CN105931066A - Transaction data processing method and device - Google Patents

Abstract

The invention discloses a transaction data processing method and device, comprising: acquiring historical transaction information of a user, the historical transaction information including transaction amount and transaction commodity type; determining the average value of the user's transaction amount according to the transaction amount, And determine the user's weighted average transaction amount according to the user's average transaction amount and transaction commodity type, and determine the user's consumption level according to the weighted transaction amount average; determine the user's transaction commodity type The user's characteristic trading commodity type, the characteristic trading commodity type is that the number of transactions corresponding to the trading commodity type is greater than the threshold corresponding to the trading commodity type and the trading commodity type belongs to the preset trading commodity type in the consumption stage; the trading commodity is based on the user's characteristics The type determines the consumption stage of the user; according to the consumption level of the user and the consumption stage of the user, the product information matching the user is determined.

Description

A transaction data processing method and device

technical field

The invention relates to the technical field of data processing, in particular to a transaction data processing method and device thereof.

Background technique

As the security of online payment services is getting higher and higher, more and more consumer behaviors are completed through the network. Some e-commerce platforms establish consumer behavior models based on consumers' online searches and consumer behaviors, and push corresponding product information for consumers.

However, due to the limitations of the network environment, consumers of some commodities will not purchase on the network, for example, cars, and at the same time, the consumption account of the consumer can be used by multiple people at the same time. Therefore, the consumption behavior model established based on the consumption behavior of consumers in the network cannot reflect the real consumption behavior of consumers.

Therefore, the effect of pushing product information based on the consumption model established by the consumer in the network is not very good.

Contents of the invention

Embodiments of the present invention provide a transaction data processing method and device thereof, so as to establish an accurate consumption behavior model.

An embodiment of the present invention provides a transaction data processing method, including:

Obtain the user's historical transaction information, the historical transaction information includes the transaction amount, transaction commodity type;

Determine the average transaction amount of the user according to the transaction amount, determine the average weighted transaction amount of the user according to the average transaction amount of the user and the type of transaction commodity, and determine the average value of the transaction amount based on the weighted average amount the consumption level of said user;

Determine the user's characteristic transaction commodity type from the user's transaction commodity type, the characteristic transaction commodity type is that the transaction times corresponding to the transaction commodity type is greater than the threshold value corresponding to the transaction commodity type, and the transaction commodity type belongs to consumption The type of trading commodity preset in the stage;

Determining the consumption stage of the user according to the type of commodity traded according to the characteristics of the user;

According to the consumption level of the user and the consumption stage of the user, product information matching the user is determined.

Preferably, the acquisition of the user's historical transaction information includes:

Determining a database node storing the user's historical transaction information in the distributed storage system;

determining an active database node among the database nodes storing the user's historical transaction information according to the status identifier of the database node;

The historical transaction information of the user is obtained through the active database node.

Preferably, the state identifier of the database node is determined in the following manner:

Send a detection message to the database node, if the response message of the database node is not received within the preset time period, then determine that the database node is in an invalid state, and determine the state identifier of the database node as an invalid state , otherwise, determine the state identifier of the database node as an active state.

Preferably, after the state identification of the database node is determined as a failure state, it further includes:

Determining a database node that has the same data stored in the database node in the failure state and is in an active state;

The data stored in the active database node that is the same as the data stored in the failed database node is backed up to other active database nodes.

Preferably, the average transaction amount of the user is determined according to the transaction amount, and the weighted average transaction amount of the user is determined according to the average transaction amount of the user and the type of commodity traded, and according to the weighted The average transaction amount determines the consumption level of the user, including:

The average weighted transaction amount of a user is determined according to the following formula:

$\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; e</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; D.</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; N</span>}$

Among them, M represents the average value of the weighted transaction amount of the user, 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, and N represents the number of transactions;

The consumption level of the user is determined by the level corresponding to the average weighted transaction amount of the user.

Preferably, the determining the commodity information matching the user according to the consumption level of the user and the consumption stage of the user includes:

Identify other users who are consistent with the user's consumption level;

Determine the transaction commodity type in the other user's historical transaction information;

Among the transaction commodity types in the historical transaction information of the other users, determine the transaction commodity types that match the consumption stage of the user, and determine the transaction commodity types that match the consumption stage of the user The corresponding transaction commodity information is determined as the commodity information matching the user.

Preferably, the determining the commodity information matching the user according to the consumption level of the user and the consumption stage of the user includes:

Obtaining merchant attribute information and merchant historical transaction information of the merchant, the merchant attribute information including the transaction commodity type, and the merchant historical transaction information including the transaction amount;

Merchants with the average transaction amount of merchants within the same range and merchants with the same type of transaction commodities are divided into a merchant cluster;

Matching the average transaction amount of the merchant with the consumption level of the user, and the merchant cluster whose transaction commodity type belongs to the consumption stage of the user is determined as the merchant cluster matching the user;

The product information corresponding to the merchant cluster matching the user is determined as the product information matching the user.

Preferably, the method also includes:

Obtain real-time transaction information of users;

Among the transaction commodity types corresponding to the commodity information matched by the user, determine the transaction commodity types that match the real-time transaction transaction commodity types, and match the transaction commodity types that match the real-time transaction transaction commodity types The corresponding transaction commodity information is pushed to the user.

An embodiment of the present invention provides a transaction data processing device, which includes:

An acquisition unit, configured to acquire historical transaction information of the user, the historical transaction information including transaction amount and transaction commodity type;

A determining unit, configured to determine the average transaction amount of the user according to the transaction amount, and determine the weighted average transaction amount of the user according to the average transaction amount of the user and the type of commodity to be traded, and determine the average transaction amount of the user according to the weighted The average transaction amount determines the user's consumption level; the user's characteristic transaction commodity type is determined from the user's transaction commodity type, and the characteristic transaction commodity type is that the transaction times corresponding to the transaction commodity type is greater than the transaction commodity type The threshold value corresponding to the type, and the transaction commodity type belongs to the preset transaction commodity type in the consumption stage; according to the user's characteristic transaction commodity type, the consumption stage of the user is determined;

The matching unit is configured to determine commodity information matching the user according to the consumption level of the user and the consumption stage of the user.

Preferably, the acquisition unit is specifically used for:

Determining a database node storing the user's historical transaction information in the distributed storage system;

determining an active database node among the database nodes storing the user's historical transaction information according to the status identifier of the database node;

The historical transaction information of the user is obtained through the active database node.

Preferably, the device further includes a detection unit, and the detection unit determines the state identifier of the database node in the following manner:

Send a detection message to the database node, if the response message of the database node is not received within the preset time period, then determine that the database node is in an invalid state, and determine the state identifier of the database node as an invalid state , otherwise, determine the state identifier of the database node as an active state.

Preferably, the device also includes a backup unit, the backup unit is used for:

Determining a database node that has the same data stored in the database node in the failure state and is in an active state;

The data stored in the active database node that is the same as the data stored in the failed database node is backed up to other active database nodes.

Preferably, the determining unit is specifically used for:

The average weighted transaction amount of a user is determined according to the following formula:

$\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; e</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; D.</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; N</span>}$

Among them, M represents the average value of the weighted transaction amount of the user, 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, and N represents the number of transactions;

The consumption level of the user is determined by the level corresponding to the average weighted transaction amount of the user.

Preferably, the matching unit is specifically used for:

Identify other users who are consistent with the user's consumption level;

Determine the transaction commodity type in the other user's historical transaction information;

Among the transaction commodity types in the historical transaction information of the other users, determine the transaction commodity types that match the consumption stage of the user, and determine the transaction commodity types that match the consumption stage of the user The corresponding transaction commodity information is determined as the commodity information matching the user.

Preferably, the matching unit is specifically used for:

Obtaining merchant attribute information and merchant historical transaction information of the merchant, the merchant attribute information including the transaction commodity type, and the merchant historical transaction information including the transaction amount;

Merchants with the average transaction amount of merchants within the same range and merchants with the same type of transaction commodities are divided into a merchant cluster;

Matching the average transaction amount of the merchant with the consumption level of the user, and the merchant cluster whose transaction commodity type belongs to the consumption stage of the user is determined as the merchant cluster matching the user;

The product information corresponding to the merchant cluster matching the user is determined as the product information matching the user.

Preferably, the device also includes a push unit; the push unit is specifically used for:

Obtain real-time transaction information of users;

Among the transaction commodity types corresponding to the commodity information matched by the user, determine the transaction commodity types that match the real-time transaction transaction commodity types, and match the transaction commodity types that match the real-time transaction transaction commodity types The corresponding transaction commodity information is pushed to the user.

Embodiments of the present invention have the following beneficial effects:

In the embodiment of the present invention, the user's average transaction amount and transaction commodity type are determined through the user's offline transaction records, thereby determining the user's consumption level and consumption stage, and finally determining the user's consumption behavior model. Since offline transaction records can better reflect the real behavior of consumers, the obtained consumption behavior model is more accurate.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings that need to be used in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For Those of ordinary skill in the art can also obtain other drawings based on these drawings without any creative effort.

Fig. 1 is a schematic flow chart of a transaction data processing method provided by an embodiment of the present invention;

Fig. 2 is a schematic structural diagram of a transaction data processing device provided by an embodiment of the present invention.

detailed description

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments . Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

As shown in Figure 1, a schematic flow chart of a transaction data processing method provided by an embodiment of the present invention, the method includes:

Step 101: Acquiring the user's historical transaction information, the historical transaction information includes the transaction amount and transaction commodity type;

Step 102: Determine the average transaction amount of the user according to the transaction amount, and determine the average weighted transaction amount of the user according to the average transaction amount of the user and the type of commodity traded, and determine the average transaction amount of the user according to the weighted transaction amount The average value determines the consumption level of said user;

Step 103: Determine the characteristic transaction commodity type of the user from the transaction commodity types of the user, and the characteristic transaction commodity type is that the transaction times corresponding to the transaction commodity type is greater than the threshold value corresponding to the transaction commodity type, and the transaction commodity type The type belongs to the preset transaction commodity type in the consumption stage;

Step 104: Determine the consumption stage of the user according to the user's characteristic transaction commodity type;

Step 105: Determine commodity information matching the user according to the consumption level of the user and the consumption stage of the user.

In step 101, the transaction commodity type in the historical transaction information may specifically be catering, clothing, home appliances, consumer electronics, etc., indicating the type of transaction commodities, or indicating the transaction type.

In the embodiment of the present invention, the user's historical transaction information can be stored in a distributed storage system. Distributed storage system is to disperse and store data on multiple independent database nodes. The traditional network storage system uses centralized database nodes to store all data, and the distributed network storage system adopts a scalable system structure and uses multiple database nodes to share the storage load. It not only improves the reliability, availability and access efficiency of the system, Also easy to expand.

In the embodiment of the present invention, the distributed data storage system has the following characteristics:

The data has more than 2 redundancy levels and can be configured as multi-level redundancy;

When the database node fails, the database node in the failed state can be automatically isolated;

When the database node becomes invalid, the data of the database node in the failed state can be automatically backed up to other active database nodes;

Can dynamically increase database nodes in real time;

Database nodes can be dynamically reduced in real time.

In order to quickly indicate the state identification of the database node, in the embodiment of the present invention, the database node in the failure state is marked, and it is determined that the data stored in the database node in the failure state is the same and is active state database node; backing up the data stored in the active database node to other active database nodes.

To sum up, in the embodiment of the present invention, the database node mainly includes two types of key information: location information and status identification. The location information may consist of an IP (Internet Protocol) address and a port number, indicating the location when accessing the database node. The status flag indicates that the database node is active or failed.

For example, when data needs to be read, the location of the database node can be determined after determining the IP address and port number of the database node, and data can be read from the determined database node.

When obtaining the user's historical transaction information, it is necessary to first determine the status identifier of the database node, and obtain the user's historical transaction information through the database node whose status identifier is active in the distributed storage system. Specifically, the database node storing the historical transaction information of the user is determined in the distributed storage system; the database node in an active state among the database nodes storing the historical transaction information of the user is determined according to the state identifier of the database node; The historical transaction information of the user is obtained through the active database node.

Among them, the status identifier of the database node can be determined in the following ways:

Send a detection message to the database node, if the response message of the database node is not received within the preset time period, then determine that the database node is in an invalid state, and determine the state identifier of the database node as an invalid state , otherwise, determine the state identifier of the database node as an active state.

Of course, other detection methods can also be used to determine the status identifier of the database node, which will not be repeated here.

After it is determined that the database node is in a failure state, it may also be necessary to back up the data in the database node in the failure state. Specifically, first determine the database node that is the same as the data stored in the database node in the failure state and is in the active state; The data stored in the database node is backed up to other active database nodes.

In step 102, after obtaining the historical transaction information of the user, the average transaction amount of the user may be determined according to the transaction amount in the user's historical transaction information, and determined according to the average transaction amount of the user and the type of transaction commodity The consumption level of the user.

Determine the average transaction amount of the user according to the transaction amount, determine the average weighted transaction amount of the user according to the average transaction amount of the user and the type of transaction commodity, and determine the average value of the transaction amount based on the weighted average amount The consumption level of the user

Specifically, the average weighted transaction amount of a user can be determined according to the following formula:

$\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; e</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; D.</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; N</span>}\mathrm{<span\; class="notranslate">\; ...</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

Among them, M represents the average weighted transaction amount of the user, 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, and N represents the number of transactions.

It should be noted that the weighted value of the transaction commodity type can be set according to the actual situation. The weighted value of the transaction commodity type is a number greater than 0. The greater the value of the transaction amount corresponding to the transaction type, the greater the weighted value of the transaction type.

Then, the level corresponding to the average value of the weighted transaction amount of the user is used to determine the consumption level of the user.

Specifically, determine the historical transaction records of all acquired users, and determine the average weighted transaction amount of all acquired users;

For a user, determine the ranking of the user's weighted average transaction amount among the weighted average transaction amounts of all obtained users, and determine according to the mapping relationship between the user's weighted average transaction amount ranking and consumption level The consumption level of the user.

For example, the consumption levels of all users ranked in the top 1% of the average weighted transaction amounts of all obtained users can be determined as the first level; the average weighted transaction amounts of all obtained users can be The first level is determined by the consumption levels of all users ranked in the top 1% of the value; the consumption level of all users ranked between the top 3% and 1% in the average weighted transaction amount of all obtained users is determined by the second level. The second level; determine the consumption level of all users who are between the top 15% and 3% of the average weighted transaction amount of all acquired users; determine the third level; determine the weighted value of all acquired users The consumption level of all users ranked between the top 47% and 15% of the average transaction amount determines the fourth level; it will be between the top 85% and 47% of the weighted average transaction amount of all acquired users The consumption level of all users of the above-mentioned user is determined as the fifth level; the consumption level of all users who are between the top 94% and 85% of the average weighted transaction amount of all obtained users is determined as the sixth level; The seventh grade is determined by the consumption grades of all users who rank in the last 6% of the average weighted transaction amount of all users obtained above. Of course, there may also be other forms of mapping relationship between the ranking of the user's weighted average transaction amount and the consumption level, which will not be repeated here.

After determining the average ranking of a user's weighted transaction amount, the user's consumption level can be determined according to the above mapping relationship.

The consumption level of the user may indicate the consumption ability of the user, or indicate the social class of the user.

Meanwhile, in step 103, the user's consumption stage can be determined through the user's historical transaction records. There can be many kinds of preset transaction commodity types in the consumption stage.

For example, the user's consumption stage can be divided into the following stages: single stage, marriage preparation stage, newly married stage, baby-raising stage, child-rearing stage, unclassified stage (unclassified refers to: the child being raised has grown up, But not yet married), empty nest stage, widowhood stage.

Among them, at the single stage, the preset trading commodity types are mainly food, books, movies and other entertainment items; at the marriage preparation stage, the preset trading commodity types are mainly high-end fashion, wedding supplies and other items; The types of commodities traded are mainly entertainment, travel and other items; during the baby-raising stage, the default types of transaction commodities are mainly milk powder, diapers and other items; during the child-rearing stage, the default types of transaction commodities are mainly education expenditures and other items; When there is no stage, the default trading commodity types are mainly social goods and other items; in the empty nest stage, the default trading commodity types are mainly health care products and other items; in the widow stage, the default trading commodity types are mainly medical treatment and other items.

In step 104, according to different characteristics of different stages of life, it can be determined that the user will have different preferences for trading commodity types in different stages of life.

For example, if the user often buys baby products such as milk powder and diapers, it can be determined that the user's characteristic transaction commodity type is child care products, so as to determine that the user's consumption stage is the baby care stage.

Finally, in step 105, the product information matching the user is determined according to the user's consumption level and consumption stage, and the product information is pushed to the user when necessary.

A possible implementation of determining the product information matched by the user is as follows:

Identify other users who are consistent with the user's consumption level;

Determine the transaction commodity type in the other user's historical transaction information;

Among the transaction commodity types in the historical transaction information of the other users, determine the transaction commodity types that match the consumption stage of the user, and determine the transaction commodity types that match the consumption stage of the user The corresponding transaction commodity information is determined as the commodity information matching the user.

For example, user A and user B belong to the same consumption class, and user A likes to consume at the Sichuan cuisine restaurant of the first brand, and user B likes to consume at the Sichuan cuisine restaurant of the second brand. At this time, the commodity information of the second brand Sichuan cuisine restaurant that user B likes can be matched with user A. Correspondingly, it is also possible to match the commodity information of the second brand Sichuan cuisine restaurant that user A likes with user B. When user A consumes at the Sichuan cuisine restaurant of the first brand, the product information of the Sichuan cuisine restaurant of the second brand can be pushed to user A, thereby realizing precise marketing.

Another possible implementation of determining the product information matched by the user is:

Obtaining merchant attribute information and merchant historical transaction information of the merchant, the merchant attribute information including the transaction commodity type, and the merchant historical transaction information including the transaction amount;

Merchants with the average transaction amount of merchants within the same range and merchants with the same type of transaction commodities are divided into a merchant cluster;

Matching the average transaction amount of the merchant with the consumption level of the user, and the merchant cluster whose transaction commodity type belongs to the consumption stage of the user is determined as the merchant cluster matching the user;

The product information corresponding to the merchant cluster matching the user is determined as the product information matching the user.

For example, user A belongs to the third consumption level, and user A is single, at this time, merchants matching user A can be clustered. When user A buys a high-end mobile phone, user A can be pushed high-end digital cameras that belong to the same merchant cluster as the high-end mobile phone, so as to achieve precise marketing.

Finally, when the user trades in real time, the user can be pushed commodity information that matches the type of traded commodity that the user trades in real time.

Specifically, obtain real-time transaction information of users;

Among the transaction commodity types corresponding to the commodity information matched by the user, determine the transaction commodity types that match the real-time transaction transaction commodity types, and match the transaction commodity types that match the real-time transaction transaction commodity types The corresponding transaction commodity information is pushed to the user.

When the user trades, the trade commodity information pushed to the user can be printed on the user's bill or in the electronic bill, so as to gain the attention of the user.

Products that match the user's consumption stage can also be pushed to the user.

Specifically, obtain real-time transaction information of users;

Determine the real-time transaction commodity type according to the real-time transaction information, and push transaction commodity information matching the user's consumption stage to the user.

Among the transaction commodity types corresponding to the commodity information matched by the user, determine the transaction commodity types that match the real-time transaction transaction commodity types, and match the transaction commodity types that match the real-time transaction transaction commodity types The corresponding transaction commodity information is pushed to the user.

Based on the same technical concept, an embodiment of the present invention also provides a transaction data processing device, which can execute the above method embodiments. The device provided by the embodiment of the present invention is shown in FIG. 2 .

As shown in Figure 2, it is a transaction data processing device provided by an embodiment of the present invention, which includes:

An acquisition unit 201, configured to acquire the user's historical transaction information, the historical transaction information including transaction amount and transaction commodity type;

The determining unit 202 is configured to determine the average transaction amount of the user according to the transaction amount, and determine the weighted average transaction amount of the user according to the average transaction amount of the user and the type of transaction commodity, and determine the average transaction amount of the user according to the average transaction amount of the user. The average value of the weighted transaction amount determines the consumption level of the user; the characteristic transaction commodity type of the user is determined from the transaction commodity type of the user, and the characteristic transaction commodity type is that the number of transactions corresponding to the transaction commodity type is greater than the transaction The threshold value corresponding to the commodity type, and the transaction commodity type belongs to the preset transaction commodity type in the consumption stage; the consumption stage of the user is determined according to the user's characteristic transaction commodity type;

The matching unit 203 is configured to determine commodity information matching the user according to the consumption level of the user and the consumption stage of the user.

Preferably, the acquisition unit 201 is specifically configured to:

Determining a database node storing the user's historical transaction information in the distributed storage system;

determining an active database node among the database nodes storing the user's historical transaction information according to the status identifier of the database node;

The historical transaction information of the user is obtained through the active database node.

Preferably, the device further includes a detection unit 204, and the detection unit 204 determines the state identifier of the database node in the following manner:

Send a detection message to the database node, if the response message of the database node is not received within the preset time period, then determine that the database node is in an invalid state, and determine the state identifier of the database node as an invalid state , otherwise, determine the state identifier of the database node as an active state.

Preferably, the device also includes a backup unit 205, and the backup unit 205 is used for:

Determining a database node that has the same data stored in the database node in the failure state and is in an active state;

The data stored in the active database node that is the same as the data stored in the failed database node is backed up to other active database nodes.

Preferably, the determining unit 202 is specifically configured to:

The average weighted transaction amount of a user is determined according to the following formula:

$\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; e</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}}<span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; D.</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; N</span>}$

Among them, M represents the average value of the weighted transaction amount of the user, 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, and N represents the number of transactions;

The consumption level of the user is determined by the level corresponding to the average weighted transaction amount of the user.

Preferably, the matching unit 203 is specifically used for:

Identify other users who are consistent with the user's consumption level;

Determine the transaction commodity type in the other user's historical transaction information;

Among the transaction commodity types in the historical transaction information of the other users, determine the transaction commodity types that match the consumption stage of the user, and determine the transaction commodity types that match the consumption stage of the user The corresponding transaction commodity information is determined as the commodity information matching the user.

Preferably, the matching unit 203 is specifically used for:

Obtaining merchant attribute information and merchant historical transaction information of the merchant, the merchant attribute information including the transaction commodity type, and the merchant historical transaction information including the transaction amount;

Merchants with the average transaction amount of merchants within the same range and merchants with the same type of transaction commodities are divided into a merchant cluster;

Matching the average transaction amount of the merchant with the consumption level of the user, and the merchant cluster whose transaction commodity type belongs to the consumption stage of the user is determined as the merchant cluster matching the user;

The product information corresponding to the merchant cluster matching the user is determined as the product information matching the user.

Preferably, the device also includes a push unit; the push unit 206 is specifically used for:

Obtain real-time transaction information of users;

Among the transaction commodity types corresponding to the commodity information matched by the user, determine the transaction commodity types that match the real-time transaction transaction commodity types, and match the transaction commodity types that match the real-time transaction transaction commodity types The corresponding transaction commodity information is pushed to the user.

In the embodiment of the present invention, the user's average transaction amount and transaction commodity type are determined through the user's offline transaction records, thereby determining the user's consumption level and consumption stage, and finally determining the user's consumption behavior model. Since offline transaction records can better reflect the real behavior of consumers, the obtained consumption behavior model is more accurate.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may 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 such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow diagram procedure or procedures and/or block diagram procedures or blocks.

While preferred embodiments of the invention have been described, additional changes and modifications to these embodiments can be made by those skilled in the art once the basic inventive concept is appreciated. Therefore, it is intended that the appended claims be construed to cover the preferred embodiment as well as all changes and modifications which fall within the scope of the invention.

Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention, the present invention is also intended to include these modifications and variations.

Claims (16)

1. a transaction data processing method, it is characterised in that the method includes:

Obtaining the historical transactional information of user, described historical transactional information includes dealing money, trader's category Type；

The dealing money meansigma methods of described user is determined according to described dealing money, and according to the friendship of described user Easily amount of money meansigma methods and tradable commodity type determine the weighting dealing money meansigma methods of described user, and according to Described weighting dealing money meansigma methods determines the consumption grade of described user；

The feature tradable commodity type of described user, described spy is determined from the tradable commodity type of described user Levying tradable commodity type is that transaction count corresponding to this tradable commodity type is corresponding more than this tradable commodity type Threshold value and this tradable commodity type belong in consumer phase preset tradable commodity type；

Feature tradable commodity type according to described user determines the consumer phase residing for described user；

Consumer phase residing for consumption grade according to described user and described user, determines and described user's phase The merchandise news of coupling.

2. the method for claim 1, it is characterised in that the historical trading letter of described acquisition user Breath, including:

The database node of the historical transactional information storing described user is determined in distributed memory system；

Status indicator according to database node determines the number of the historical transactional information of the described user of described storage According to the database node being in active state in the node of storehouse；

The historical transactional information of described user is obtained by the described database node being in active state.

3. method as claimed in claim 2, it is characterised in that determine that data base saves in the following manner The status indicator of point:

Detection messages is sent, if not receiving described database node in preset time period to database node Response message, it is determined that described database node is in failure state, and by the shape of described database node State mark is defined as failure state, otherwise the status indicator of described database node is defined as active state.

4. method as claimed in claim 3, it is characterised in that the described shape by described database node After state mark is defined as failure state, also include:

Determine and in the described database node being in failure state, the data of storage are identical and be in and enliven shape The database node of state；

To in the described and described database node being in failure state, the data of storage are identical and are in active The data backup stored in the database node of state is in the database node of active state to other.

5. the method as described in any one of Claims 1-4, it is characterised in that described according to described friendship Easily the amount of money determines the dealing money meansigma methods of described user, and according to the dealing money meansigma methods of described user with And tradable commodity type determines the weighting dealing money meansigma methods of described user, and according to described weighting trade gold Volume meansigma methods determines the consumption grade of described user, including:

The weighting dealing money meansigma methods of user is determined according to below equation:

$M=\underset{e=1}{\overset{N}{\&Sigma;}}{C}_e\&times;D/N$

Wherein, M represents the weighting dealing money meansigma methods of user, and D represents the dealing money meansigma methods of user, C_eRepresenting the weighted value of the tradable commodity type concluded the business the e time, e is more than or equal to 1 and less than or equal to N, N Represent transaction count；

Grade corresponding for the weighting dealing money meansigma methods of described user is determined the consumption grade of described user.

6. the method for claim 1, it is characterised in that the described consumption etc. according to described user Level and the consumer phase residing for described user, determine the merchandise news matched with described user, including:

Determine other users consistent with the consumption grade of described user；

Determine the tradable commodity type in the historical transactional information of other users described；

In tradable commodity type in the historical transactional information of other users described, determine and described user institute The tradable commodity type that the consumer phase at place matches, and will match with the consumer phase residing for described user Tradable commodity information corresponding to tradable commodity type be defined as the merchandise news that matches with described user.

7. the method for claim 1, it is characterised in that the described consumption etc. according to described user Level and the consumer phase residing for described user, determine the merchandise news matched with described user, including:

Obtain businessman's attribute information and the historical transactional information of businessman of businessman, in described businessman attribute information Including tradable commodity type, the historical transactional information of described businessman includes dealing money；

By the business that the dealing money meansigma methods of businessman is in same scope and the tradable commodity type of businessman is identical Family is divided into businessman's cluster；

The consumption grade of the dealing money meansigma methods of businessman Yu described user is matched and the trader of businessman Category type belongs to businessman's cluster of the consumer phase residing for described user, is defined as matching with described user Businessman clusters；

The businessman described and described user matched clusters corresponding merchandise news and is defined as and described user The merchandise news matched.

Method the most as claimed in claims 6 or 7, it is characterised in that the method also includes:

Obtain the real-time deal information of user；

In the tradable commodity type that the merchandise news that matches described user is corresponding, determine and described real-time friendship The tradable commodity type of easy tradable commodity type matching, and by the trader's category with described real-time deal Tradable commodity information pushing corresponding to tradable commodity type that type matches gives described user.

9. a transaction data processing means, it is characterised in that this device includes:

Acquiring unit, for obtaining the historical transactional information of user, described historical transactional information includes trade gold Volume, tradable commodity type；

Determine unit, for determining the dealing money meansigma methods of described user according to described dealing money, and root The weighting trade gold of described user is determined according to the dealing money meansigma methods of described user and tradable commodity type Volume meansigma methods, and the consumption grade of described user is determined according to described weighting dealing money meansigma methods；From described The tradable commodity type of user determines the feature tradable commodity type of described user, described feature tradable commodity Type is threshold value that transaction count corresponding to this tradable commodity type is corresponding more than this tradable commodity type and should Tradable commodity type belongs to the tradable commodity type preset in consumer phase；Feature transaction according to described user The type of merchandise determines the consumer phase residing for described user；

Matching unit, for the consumer phase residing for the consumption grade according to described user and described user, really The fixed merchandise news matched with described user.

10. device as claimed in claim 9, it is characterised in that described acquiring unit specifically for:

The database node of the historical transactional information storing described user is determined in distributed memory system；

Status indicator according to database node determines the number of the historical transactional information of the described user of described storage According to the database node being in active state in the node of storehouse；

The historical transactional information of described user is obtained by the described database node being in active state.

11. devices as claimed in claim 10, it is characterised in that this device also includes detector unit, Described detector unit determines the status indicator of database node in the following manner:

Detection messages is sent, if not receiving described database node in preset time period to database node Response message, it is determined that described database node is in failure state, and by the shape of described database node State mark is defined as failure state, otherwise the status indicator of described database node is defined as active state.

12. devices as claimed in claim 11, it is characterised in that this device also includes backup units, Described backup units is used for:

Determine and in the described database node being in failure state, the data of storage are identical and be in and enliven shape The database node of state；

To in the described and described database node being in failure state, the data of storage are identical and are in active The data backup stored in the database node of state is in the database node of active state to other.

13. devices as described in any one of claim 9 to 12, it is characterised in that described determine unit Specifically for:

The weighting dealing money meansigma methods of user is determined according to below equation:

$M=\underset{e=1}{\overset{N}{\&Sigma;}}{C}_e\&times;D/N$

Wherein, M represents the weighting dealing money meansigma methods of user, and D represents the dealing money meansigma methods of user, C_eRepresenting the weighted value of the tradable commodity type concluded the business the e time, e is more than or equal to 1 and less than or equal to N, N Represent transaction count；

Grade corresponding for the weighting dealing money meansigma methods of described user is determined the consumption grade of described user.

14. devices as claimed in claim 9, it is characterised in that described matching unit specifically for:

Determine other users consistent with the consumption grade of described user；

Determine the tradable commodity type in the historical transactional information of other users described；

In tradable commodity type in the historical transactional information of other users described, determine and described user institute The tradable commodity type that the consumer phase at place matches, and will match with the consumer phase residing for described user Tradable commodity information corresponding to tradable commodity type be defined as the merchandise news that matches with described user.

15. devices as claimed in claim 9, it is characterised in that described matching unit specifically for:

Obtain businessman's attribute information and the historical transactional information of businessman of businessman, in described businessman attribute information Including tradable commodity type, the historical transactional information of described businessman includes dealing money；

By the business that the dealing money meansigma methods of businessman is in same scope and the tradable commodity type of businessman is identical Family is divided into businessman's cluster；

The consumption grade of the dealing money meansigma methods of businessman Yu described user is matched and the trader of businessman Category type belongs to businessman's cluster of the consumer phase residing for described user, is defined as matching with described user Businessman clusters；

The businessman described and described user matched clusters corresponding merchandise news and is defined as and described user The merchandise news matched.

16. devices as described in claims 14 or 15, it is characterised in that this device also includes pushing list Unit；Described push unit specifically for:

Obtain the real-time deal information of user；

In the tradable commodity type that the merchandise news that matches described user is corresponding, determine and described real-time friendship The tradable commodity type of easy tradable commodity type matching, and by the trader's category with described real-time deal Tradable commodity information pushing corresponding to tradable commodity type that type matches gives described user.