由于线下交易记录更能反映消费者的真实行为，因此获得的消费行为模型更加准确。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简要介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域的普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1为本发明实施例提供的一种交易数据处理方法流程示意图；
图2为本发明实施例提供的一种交易数据处理装置结构示意图；
图3为本发明实施例提供的一种交易数据处理装置结构示意图。
具体实施方式
为了使本发明的目的、技术方案和优点更加清楚，下面将结合附图对本发明作进一步地详细描述，显然，所描述的实施例仅仅是本发明一部份实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其它实施例，都属于本发明保护的范围。
如图1所示，本发明实施例提供的一种交易数据处理方法流程示意图，该方法包括：
步骤101：获取用户的历史交易信息，所述历史交易信息包括交易金额、交易商品类型；
步骤102：根据所述交易金额确定所述用户的交易金额平均值，并根据所述用户的交易金额平均值以及交易商品类型确定所述用户的加权交易金额平均值，并根据所述加权交易金额平均值确定所述用户的消费等级；
步骤103：从所述用户的交易商品类型中确定所述用户的特征交易商品类型，所述特征交易商品类型为该交易商品类型对应的交易次数大于该交易商品类型对应的阈值、且该交易商品类型属于消费阶段中预设的交易商品类型；
步骤104：根据所述用户的特征交易商品类型确定所述用户所处的消费阶段；
步骤105：根据所述用户的消费等级和所述用户所处的消费阶段，确定与所述用户相匹配的商品信息。
步骤101中，历史交易信息中的交易商品类型具体可以为餐饮、服饰、家电、消费电子等，指示出交易的商品的类型，或者指示出交易类型。
本发明实施例中，用户的历史交易信息可以存储于分布式存储系统中。分布式存储系统，是将数据分散存储在多台独立的数据库节点上。传统的网络存储系统采用集中的数据库节点存放所有数据，分布式网络存储系统采用可扩展的系统结构，利用多台数据库节点分担存储负荷，它不但提高了系统的可靠性、可用性和存取效率，还易于扩展。
本发明实施例中，分布式数据存储系统有如下特征：
数据具有2份以上的冗余度，可配置成多分冗余；
当数据库节点失效时，可以自动隔离处于失效状态的数据库节点；
当数据库节点实效时，可以自动备份处于失效状态的数据库节点的数据至其他活跃的数据库节点；
可以动态实时增加数据库节点；
可以动态实时减少数据库节点。
为了能够快速的指示出数据库节点的状态标识，本发明实施例中，对所述处于失效状态的数据库节点进行标记，并确定与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点；对所述与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点中存储的数据备份至其他处于活跃状态的数据库节点。
综上所述，本发明实施例中，数据库节点主要包含两类关键信息：位置信息和状态标识。位置信息可以由IP(网络间互连的协议，Internet Protocol)地址和端口(port)号构成，指示出访问该数据库节点时的位置。状态标识表示出数据库节点为活跃状态或者失效状态。
举例来说，当需要读取数据时，确定了数据库节点的IP地址和端口号就可以确定数据库节点的位置，并从确定出的数据库节点中读取数据。
在获取用户的历史交易信息时，需要先确定数据库节点的状态标识，并通过分布式存储系统中状态标识为活跃状态的数据库节点获取用户的历史交易信息。具体的，在分布式存储系统中确定存储所述用户的历史交易信息的数据库节点；根据数据库节点的状态标识确定所述存储所述用户的历史交易信息的数据库节点中处于活跃状态的数据库节点；通过所述处于活跃状态的数据库节点获取所述用户的历史交易信息。
其中，可以通过以下方式确定数据库节点的状态标识：
向数据库节点发送检测报文，若在预设时间段内未接收到所述数据库节点的响应报文，则确定所述数据库节点处于失效状态，并将所述数据库节点 的状态标识确定为失效状态，否则将所述数据库节点的状态标识确定为活跃状态。
当然，还可以通过其他检测方法确定数据库节点的状态标识，在此不再赘述。
当确定数据库节点为失效状态之后，还可能需要对该失效状态的数据库节点中的数据进行备份。具体的，先确定与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点；对所述与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点中存储的数据备份至其他处于活跃状态的数据库节点。
步骤102中，获取所述用户的历史交易信息之后，可以根据用户的历史交易信息中的交易金额确定所述用户的交易金额平均值，并根据所述用户的交易金额平均值以及交易商品类型确定所述用户的消费等级。
根据所述交易金额确定所述用户的交易金额平均值，并根据所述用户的交易金额平均值以及交易商品类型确定所述用户的加权交易金额平均值，并根据所述加权交易金额平均值确定所述用户的消费等级
具体的，可以根据以下公式确定用户的加权交易金额平均值：
Figure PCTCN2016099224-appb-000004
其中，M表示用户的加权交易金额平均值，D表示用户的交易金额平均值，Ce表示第e次交易的交易商品类型的加权值，e大于等于1且小于等于N，N表示交易次数。
需要说明的是，交易商品类型的加权值可以根据实际情况去设置。交易商品类型的加权值为大于0的数。交易类型对应的交易金额的值越大，该交易类型的加权值可以越大。
然后将所述用户的加权交易金额平均值对应的等级确定所述用户的消费等级。
具体的，确定所有获取到的用户的历史交易记录，并确定所有获取到的 用户的加权交易金额平均值；
针对一个用户，确定该用户的加权交易金额平均值位于所述所有获取到的用户的加权交易金额平均值中的排名，根据该用户的加权交易金额平均值的排名与消费等级的映射关系，确定所述用户的消费等级。
举例来说，可以将位于所述所有获取到的用户的加权交易金额平均值中排名前1％的所有用户的消费等级确定第一等级；将位于所述所有获取到的用户的加权交易金额平均值中排名前1％的所有用户的消费等级确定第一等级；将位于所述所有获取到的用户的加权交易金额平均值中排名前3％至1％之间的所有用户的消费等级确定第二等级；将位于所述所有获取到的用户的加权交易金额平均值中排名前15％至3％之间的所有用户的消费等级确定第三等级；将位于所述所有获取到的用户的加权交易金额平均值中排名前47％至15％之间的所有用户的消费等级确定第四等级；将位于所述所有获取到的用户的加权交易金额平均值中排名前85％至47％之间的所有用户的消费等级确定第五等级；将位于所述所有获取到的用户的加权交易金额平均值中排名前94％至85％之间的所有用户的消费等级确定第六等级；将位于所述所有获取到的用户的加权交易金额平均值中排名最后6％的所有用户的消费等级确定第七等级。当然，也可以有其他形式的用户的加权交易金额平均值的排名与消费等级的映射关系，在此不再赘述。
当确定一个用户的加权交易金额平均值排名后，就可以根据上面的映射关系确定用户的消费等级。
用户的消费等级可以表明用户的消费能力，或者表明用户的社会阶层。
同时，在步骤103中，可以通过用户的历史交易记录确定用户的消费阶段。消费阶段中预设的交易商品类型可以有多种。
举例来说，可以将用户的消费阶段划分为以下几个阶段：单身阶段、备婚阶段、新婚阶段、育婴阶段、育儿阶段、未分阶段(未分阶段是指：抚育的孩子已经成年，但还未结婚)、空巢阶段、鰥寡阶段。
其中，单身阶段时，预设的交易商品类型主要为食品、书籍、电影等娱 乐项目；备婚阶段时，预设的交易商品类型主要为高级时装、结婚用品等项目；新婚阶段时，预设的交易商品类型主要为娱乐、旅游等项目；育婴阶段时，预设的交易商品类型主要为奶粉、尿不湿等项目；育儿阶段时，预设的交易商品类型主要为教育支出等项目；未分阶段时，预设的交易商品类型主要为社交用品等项目；空巢阶段时，预设的交易商品类型主要是保健品等项目；鰥寡阶段时，预设的交易商品类型主要为医疗等项目。
步骤104中，可以根据人生不同阶段的不同的特点，确定用户会在不同人生阶段有着不同偏好的交易商品类型。
举例来说，若用户经常购买奶粉以及尿不湿等婴儿用品，可以确定用户的特征交易商品类型为育儿产品，从而确定所述用户所处的消费阶段为育婴阶段。
最后在步骤105中，根据用户的消费等级以及消费阶段确定用户匹配的商品信息，并在需要时为用户推送这些商品信息。
确定用户匹配的商品信息的一种可能的实现方式为：
确定与所述用户的消费等级一致的其他用户；
确定所述其他用户的历史交易信息中的交易商品类型；
在所述其他用户的历史交易信息中的交易商品类型中，确定与所述用户所处的消费阶段相匹配的交易商品类型，并将与所述用户所处的消费阶段相匹配的交易商品类型对应的交易商品信息确定为与所述用户相匹配的商品信息。
举例来说，用户A和用户B属于同一消费等级，且用户A喜欢去第一品牌的川菜馆消费，用户B喜欢去第二品牌的川菜馆消费。此时，可以将用户B喜欢的第二品牌的川菜馆的商品信息与用户A进行匹配。相应的，也可以将用户A喜欢的第二品牌的川菜馆的商品信息与用户B进行匹配。当用户A在第一品牌的川菜馆消费时，可以将第二品牌的川菜馆的商品信息推送给用户A，从而实现精准营销。
确定用户匹配的商品信息的另一种可能的实现方式为：
获取商家的商家属性信息以及商家的历史交易信息，所述商家属性信息中包括交易商品类型，所述商家的历史交易信息中包括交易金额；
将商家的交易金额平均值在同一范围内、且商家的交易商品类型相同的商家划分为一个商家聚类；
将商家的交易金额平均值与所述用户的消费等级相匹配、且商家的交易商品类型属于所述用户所处的消费阶段的商家聚类，确定为与所述用户相匹配的商家聚类；
将所述与所述用户相匹配的商家聚类对应的商品信息确定为与所述用户相匹配的商品信息。
举例来说，用户A属于第三消费等级，且用户A处于单身阶段，此时可以将与用户A匹配对应的商家聚类。当用户A购买某高档手机时，可以为用户A推送与该高档手机属于同一个商家聚类的高档数码相机，从而实现精准营销。
最后，在用户实时交易时，可以为用户推送与用户实时交易的交易商品类型相匹配的商品信息。
具体的，获取用户的实时交易信息；
在所述用户相匹配的商品信息对应的交易商品类型中，确定与所述实时交易的交易商品类型相匹配的交易商品类型，并将与所述实时交易的交易商品类型相匹配的交易商品类型对应的交易商品信息推送给所述用户。
可以在用户交易时，将推送给所述用户的交易商品信息打印在所述用户的账单上，或者电子票据中，从而获得用户的关注。
还可以向用户推送与用户的消费阶段相匹配的商品。
具体的，获取用户的实时交易信息；
根据所述实时交易信息确定实时的交易商品类型，并向所述用户推送与所述用户的消费阶段相匹配的交易商品信息。
在所述用户相匹配的商品信息对应的交易商品类型中，确定与所述实时交易的交易商品类型相匹配的交易商品类型，并将与所述实时交易的交易商 品类型相匹配的交易商品类型对应的交易商品信息推送给所述用户。
基于相同的技术构思，本发明实施例还提供一种交易数据处理装置，该装置可执行上述方法实施例。本发明实施例提供的装置如图2所示。
如图2所示，为本发明实施例提供的一种交易数据处理装置，该装置包括：
获取单元201，用于获取用户的历史交易信息，所述历史交易信息包括交易金额、交易商品类型；确定单元202，用于根据所述交易金额确定所述用户的交易金额平均值，并根据所述用户的交易金额平均值以及交易商品类型确定所述用户的加权交易金额平均值，并根据所述加权交易金额平均值确定所述用户的消费等级；从所述用户的交易商品类型中确定所述用户的特征交易商品类型，所述特征交易商品类型为该交易商品类型对应的交易次数大于该交易商品类型对应的阈值、且该交易商品类型属于消费阶段中预设的交易商品类型；根据所述用户的特征交易商品类型确定所述用户所处的消费阶段；匹配单元203，用于根据所述用户的消费等级和所述用户所处的消费阶段，确定与所述用户相匹配的商品信息。
可选地，所述获取单元201具体用于：在分布式存储系统中确定存储所述用户的历史交易信息的数据库节点；
根据数据库节点的状态标识确定所述存储所述用户的历史交易信息的数据库节点中处于活跃状态的数据库节点；通过所述处于活跃状态的数据库节点获取所述用户的历史交易信息。
可选地，该装置还包括检测单元204，所述检测单元204通过以下方式确定数据库节点的状态标识：向数据库节点发送检测报文，若在预设时间段内未接收到所述数据库节点的响应报文，则确定所述数据库节点处于失效状态，并将所述数据库节点的状态标识确定为失效状态，否则将所述数据库节点的状态标识确定为活跃状态。
可选地，该装置还包括备份单元205，所述备份单元205用于：确定与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库 节点；对所述与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点中存储的数据备份至其他处于活跃状态的数据库节点。
可选地，所述确定单元202具体用于：根据以下公式确定用户的加权交易金额平均值：
Figure PCTCN2016099224-appb-000005
其中，M表示用户的加权交易金额平均值，D表示用户的交易金额平均值，Ce表示第e次交易的交易商品类型的加权值，e大于等于1且小于等于N，N表示交易次数；将所述用户的加权交易金额平均值对应的等级确定所述用户的消费等级。
可选地，所述匹配单元203具体用于：确定与所述用户的消费等级一致的其他用户；确定所述其他用户的历史交易信息中的交易商品类型；在所述其他用户的历史交易信息中的交易商品类型中，确定与所述用户所处的消费阶段相匹配的交易商品类型，并将与所述用户所处的消费阶段相匹配的交易商品类型对应的交易商品信息确定为与所述用户相匹配的商品信息。
可选地，所述匹配单元203具体用于：获取商家的商家属性信息以及商家的历史交易信息，所述商家属性信息中包括交易商品类型，所述商家的历史交易信息中包括交易金额；将商家的交易金额平均值在同一范围内、且商家的交易商品类型相同的商家划分为一个商家聚类；将商家的交易金额平均值与所述用户的消费等级相匹配、且商家的交易商品类型属于所述用户所处的消费阶段的商家聚类，确定为与所述用户相匹配的商家聚类；将所述与所述用户相匹配的商家聚类对应的商品信息确定为与所述用户相匹配的商品信息。
可选地，该装置还包括推送单元；所述推送单元206具体用于：获取用户的实时交易信息；在所述用户相匹配的商品信息对应的交易商品类型中，确定与所述实时交易的交易商品类型相匹配的交易商品类型，并将与所述实时交易的交易商品类型相匹配的交易商品类型对应的交易商品信息推送给所 述用户。
本发明实施例中，是通过用户的线下交易记录确定用户的交易金额平均值以及交易商品类型，从而确定用户的消费等级以及消费阶段，最终确定用户的消费行为模型。由于线下交易记录更能反映消费者的真实行为，因此获得的消费行为模型更加准确。
基于相同的技术构思，本发明实施例还提供一种交易数据处理装置，该装置可执行上述方法实施例。本发明实施例提供的装置如图3所示。
如图3所示，为本发明实施例提供的一种交易数据处理装置，该装置包括存储器301和处理器302和总线303：
总线303可以是外设部件互连标准(peripheral component interconnect，简称PCI)总线或扩展工业标准结构(extended industry standard architecture，简称EISA)总线等。总线可以分为地址总线、数据总线、控制总线等。为便于表示，图3中仅用一条粗线表示，但并不表示仅有一根总线或一种类型的总线。
存储器301可以包括易失性存储器(volatile memory)，例如随机存取存储器(random-access memory，简称RAM)；存储器也可以包括非易失性存储器(non-volatile memory)，例如快闪存储器(flash memory)，硬盘(hard disk drive，简称HDD)或固态硬盘(solid-state drive，简称SSD)；存储器301还可以包括上述种类的存储器的组合。
处理器302可以是中央处理器(central processing unit，简称CPU)，网络处理器(network processor，简称NP)或者CPU和NP的组合。
处理器302还可以进一步包括硬件芯片。上述硬件芯片可以是专用集成电路(application-specific integrated circuit，简称ASIC)，可编程逻辑器件(programmable logic device，简称PLD)或其组合。上述PLD可以是复杂可编程逻辑器件(complex programmable logic device，简称CPLD)，现场可编 程逻辑门阵列(field-programmable gate array，简称FPGA)，通用阵列逻辑(generic array logic,简称GAL)或其任意组合。
存储器301，用于存储程序和指令；
处理器302，用于通过调用所述存储器中存储的程序和指令，执行：
获取用户的历史交易信息，所述历史交易信息包括交易金额、交易商品类型；根据所述交易金额确定所述用户的交易金额平均值，并根据所述用户的交易金额平均值以及交易商品类型确定所述用户的加权交易金额平均值，并根据所述加权交易金额平均值确定所述用户的消费等级；从所述用户的交易商品类型中确定所述用户的特征交易商品类型；根据所述用户的特征交易商品类型确定所述用户所处的消费阶段；根据所述用户的消费等级和所述用户所处的消费阶段，确定与所述用户相匹配的商品信息；
其中，所述特征交易商品类型为该交易商品类型对应的交易次数大于该交易商品类型对应的阈值、且该交易商品类型属于消费阶段中预设的交易商品类型。
可选地，所述处理器302，具体用于：在分布式存储系统中确定存储所述用户的历史交易信息的数据库节点；根据数据库节点的状态标识确定所述存储所述用户的历史交易信息的数据库节点中处于活跃状态的数据库节点；通过所述处于活跃状态的数据库节点获取所述用户的历史交易信息。
可选地，所述处理器302，还用于通过以下方式确定数据库节点的状态标识：
向数据库节点发送检测报文，若在预设时间段内未接收到所述数据库节点的响应报文，则确定所述数据库节点处于失效状态，并将所述数据库节点的状态标识确定为失效状态，否则将所述数据库节点的状态标识确定为活跃状态。
可选地，所述处理器302，还用于：确定与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点；对所述与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点中存 储的数据备份至其他处于活跃状态的数据库节点。
可选地，所述处理器302，具体用于：根据以下公式确定用户的加权交易金额平均值：
Figure PCTCN2016099224-appb-000006
其中，M表示用户的加权交易金额平均值，D表示用户的交易金额平均值，Ce表示第e次交易的交易商品类型的加权值，e大于等于1且小于等于N，N表示交易次数；将所述用户的加权交易金额平均值对应的等级确定所述用户的消费等级。
可选地，所述处理器302，具体用于：确定与所述用户的消费等级一致的其他用户；确定所述其他用户的历史交易信息中的交易商品类型；在所述其他用户的历史交易信息中的交易商品类型中，确定与所述用户所处的消费阶段相匹配的交易商品类型，并将与所述用户所处的消费阶段相匹配的交易商品类型对应的交易商品信息确定为与所述用户相匹配的商品信息。
可选地，所述处理器302，具体用于：获取商家的商家属性信息以及商家的历史交易信息，所述商家属性信息中包括交易商品类型，所述商家的历史交易信息中包括交易金额；将商家的交易金额平均值在同一范围内、且商家的交易商品类型相同的商家划分为一个商家聚类；将商家的交易金额平均值与所述用户的消费等级相匹配、且商家的交易商品类型属于所述用户所处的消费阶段的商家聚类，确定为与所述用户相匹配的商家聚类；将所述与所述用户相匹配的商家聚类对应的商品信息确定为与所述用户相匹配的商品信息。
可选地，所述处理器302，还用于：获取用户的实时交易信息；在所述用户相匹配的商品信息对应的交易商品类型中，确定与所述实时交易的交易商品类型相匹配的交易商品类型，并将与所述实时交易的交易商品类型相匹配的交易商品类型对应的交易商品信息推送给所述用户。
本发明实施例中，是通过用户的线下交易记录确定用户的交易金额平均值以及交易商品类型，从而确定用户的消费等级以及消费阶段，最终确定用 户的消费行为模型。由于线下交易记录更能反映消费者的真实行为，因此获得的消费行为模型更加准确。
本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器指令，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
尽管已描述了本发明的优选实施例，但本领域内的技术人员一旦得知了基本创造性概念，则可对这些实施例作出另外的变更和修改。所以，所附权利要求意欲解释为包括优选实施例以及落入本发明范围的所有变更和修改。
显然，本领域的技术人员可以对本发明进行各种改动和变型而不脱离本发明的范围。这样，倘若本发明的这些修改和变型属于本发明权利要求的范围之内，则本发明也意图包含这些改动和变型在内。

Claims (24)

  1. 一种交易数据处理方法，其特征在于，该方法包括：
    获取用户的历史交易信息，所述历史交易信息包括交易金额、交易商品类型；
    根据所述交易金额确定所述用户的交易金额平均值，并根据所述用户的交易金额平均值以及交易商品类型确定所述用户的加权交易金额平均值，并根据所述加权交易金额平均值确定所述用户的消费等级；
    从所述用户的交易商品类型中确定所述用户的特征交易商品类型，所述特征交易商品类型为该交易商品类型对应的交易次数大于该交易商品类型对应的阈值、且该交易商品类型属于消费阶段中预设的交易商品类型；
    根据所述用户的特征交易商品类型确定所述用户所处的消费阶段；
    根据所述用户的消费等级和所述用户所处的消费阶段，确定与所述用户相匹配的商品信息。
  2. 如权利要求1所述的方法，其特征在于，所述获取用户的历史交易信息，包括：
    在分布式存储系统中确定存储所述用户的历史交易信息的数据库节点；
    根据数据库节点的状态标识确定所述存储所述用户的历史交易信息的数据库节点中处于活跃状态的数据库节点；
    通过所述处于活跃状态的数据库节点获取所述用户的历史交易信息。
  3. 如权利要求2所述的方法，其特征在于，通过以下方式确定数据库节点的状态标识：
    向数据库节点发送检测报文，若在预设时间段内未接收到所述数据库节点的响应报文，则确定所述数据库节点处于失效状态，并将所述数据库节点的状态标识确定为失效状态，否则将所述数据库节点的状态标识确定为活跃状态。
  4. 如权利要求3所述的方法，其特征在于，所述将所述数据库节点的状 态标识确定为失效状态之后，还包括：
    确定与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点；
    对所述与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点中存储的数据备份至其他处于活跃状态的数据库节点。
  5. 如权利要求1至4任一项所述的方法，其特征在于，所述根据所述交易金额确定所述用户的交易金额平均值，并根据所述用户的交易金额平均值以及交易商品类型确定所述用户的加权交易金额平均值，并根据所述加权交易金额平均值确定所述用户的消费等级，包括：
    根据以下公式确定用户的加权交易金额平均值：
    Figure PCTCN2016099224-appb-100001
    其中，M表示用户的加权交易金额平均值，D表示用户的交易金额平均值，Ce表示第e次交易的交易商品类型的加权值，e大于等于1且小于等于N，N表示交易次数；
    将所述用户的加权交易金额平均值对应的等级确定所述用户的消费等级。
  6. 如权利要求1所述的方法，其特征在于，所述根据所述用户的消费等级和所述用户所处的消费阶段，确定与所述用户相匹配的商品信息，包括：
    确定与所述用户的消费等级一致的其他用户；
    确定所述其他用户的历史交易信息中的交易商品类型；
    在所述其他用户的历史交易信息中的交易商品类型中，确定与所述用户所处的消费阶段相匹配的交易商品类型，并将与所述用户所处的消费阶段相匹配的交易商品类型对应的交易商品信息确定为与所述用户相匹配的商品信息。
  7. 如权利要求1所述的方法，其特征在于，所述根据所述用户的消费等级和所述用户所处的消费阶段，确定与所述用户相匹配的商品信息，包括：
    获取商家的商家属性信息以及商家的历史交易信息，所述商家属性信息 中包括交易商品类型，所述商家的历史交易信息中包括交易金额；
    将商家的交易金额平均值在同一范围内、且商家的交易商品类型相同的商家划分为一个商家聚类；
    将商家的交易金额平均值与所述用户的消费等级相匹配、且商家的交易商品类型属于所述用户所处的消费阶段的商家聚类，确定为与所述用户相匹配的商家聚类；
    将所述与所述用户相匹配的商家聚类对应的商品信息确定为与所述用户相匹配的商品信息。
  8. 如权利要求6或7所述的方法，其特征在于，该方法还包括：
    获取用户的实时交易信息；
    在所述用户相匹配的商品信息对应的交易商品类型中，确定与所述实时交易的交易商品类型相匹配的交易商品类型，并将与所述实时交易的交易商品类型相匹配的交易商品类型对应的交易商品信息推送给所述用户。
  9. 一种交易数据处理装置，其特征在于，该装置包括：
    获取单元，用于获取用户的历史交易信息，所述历史交易信息包括交易金额、交易商品类型；
    确定单元，用于根据所述交易金额确定所述用户的交易金额平均值，并根据所述用户的交易金额平均值以及交易商品类型确定所述用户的加权交易金额平均值，并根据所述加权交易金额平均值确定所述用户的消费等级；从所述用户的交易商品类型中确定所述用户的特征交易商品类型，所述特征交易商品类型为该交易商品类型对应的交易次数大于该交易商品类型对应的阈值、且该交易商品类型属于消费阶段中预设的交易商品类型；根据所述用户的特征交易商品类型确定所述用户所处的消费阶段；
    匹配单元，用于根据所述用户的消费等级和所述用户所处的消费阶段，确定与所述用户相匹配的商品信息。
  10. 如权利要求9所述的装置，其特征在于，所述获取单元具体用于：
    在分布式存储系统中确定存储所述用户的历史交易信息的数据库节点；
    根据数据库节点的状态标识确定所述存储所述用户的历史交易信息的数据库节点中处于活跃状态的数据库节点；
    通过所述处于活跃状态的数据库节点获取所述用户的历史交易信息。
  11. 如权利要求10所述的装置，其特征在于，该装置还包括检测单元，所述检测单元通过以下方式确定数据库节点的状态标识：
    向数据库节点发送检测报文，若在预设时间段内未接收到所述数据库节点的响应报文，则确定所述数据库节点处于失效状态，并将所述数据库节点的状态标识确定为失效状态，否则将所述数据库节点的状态标识确定为活跃状态。
  12. 如权利要求11所述的装置，其特征在于，该装置还包括备份单元，所述备份单元用于：
    确定与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点；
    对所述与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点中存储的数据备份至其他处于活跃状态的数据库节点。
  13. 如权利要求9至12任一项所述的装置，其特征在于，所述确定单元具体用于：
    根据以下公式确定用户的加权交易金额平均值：
    Figure PCTCN2016099224-appb-100002
    其中，M表示用户的加权交易金额平均值，D表示用户的交易金额平均值，Ce表示第e次交易的交易商品类型的加权值，e大于等于1且小于等于N，N表示交易次数；
    将所述用户的加权交易金额平均值对应的等级确定所述用户的消费等级。
  14. 如权利要求9所述的装置，其特征在于，所述匹配单元具体用于：
    确定与所述用户的消费等级一致的其他用户；
    确定所述其他用户的历史交易信息中的交易商品类型；
    在所述其他用户的历史交易信息中的交易商品类型中，确定与所述用户所处的消费阶段相匹配的交易商品类型，并将与所述用户所处的消费阶段相匹配的交易商品类型对应的交易商品信息确定为与所述用户相匹配的商品信息。
  15. 如权利要求9所述的装置，其特征在于，所述匹配单元具体用于：
    获取商家的商家属性信息以及商家的历史交易信息，所述商家属性信息中包括交易商品类型，所述商家的历史交易信息中包括交易金额；
    将商家的交易金额平均值在同一范围内、且商家的交易商品类型相同的商家划分为一个商家聚类；
    将商家的交易金额平均值与所述用户的消费等级相匹配、且商家的交易商品类型属于所述用户所处的消费阶段的商家聚类，确定为与所述用户相匹配的商家聚类；
    将所述与所述用户相匹配的商家聚类对应的商品信息确定为与所述用户相匹配的商品信息。
  16. 如权利要求14或15所述的装置，其特征在于，该装置还包括推送单元；所述推送单元具体用于：
    获取用户的实时交易信息；
    在所述用户相匹配的商品信息对应的交易商品类型中，确定与所述实时交易的交易商品类型相匹配的交易商品类型，并将与所述实时交易的交易商品类型相匹配的交易商品类型对应的交易商品信息推送给所述用户。
  17. 一种交易数据处理装置，其特征在于，该装置包括：
    存储器，用于存储程序和指令；
    处理器，用于通过调用所述存储器中存储的程序和指令，执行：
    获取用户的历史交易信息，所述历史交易信息包括交易金额、交易商品类型；根据所述交易金额确定所述用户的交易金额平均值，并根据所述用户的交易金额平均值以及交易商品类型确定所述用户的加权交易金额平均值，并根据所述加权交易金额平均值确定所述用户的消费等级；从所述用户的交 易商品类型中确定所述用户的特征交易商品类型；根据所述用户的特征交易商品类型确定所述用户所处的消费阶段；根据所述用户的消费等级和所述用户所处的消费阶段，确定与所述用户相匹配的商品信息；
    其中，所述特征交易商品类型为该交易商品类型对应的交易次数大于该交易商品类型对应的阈值、且该交易商品类型属于消费阶段中预设的交易商品类型。
  18. 如权利要求17所述的装置，其特征在于，所述处理器，具体用于：
    在分布式存储系统中确定存储所述用户的历史交易信息的数据库节点；
    根据数据库节点的状态标识确定所述存储所述用户的历史交易信息的数据库节点中处于活跃状态的数据库节点；
    通过所述处于活跃状态的数据库节点获取所述用户的历史交易信息。
  19. 如权利要求18所述的装置，其特征在于，所述处理器，还用于通过以下方式确定数据库节点的状态标识：
    向数据库节点发送检测报文，若在预设时间段内未接收到所述数据库节点的响应报文，则确定所述数据库节点处于失效状态，并将所述数据库节点的状态标识确定为失效状态，否则将所述数据库节点的状态标识确定为活跃状态。
  20. 如权利要求19所述的装置，其特征在于，所述处理器，还用于：
    确定与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点；
    对所述与所述处于失效状态的数据库节点中存储的数据相同、且处于活跃状态的数据库节点中存储的数据备份至其他处于活跃状态的数据库节点。
  21. 如权利要求17至20任一项所述的装置，其特征在于，所述处理器，具体用于：
    根据以下公式确定用户的加权交易金额平均值：
    Figure PCTCN2016099224-appb-100003
    其中，M表示用户的加权交易金额平均值，D表示用户的交易金额平均值，Ce表示第e次交易的交易商品类型的加权值，e大于等于1且小于等于N，N表示交易次数；
    将所述用户的加权交易金额平均值对应的等级确定所述用户的消费等级。
  22. 如权利要求17所述的装置，其特征在于，所述处理器，具体用于：
    确定与所述用户的消费等级一致的其他用户；
    确定所述其他用户的历史交易信息中的交易商品类型；
    在所述其他用户的历史交易信息中的交易商品类型中，确定与所述用户所处的消费阶段相匹配的交易商品类型，并将与所述用户所处的消费阶段相匹配的交易商品类型对应的交易商品信息确定为与所述用户相匹配的商品信息。
  23. 如权利要求17所述的装置，其特征在于，所述处理器，具体用于：
    获取商家的商家属性信息以及商家的历史交易信息，所述商家属性信息中包括交易商品类型，所述商家的历史交易信息中包括交易金额；
    将商家的交易金额平均值在同一范围内、且商家的交易商品类型相同的商家划分为一个商家聚类；
    将商家的交易金额平均值与所述用户的消费等级相匹配、且商家的交易商品类型属于所述用户所处的消费阶段的商家聚类，确定为与所述用户相匹配的商家聚类；
    将所述与所述用户相匹配的商家聚类对应的商品信息确定为与所述用户相匹配的商品信息。
  24. 如权利要求22或23所述的装置，其特征在于，所述处理器，还用于：
    获取用户的实时交易信息；
    在所述用户相匹配的商品信息对应的交易商品类型中，确定与所述实时交易的交易商品类型相匹配的交易商品类型，并将与所述实时交易的交易商 品类型相匹配的交易商品类型对应的交易商品信息推送给所述用户。
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