Data integration method and device based on multi-dimension weight mechanism, equipment and medium

Abstract

Embodiments of the present application disclose a data integration method and device based on a multi-dimensional weight mechanism, equipment and a medium. The method comprises: when a first information node in a graph database adds associated first target user information, determining whether a second information node corresponding to the first target user information exists in the graph database; if it exists, determining a first node weight of a first OneID node and a second node weight of a second OneID node according to a preset multi-dimensional weight mechanism, the second OneID node being a OneID node currently associated with the second information node; determining a target OneID node from the first OneID node and the second OneID node according to the first node weight and the second node weight; and associating the first target user information to the target OneID node and canceling the association between the first target user information and a non-target OneID node. The method of the embodiments of the present application can improve the data fusion effect.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to data integration methods, apparatus, devices and media based on multi-dimensional weighting mechanisms. Background Technology

[0002] With the development of internet technology, businesses have more and more marketing channels. Understanding consumer data helps businesses gain a deeper understanding of consumers, thereby optimizing marketing strategies and improving business results.

[0003] However, because user data from different channels is not interconnected, and user data from the same channel may have overlapping data (such as different users corresponding to the same phone number), when different users are associated with the same user information, it is difficult to determine which user the user information should be associated with using existing technology, which affects the data fusion effect. Summary of the Invention

[0004] This application provides a data integration method, apparatus, device, and medium based on a multi-dimensional weighting mechanism, which can accurately identify the OneID node to which the newly added associated user information belongs, thereby improving the data fusion effect.

[0005] In a first aspect, embodiments of this application provide a data integration method based on a multi-dimensional weighting mechanism, which includes:

[0006] When a first information node in the graph database is newly associated with first target user information, it is determined whether there is a second information node in the graph database corresponding to the first target user information. The graph database includes multiple OneID nodes, and different OneID nodes are connected to at least one information node belonging to the same user. Different information nodes under the same OneID node store different user information of the same user.

[0007] If the second information node exists, the first node weight of the first OneID node and the second node weight of the second OneID node are determined according to the preset multi-dimensional weight mechanism. The first OneID node is the OneID node currently associated with the first information node, and the second OneID node is the OneID node currently associated with the second information node. The multi-dimensional weight mechanism includes the source credibility weight mechanism, the relationship pair count weight mechanism, the user information weight mechanism, and the data timeliness weight mechanism.

[0008] The target OneID node is determined from the first OneID node and the second OneID node based on the first node weight and the second node weight;

[0009] The first target user information is associated with the target OneID node, and the association between the first target user information and a non-target OneID node is canceled. The non-target OneID node is the OneID node between the first OneID node and the second OneID node, excluding the target OneID node.

[0010] Secondly, embodiments of this application also provide a data integration device based on a multi-dimensional weighting mechanism, comprising:

[0011] In the transceiver unit, the user obtains the newly added associated first target user information from the first information node;

[0012] The processing unit is configured to, when a first information node in the graph database is newly associated with first target user information, determine whether a second information node corresponding to the first target user information exists in the graph database. The graph database includes multiple OneID nodes, different OneID nodes are connected to at least one information node belonging to the same user, and different information nodes under the same OneID node store different user information of the same user. If a second information node exists, the unit determines the first node weight of the first OneID node and the second node weight of the second OneID node according to a preset multi-dimensional weighting mechanism. The first OneID node is the OneID node currently associated with the first information node, and the second OneID node is the OneID node currently associated with the second information node. The multi-dimensional weighting mechanism includes a source credibility weighting mechanism, a relation pair frequency weighting mechanism, a user information weighting mechanism, and a data timeliness weighting mechanism. The unit determines a target OneID node from the first OneID node and the second OneID node according to the first node weight and the second node weight. The unit associates the first target user information with the target OneID node and cancels the association between the first target user information and non-target OneID nodes. The non-target OneID nodes are the OneID nodes between the first OneID node and the second OneID node excluding the target OneID node.

[0013] Thirdly, embodiments of this application also provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0014] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, the computer program including program instructions that, when executed by a processor, can implement the above-described method.

[0015] This application provides a data integration method, apparatus, device, and medium based on a multi-dimensional weighting mechanism. The method includes: when a first information node in a graph database is newly associated with first target user information, determining whether a second information node corresponding to the first target user information exists in the graph database, wherein the graph database includes multiple OneID nodes, different OneID nodes are connected to at least one information node belonging to the same user, and different information nodes under the same OneID node store different user information of the same user; if a second information node exists, determining the first node weight of the first OneID node and the second node weight of the second OneID node according to a preset multi-dimensional weight mechanism, wherein the first OneID node is the OneID node currently associated with the first information node, and the second OneID node is the OneID node currently associated with the second information node, wherein the multi-dimensional weight mechanism includes a source credibility weight mechanism, a relation pair frequency weight mechanism, a user information weight mechanism, and a data timeliness weight mechanism; determining a target OneID node from the first OneID node and the second OneID node according to the first node weight and the second node weight; associating the first target user information with the target OneID node, and canceling the association between the first target user information and a non-target OneID node, wherein the non-target OneID node is the OneID node between the first OneID node and the second OneID node excluding the target OneID node. This application embodiment uses a multi-dimensional weighting mechanism to accurately identify the OneID node to which the newly added associated user information belongs, thereby improving the data fusion effect. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of a common integrated calculation in a graph database;

[0018] Figure 2 A flowchart illustrating the data integration method based on a multi-dimensional weighting mechanism provided in this application embodiment;

[0019] Figure 3 A schematic diagram of a sub-process of the data integration method based on a multi-dimensional weighting mechanism provided in the embodiments of this application;

[0020] Figure 4This is a schematic diagram illustrating a specific data integration scenario provided in an embodiment of this application.

[0021] Figure 5 Another sub-process diagram of the data integration method based on a multi-dimensional weighting mechanism provided in the embodiments of this application;

[0022] Figure 6 This is a schematic diagram illustrating another specific data integration scenario provided in an embodiment of this application;

[0023] Figure 7 Another sub-process diagram of the data integration method based on a multi-dimensional weighting mechanism provided in the embodiments of this application;

[0024] Figure 8 Another sub-process diagram of the data integration method based on a multi-dimensional weighting mechanism provided in the embodiments of this application;

[0025] Figure 9 This is a schematic diagram illustrating another specific data integration scenario provided in an embodiment of this application;

[0026] Figure 10 Another sub-process diagram of the data integration method based on a multi-dimensional weighting mechanism provided in the embodiments of this application;

[0027] Figure 11 This is a schematic diagram illustrating another specific data integration scenario provided in an embodiment of this application;

[0028] Figure 12 A schematic block diagram of a data integration device based on a multi-dimensional weighting mechanism provided in the embodiments of this application;

[0029] Figure 13 A schematic block diagram of a computer device provided in an embodiment of this application. Detailed Implementation

[0030] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0031] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0032] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0033] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0034] This application provides a data integration method, apparatus, device, and medium based on a multi-dimensional weighting mechanism.

[0035] The execution entity of the data integration method based on the multi-dimensional weight mechanism can be the data integration device based on the multi-dimensional weight mechanism provided in the embodiments of this application, or a computer device that integrates the data integration device based on the multi-dimensional weight mechanism. The data integration device based on the multi-dimensional weight mechanism can be implemented in hardware or software, and the computer device can be a terminal or a server.

[0036] like Figure 1 As shown, Figure 1 In the conventional integration computation of existing technologies, when a new associated mobile phone number 1 is added to OpenID:1 in an existing graph database, the newly added mobile phone number 1 is directly integrated into the OneID:1 node corresponding to OpenID:1. If other OneID nodes are also associated with the same mobile phone number 1, different users may have the same mobile phone number, resulting in poor data fusion.

[0037] To address this, this application provides a data integration method based on a multi-dimensional weighting mechanism. This method can clearly identify which OneID node the newly added user information belongs to, thus avoiding the situation where different OneID nodes are associated with the same user information and improving the data fusion effect.

[0038] Figure 2 This is a flowchart illustrating the data integration method based on a multi-dimensional weighting mechanism provided in an embodiment of this application. Figure 2 As shown, the method includes the following steps S110-S140.

[0039] S110. When a first information node in the graph database is newly associated with first target user information, it is determined whether there is a second information node in the graph database corresponding to the first target user information. The graph database includes multiple OneID nodes, and different OneID nodes are connected to at least one information node belonging to the same user. Different information nodes under the same OneID node store different user information of the same user.

[0040] In this embodiment, when a first information node in the graph database adds associated first target user information, the first target user information is used as an identification field to traverse each OneID node in the graph database to determine whether there is a second information node in the graph database corresponding to the first target user information. The second information node corresponding to the first target user information refers to a second information node that stores the first target user information or a newly added information node associated with the first target user information.

[0041] S120. If the second information node exists, the first node weight of the first OneID node and the second node weight of the second OneID node are determined according to the preset multi-dimensional weight mechanism. The first OneID node is the OneID node currently associated with the first information node, and the second OneID node is the OneID node currently associated with the second information node. The multi-dimensional weight mechanism includes the source credibility weight mechanism, the relationship pair frequency weight mechanism, the user information weight mechanism, and the data timeliness weight mechanism.

[0042] In this embodiment, if a second information node exists, it means that there is user information in the graph database that is duplicated with the first target user information. In this case, it is necessary to determine which OneID node the first target user information belongs to based on a multi-dimensional weighting mechanism.

[0043] Specifically, this embodiment can automatically determine the current weighting mechanism from the multi-dimensional weighting mechanism based on different preconditions. This embodiment includes at least three preconditions.

[0044] in:

[0045] The first prerequisite is that the user information in the first information node and the second information node comes from different channels, the second information node is the information node that currently stores the first target user information, and the second information node has not added any new associated user information. In this case, the current weighting mechanism includes the source credibility weighting mechanism and / or the user information weighting mechanism. Whether the source credibility weighting mechanism, the user information weighting mechanism, or both are used can be set according to the user's choice.

[0046] The second prerequisite is that the user information in the first information node and the second information node comes from the same channel, and the second information node is a newly added information node associated with the first target user information. In this case, the current weighting mechanism is the relationship pair frequency weighting mechanism.

[0047] The third prerequisite is that the user information in the first information node and the second information node comes from different channels, the second information node is the information node that currently stores the first target user information, and the second information node adds a new association with the same second target user information as the first information node. In this case, the current weighting mechanism is the data timeliness weighting mechanism.

[0048] The following sections will describe each of these three prerequisites in detail.

[0049] The first prerequisite:

[0050] Step S120 is as follows: If the user information in the first information node and the second information node comes from different channels, the second information node is the information node currently storing the first target user information, and the second information node has not added any new associated user information, then the first node weight of the first OneID node and the second node weight of the second OneID node are determined according to the current weighting mechanism. The current weighting mechanism includes the source credibility weighting mechanism and / or the user information weighting mechanism.

[0051] In some embodiments, please refer to Figure 3 When the current weighting mechanism includes the source credibility weighting mechanism, determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the current weighting mechanism includes:

[0052] S1201a. Obtain the first channel identifier corresponding to the first information node, and obtain the second channel identifier corresponding to the second information node;

[0053] S1202a. Based on the preset correspondence between channel identifiers and weights, determine the first channel weight of the first channel identifier and the second channel weight of the second channel identifier, and use the first channel weight as the first node weight and the second channel weight as the second node weight.

[0054] In this embodiment, different weights are defined for different channels in the correspondence between channel identifiers and weights. For example, channel A corresponds to a weight of 4, and channel B corresponds to a weight of 3.

[0055] For example, such as Figure 4As shown, Channel A supplements its mobile phone number data by adding the obtained mobile phone number data (mobile: 1891111111x) to the information node openID:1 under the OneID:1 node. The information node openID:1 under OneID:1 originates from Channel A, and the information node mobile: 1891111111x under OneID:2 originates from Channel B. The weight of Channel A can be used as the weight of the OneID:1 node, and the weight of Channel B can be used as the weight of the OneID:2 node. At this point, based on the correspondence between channel identifiers and weights, the weight of Channel A is obtained by subtracting weight 4. And obtain the weight of channel B - weight 3, and use weight 4 as the weight of node OneID:1, and use weight 3 as the weight of node OneID:2. At this time, the weight of node OneID:1 is greater than the weight of node OneID:2. Node OneID:1 is determined as the target OneID node (the step of determining the target OneID node corresponds to step S130). The association between mobile:1891111111x and node OneID:1 is established, and the association between mobile:1891111111x and node OneID:2 is canceled (the step of canceling the association corresponds to step S140).

[0056] In some embodiments, please refer to Figure 5 When the current weighting mechanism includes the user information weighting mechanism, determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the current weighting mechanism includes:

[0057] S1201b: Obtain the first data type corresponding to the first information node, and obtain the second data type corresponding to the second information node;

[0058] S1202b: Based on the preset correspondence between data types and weights, determine the first data type weight of the first data type and the second data type weight of the second data type, and use the first data type weight as the first node weight and the second data type weight as the second node weight.

[0059] In this embodiment, different weights are defined for different data types in the correspondence between data types and weights. For example, mobile number (mobile) weight 4 > email weight 3 > unionID weight 2 > openID weight 1.

[0060] For example, such as Figure 6As shown, Channel A supplements mobile phone number data by adding the obtained mobile phone number data: mobile: 1891111111x to the information node openID:1 under the OneID:1 node. The data type of the information node openID:1 under the OneID:1 node is openID, and the data type of the information node mobile: 1891111111x under the OneID:2 node is mobile. According to the above correspondence between data types and weights, it can be seen that the weight of mobile is 4 > the weight of openID is 1. At this time, openID Weight 1 is used as the weight of node OneID:1, and weight 4 is used as the weight of node OneID:2. It can be seen that the weight of node OneID:2 is greater than the weight of node OneID:1. Therefore, node OneID:2 is determined as the target OneID node (the step of determining the target OneID node corresponds to step S130). An association is established between mobile:1891111111x and node OneID:2 (since mobile:1891111111x is already associated with node OneID:2, this association establishment is to maintain the relationship between mobile:1891111111x and node OneID:2). (The steps involve) canceling the association between mobile:1891111111x and the OneID:1 node. Since mobile:1891111111x is associated with information node openID:1 under the OneID:1 node, and mobile's weight is greater than openID's, in addition to canceling the association between mobile:1891111111x and the OneID:1 node, it is also necessary to cancel the association between openID:1 and the OneID:1 node, and then associate openID:1 with the OneID:2 node, thus integrating channel A information into the OneID:2 node. (The cancellation and association steps correspond to step S140).

[0061] In some embodiments, please refer to Figure 7 When the current weighting mechanism includes the source credibility weighting mechanism and the user information weighting mechanism, determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the current weighting mechanism includes:

[0062] S1201c: Obtain the first channel identifier corresponding to the first information node, and obtain the second channel identifier corresponding to the second information node;

[0063] S1202c. Based on the preset correspondence between channel identifiers and weights, determine the first channel weight of the first channel identifier and the second channel weight of the second channel identifier respectively.

[0064] S1203c: Obtain the first data type corresponding to the first information node, and obtain the second data type corresponding to the second information node;

[0065] S1204c. Based on the preset correspondence between data types and weights, determine the first data type weight of the first data type and the second data type weight of the second data type, respectively.

[0066] S1205c: Determine the weight of the first node based on the weight of the first channel and the weight of the first data type, and determine the weight of the second node based on the weight of the second channel and the weight of the second data type.

[0067] In this embodiment, determining the first node weight based on the first channel weight and the first data type weight includes: taking the higher weight among the first channel weight and the first data type weight as the first node weight; or, pre-setting a first weight for the channel weight and a second weight for the data type weight, where the first node weight = first channel weight × first weight + first data type weight × second weight.

[0068] The second node weight is determined based on the second channel weight and the second data type weight, including: taking the higher weight of the second channel weight and the second data type weight as the second node weight; or, setting a first weight for the channel weight and a second weight for the data type weight in advance, wherein the second node weight = second channel weight × first weight + second data type weight × second weight.

[0069] The second prerequisite:

[0070] like Figure 8 As shown, determining the first node weight of the first OneID node and the second node weight of the second OneID node according to a preset multi-dimensional weighting mechanism includes:

[0071] S1201d. If the user information in the first information node and the second information node comes from the same channel, and the second information node is a newly added information node associated with the first target user information, then the relationship pair frequency weighting mechanism is used as the current weighting mechanism.

[0072] S1202d: Based on the current weighting mechanism, obtain the first information quantity of the first target user information currently newly associated with the first information node, and obtain the second information quantity of the first target user information currently newly associated with the second information node;

[0073] S1203d: Determine the weight of the first node and the weight of the second node based on the quantity of the first information and the quantity of the second information, respectively.

[0074] In this embodiment, a correspondence between the number of information items and their weights can be set. The more information items there are, the greater the corresponding weight.

[0075] For example, such as Figure 9 As shown, the information node openID:1 under the OneID:1 node (where openID indicates not only the corresponding data type but also the corresponding data channel; openID is the channel identifier of the WeChat Official Account) adds 3 associated mobile phone numbers 2. The information node openID:2 under the OneID:2 node adds 1 associated mobile phone number 2. Since the number of mobile phone numbers 2 bound to openID:1 is more than the number of mobile phone numbers 2 bound to openID:2, it can be determined that the OneID:1 node has a higher weight. Specifically, the weight value corresponding to the first number of information (e.g., 3) can be determined as the weight of the first node based on the correspondence between the number of information and the weight, and the weight value corresponding to the second number of information (e.g., 1) can be determined as the weight of the second node. At this time, the weight corresponding to the OneID:1 node is greater than the weight corresponding to the OneID:2 node. The OneID:1 node is determined as the target OneID node (the step of determining the target OneID node corresponds to step S130). The mobile phone number 2 is associated with OneID:1, and the association between the mobile phone number 2 and OneID:2 is canceled (specifically, the association between the mobile phone number 2 and openID:2 under OneID:2 is canceled) (the step of canceling the association corresponds to step S140).

[0076] The third prerequisite:

[0077] like Figure 10 As shown, determining the first node weight of the first OneID node and the second node weight of the second OneID node according to a preset multi-dimensional weighting mechanism includes:

[0078] S1201e If the user information in the first information node and the second information node comes from different channels, the second information node is the information node that currently stores the first target user information, and the second information node adds a second target user information that is the same as the first information node, then the data timeliness weight mechanism is used as the current weight mechanism.

[0079] S1202e, Obtain the first association time when the first information node adds association with the first target user information, and obtain the second association time when the second information node adds association with the second target user information;

[0080] S1203e: Obtain the third data type of the second target user information in the first information node, and obtain the fourth data type of the first target user information in the second target user information;

[0081] S1204e: Determine the weight of the first node and the weight of the second node based on the first associated time, the second associated time, the third data type, the fourth data type, the preset first timeliness weight rule of the third data type, and the second timeliness weight rule of the fourth data type.

[0082] In this embodiment, different timeliness weight rules are pre-set for different data types. In some embodiments, the first association time is the time between the time when the first information node adds association with the first target user information and the creation time of the first information node, and the second association time is the time between the time when the second information node adds association with the second target user information and the creation time of the second information node.

[0083] For example, such as Figure 11 As shown, information node openID:1 under node OneID:1 adds association to mobile:1891111111x, and information node mobile:1891111111x under node OneID:2 adds association to openID:1. When the first association time and the second association time are both within 1 day, the corresponding timeliness weight rules are found according to the corresponding data types. According to the corresponding timeliness weight rules, the weight corresponding to the mobile number (information node mobile) adding association data within one day is 3, and the weight corresponding to the openID:1 adding association data within one day is 4. At this time, the information node openID:1 under node OneID:1 has a higher weight, so node OneID:1 is determined as the target node. At this time, mobile:1891111111x is associated with node OneID:1, and the association between mobile:1891111111x and node OneID:2 is canceled.

[0084] For example, when the first association time and the second association time exceed one day, the corresponding timeliness weight rules are found according to the corresponding data types. According to the corresponding timeliness weight rules, the weight corresponding to supplementing the association data for a mobile number that exceeds one day is 4, and the weight corresponding to supplementing the association data for openID:1 that exceeds one day is 3. At this time, the information node mobile:1891111111x under the OneID:2 node has a higher weight, so the OneID:2 node is determined as the target node. At this time, mobile:1891111111x is associated with the OneID:2 node (since mobile:1891111111x is already associated with the OneID:2 node, the association is established here to maintain the mobile The association between mobile:1891111111x and OneID:2 node is cancelled, and the association between mobile:1891111111x and OneID:1 node is also cancelled. Since mobile:1891111111x is associated with information node openID:1 under OneID:1 node, and mobile's weight is greater than openID's weight, in addition to cancelling the association between mobile:1891111111x and OneID:1 node, the association between openID:1 and OneID:1 node also needs to be cancelled, and openID:1 should be associated with OneID:2 node, thus integrating channel A information into OneID:2 node. (The cancellation and association steps correspond to step S140).

[0085] S130. Determine the target OneID node from the first OneID node and the second OneID node based on the weight of the first node and the weight of the second node.

[0086] Specifically, if the weight of the first node is greater than the weight of the second node, then the first OneID node is determined as the target OneID node; if the weight of the first node is less than the weight of the second node, then the second OneID node is determined as the target OneID node.

[0087] S140. Associate the first target user information with the target OneID node, and cancel the association between the first target user information and the non-target OneID node, wherein the non-target OneID node is the OneID node between the first OneID node and the second OneID node excluding the target OneID node.

[0088] Specifically, the first target user information is associated with the target OneID node, that is, an information node corresponding to the first target user information is generated (the information node stores the first target user information), and the generated information node is connected to the target OneID node.

[0089] In some embodiments, when adding new associated target user information to an information node, if the weight of the target user information is greater than the weight of the corresponding information node, and it is necessary to cancel the association between the target user information and the corresponding OneID node, in addition to canceling the association between the target user information and the corresponding OneID node, it is also necessary to cancel the association between the corresponding information node and the corresponding OneID node, and then associate the canceled information node with the target OneID node (e.g., ...). Figure 6 (As shown).

[0090] In summary, when a first information node in the graph database is newly associated with first target user information, it is determined whether a second information node corresponding to the first target user information exists in the graph database. The graph database includes multiple OneID nodes, and different OneID nodes are connected to at least one information node belonging to the same user. Different information nodes under the same OneID node store different user information of the same user. If a second information node exists, the first node weight of the first OneID node and the second node weight of the second OneID node are determined according to a preset multi-dimensional weight mechanism. The first OneID node is the OneID node currently associated with the first information node, and the second OneID node is the OneID node currently associated with the second information node. The multi-dimensional weight mechanism includes a source credibility weight mechanism, a relation pair frequency weight mechanism, a user information weight mechanism, and a data timeliness weight mechanism. A target OneID node is determined from the first OneID node and the second OneID node according to the first node weight and the second node weight. The first target user information is associated with the target OneID node, and the association between the first target user information and non-target OneID nodes is canceled. The non-target OneID node is the OneID node between the first OneID node and the second OneID node excluding the target OneID node. This application embodiment uses a multi-dimensional weighting mechanism to accurately identify the OneID node to which the newly added associated user information belongs, thereby improving the data fusion effect.

[0091] Figure 12 This is a schematic block diagram of a data integration device 1200 based on a multi-dimensional weighting mechanism provided in an embodiment of this application. Figure 12 As shown, corresponding to the above-described data integration method based on a multi-dimensional weighting mechanism, this application also provides a data integration apparatus 1200 based on a multi-dimensional weighting mechanism. This data integration apparatus 1200 includes a unit for executing the above-described data integration method based on a multi-dimensional weighting mechanism, and can be configured in a terminal or server. Specifically, please refer to... Figure 12 The data integration device 1200 based on a multi-dimensional weighting mechanism includes a transceiver unit 1201 and a processing unit 1202, wherein:

[0092] Transceiver unit 1201: The user obtains the newly added associated first target user information from the first information node;

[0093] Processing unit 1202 is configured to, when a first information node in the graph database is newly associated with first target user information, determine whether a second information node corresponding to the first target user information exists in the graph database. The graph database includes multiple OneID nodes, different OneID nodes are connected to at least one information node belonging to the same user, and different information nodes under the same OneID node store different user information of the same user. If a second information node exists, the first node weight of the first OneID node and the second node weight of the second OneID node are determined according to a preset multi-dimensional weighting mechanism. The first OneID node is the OneID node currently associated with the first information node. The second OneID node is the OneID node currently associated with the second information node. The multi-dimensional weighting mechanism includes a source credibility weighting mechanism, a relationship pair frequency weighting mechanism, a user information weighting mechanism, and a data timeliness weighting mechanism. A target OneID node is determined from the first OneID node and the second OneID node based on the weight of the first node and the weight of the second node. The first target user information is associated with the target OneID node, and the association between the first target user information and non-target OneID nodes is canceled. The non-target OneID node is any OneID node between the first OneID node and the second OneID node other than the target OneID node.

[0094] In some embodiments, when the processing unit 1202 performs the step of determining the first node weight of the first OneID node and the second node weight of the second OneID node according to a preset multi-dimensional weighting mechanism, it is specifically used for:

[0095] If the user information in the first information node and the second information node comes from different channels, the second information node is the information node currently storing the first target user information, and the second information node has not added any new associated user information, then the first node weight of the first OneID node and the second node weight of the second OneID node are determined according to the current weighting mechanism, wherein the current weighting mechanism includes the source credibility weighting mechanism and / or the user information weighting mechanism.

[0096] In some embodiments, when the current weighting mechanism includes the source credibility weighting mechanism, the processing unit 1202, when performing the step of determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the current weighting mechanism, is specifically used for:

[0097] Obtain the first channel identifier corresponding to the first information node, and obtain the second channel identifier corresponding to the second information node; according to the preset correspondence between channel identifier and weight, determine the first channel weight of the first channel identifier and the second channel weight of the second channel identifier, and use the first channel weight as the first node weight and the second channel weight as the second node weight.

[0098] In some embodiments, when the current weighting mechanism includes the user information weighting mechanism, the processing unit 1202, when performing the step of determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the current weighting mechanism, is specifically configured to:

[0099] Obtain the first data type corresponding to the first information node, and obtain the second data type corresponding to the second information node; according to the preset correspondence between data type and weight, determine the first data type weight of the first data type and the second data type weight of the second data type, and use the first data type weight as the weight of the first node and the second data type weight as the weight of the second node.

[0100] In some embodiments, when the current weighting mechanism includes the source credibility weighting mechanism and the user information weighting mechanism, the processing unit 1202, when performing the step of determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the current weighting mechanism, is specifically used for:

[0101] Obtain the first channel identifier corresponding to the first information node, and obtain the second channel identifier corresponding to the second information node; determine the first channel weight of the first channel identifier and the second channel weight of the second channel identifier according to the preset correspondence between channel identifier and weight; obtain the first data type corresponding to the first information node, and obtain the second data type corresponding to the second information node; determine the first data type weight of the first data type and the second data type weight of the second data type according to the preset correspondence between data type and weight; determine the first node weight according to the first channel weight and the first data type weight; and determine the second node weight according to the second channel weight and the second data type weight.

[0102] In some embodiments, when the processing unit 1202 performs the step of determining the first node weight of the first OneID node and the second node weight of the second OneID node according to a preset multi-dimensional weighting mechanism, it is specifically used for:

[0103] If the user information in the first information node and the second information node originates from the same channel, and the second information node is a newly added information node associated with the first target user information, then the relationship pair frequency weighting mechanism is used as the current weighting mechanism; based on the current weighting mechanism, the first information quantity of the newly added first target user information associated with the first information node and the second information quantity of the newly added first target user information associated with the second information node are obtained; the weight of the first node and the weight of the second node are determined according to the first information quantity and the second information quantity, respectively.

[0104] In some embodiments, when the processing unit 1202 performs the step of determining the first node weight of the first OneID node and the second node weight of the second OneID node according to a preset multi-dimensional weighting mechanism, it is specifically used for:

[0105] If the user information in the first information node and the second information node originates from different channels, and the second information node is the current information node storing the first target user information, and the second information node adds a new association with the same second target user information as the first information node, then the data timeliness weight mechanism is used as the current weight mechanism; the first association time when the first information node adds a new association with the first target user information is obtained, and the second association time when the second information node adds a new association with the second target user information is obtained; the third data type of the second target user information in the first information node is obtained, and the fourth data type of the first target user information in the second target user information is obtained; the weight of the first node and the weight of the second node are determined according to the first association time, the second association time, the third data type, the fourth data type, the preset first timeliness weight rule of the third data type, and the second timeliness weight rule of the fourth data type.

[0106] In summary, the embodiments of this application, through a multi-dimensional weighting mechanism, can accurately identify the OneID node to which the newly added associated user information belongs, thereby improving the data fusion effect.

[0107] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the data integration device 1200 based on the multi-dimensional weight mechanism and each unit can be referred to the corresponding description in the foregoing method embodiments. For the sake of convenience and brevity, it will not be repeated here.

[0108] The aforementioned data integration device based on a multi-dimensional weighting mechanism can be implemented as a computer program, which can, for example... Figure 13 It runs on the computer device shown.

[0109] Please see Figure 13 , Figure 13 This is a schematic block diagram of a computer device provided in an embodiment of this application. The computer device 1300 can be a terminal or a server.

[0110] See Figure 13 The computer device 1300 includes a processor 1302, a memory, and a network interface 1305 connected via a system bus 1301. The memory may include a non-volatile storage medium 1303 and internal memory 1304.

[0111] The non-volatile storage medium 1303 may store an operating system 13031 and a computer program 13032. The computer program 13032 includes program instructions that, when executed, cause the processor 1302 to perform a data integration method based on a multi-dimensional weighting mechanism.

[0112] The processor 1302 provides computing and control capabilities to support the operation of the entire computer device 1300.

[0113] The internal memory 1304 provides an environment for the execution of the computer program 13032 in the non-volatile storage medium 1303. When the computer program 13032 is executed by the processor 1302, the processor 1302 can execute a data integration method based on a multi-dimensional weighting mechanism.

[0114] This network interface 1305 is used for network communication with other devices. Those skilled in the art will understand that... Figure 13 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 1300 to which the present application is applied. The specific computer device 1300 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0115] The processor 1302 is used to run a computer program 13032 stored in the memory to perform the following steps:

[0116] When a first information node in the graph database is newly associated with first target user information, it is determined whether there is a second information node in the graph database corresponding to the first target user information. The graph database includes multiple OneID nodes, and different OneID nodes are connected to at least one information node belonging to the same user. Different information nodes under the same OneID node store different user information of the same user.

[0117] If the second information node exists, the first node weight of the first OneID node and the second node weight of the second OneID node are determined according to the preset multi-dimensional weight mechanism. The first OneID node is the OneID node currently associated with the first information node, and the second OneID node is the OneID node currently associated with the second information node. The multi-dimensional weight mechanism includes the source credibility weight mechanism, the relationship pair count weight mechanism, the user information weight mechanism, and the data timeliness weight mechanism.

[0118] The target OneID node is determined from the first OneID node and the second OneID node based on the first node weight and the second node weight;

[0119] The first target user information is associated with the target OneID node, and the association between the first target user information and a non-target OneID node is canceled. The non-target OneID node is the OneID node between the first OneID node and the second OneID node, excluding the target OneID node.

[0120] It should be understood that in the embodiments of this application, the processor 1302 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0121] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0122] Therefore, this application also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When executed by a processor, the program instructions cause the processor to perform the following steps:

[0123] When a first information node in the graph database is newly associated with first target user information, it is determined whether there is a second information node in the graph database corresponding to the first target user information. The graph database includes multiple OneID nodes, and different OneID nodes are connected to at least one information node belonging to the same user. Different information nodes under the same OneID node store different user information of the same user.

[0124] If the second information node exists, the first node weight of the first OneID node and the second node weight of the second OneID node are determined according to the preset multi-dimensional weight mechanism. The first OneID node is the OneID node currently associated with the first information node, and the second OneID node is the OneID node currently associated with the second information node. The multi-dimensional weight mechanism includes the source credibility weight mechanism, the relationship pair count weight mechanism, the user information weight mechanism, and the data timeliness weight mechanism.

[0125] The target OneID node is determined from the first OneID node and the second OneID node based on the first node weight and the second node weight;

[0126] The first target user information is associated with the target OneID node, and the association between the first target user information and a non-target OneID node is canceled. The non-target OneID node is the OneID node between the first OneID node and the second OneID node, excluding the target OneID node.

[0127] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0128] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0129] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0130] The steps in the methods of this application embodiment can be adjusted, merged, or deleted according to actual needs. The units in the apparatus of this application embodiment can be merged, divided, or deleted according to actual needs. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0131] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0132] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A data integration method based on a multi-dimension weight mechanism, characterized in that, The method comprises the following steps: When a first information node in a graph database newly adds associated first target user information, it is determined whether a second information node corresponding to the first target user information exists in the graph database, the graph database comprises a plurality of OneID nodes, different OneID nodes are connected with at least one information node belonging to the same user, and different information nodes under the same OneID node store different user information of the same user, and the second information node is an information node storing the first target user information or newly adding associated first target user information; If the second information node exists, the first node weight of a first OneID node and the second node weight of a second OneID node are determined according to a current weight mechanism in a preset multi-dimensional weight mechanism, the first OneID node is a OneID node currently associated with the first information node, the second OneID node is a OneID node currently associated with the second information node, and the multi-dimensional weight mechanism comprises a source credibility weight mechanism, a relationship pair number weight mechanism, a user information weight mechanism and a data timeliness weight mechanism; When the user information in the first information node and the second information node comes from different channels, the second information node is an information node currently storing the first target user information, and the second information node currently has no newly added associated user information, the current weight mechanism comprises the source credibility weight mechanism and / or the user information weight mechanism; when the user information in the first information node and the second information node comes from the same channel, and the second information node is an information node newly adding associated first target user information, the current weight mechanism is the relationship pair number weight mechanism; when the user information in the first information node and the second information node comes from different channels, the second information node is an information node currently storing the first target user information, and the second information node newly adds associated second target user information same as the first information node, the current weight mechanism is the data timeliness weight mechanism; A target OneID node is determined from the first OneID node and the second OneID node according to the first node weight and the second node weight. associating the first target user information to the target OneID node and canceling association of the first target user information with a non-target OneID node, the non-target OneID node being an OneID node other than the target OneID node among the first OneID node and the second OneID node; when the weight of the first target user information is greater than the weight of a corresponding information node, and the association of the first target user information with the corresponding OneID node needs to be canceled, canceling the association of the first target user information with the corresponding OneID node, canceling the association of the corresponding information node with the corresponding OneID node, and associating the canceled information node with the target OneID node; when the current weight mechanism includes the user information weight mechanism, determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the current weight mechanism, comprising: obtaining a first data type corresponding to the first information node, and obtaining a second data type corresponding to the second information node; determining a first data type weight of the first data type and a second data type weight of the second data type according to a preset corresponding relationship between data types and weights, and taking the first data type weight as the first node weight and the second data type weight as the second node weight; when the current weight mechanism includes the source credibility weight mechanism and the user information weight mechanism, the determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the current weight mechanism in the preset multi-dimensional weight mechanism, comprising: obtaining a first channel identifier corresponding to the first information node, and obtaining a second channel identifier corresponding to the second information node; determining a first channel weight of the first channel identifier and a second channel weight of the second channel identifier according to a preset corresponding relationship between channel identifiers and weights; obtaining a first data type corresponding to the first information node, and obtaining a second data type corresponding to the second information node; determining a first data type weight of the first data type and a second data type weight of the second data type according to a preset corresponding relationship between data types and weights; previously setting a first weight for the channel weight and a second weight for the data type weight, determining the first node weight according to the first channel weight and the first data type weight, comprising: first node weight = first channel weight × first weight + first data type weight × second weight, and determining the second node weight according to the second channel weight and the second data type weight, comprising: second node weight = second channel weight × first weight + second data type weight × second weight; the determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the current weight mechanism in the preset multi-dimensional weight mechanism, comprising: If the user information in the first information node and the second information node comes from different channels, the second information node is an information node currently storing the first target user information, and the second information node newly associates the same second target user information as the first information node, the data timeliness weight mechanism is taken as the current weight mechanism; A first association time when the first information node newly associates the first target user information is obtained, and a second association time when the second information node newly associates the second target user information is obtained; A third data type of the second target user information in the first information node is obtained, and a fourth data type of the first target user information in the second target user information is obtained; The first association time is a time length between a time when the first information node newly associates the first target user information and a creation time of the first information node, and the second association time is a time length between a time when the second information node newly associates the second target user information and a creation time of the second information node. The first association time, the second association time, the third data type, the fourth data type, a first timeliness weight rule of the third data type and a second timeliness weight rule of the fourth data type are used to determine the first node weight and the second node weight.

2. The method of claim 1, wherein, When the current weight mechanism includes the source credibility weight mechanism, the first node weight of the first OneID node and the second node weight of the second OneID node are determined according to the current weight mechanism in the preset multi-dimensional weight mechanism, including: A first channel identifier corresponding to the first information node is obtained, and a second channel identifier corresponding to the second information node is obtained; According to a preset corresponding relationship between a channel identifier and a weight, a first channel weight of the first channel identifier and a second channel weight of the second channel identifier are determined respectively, and the first channel weight is taken as the first node weight and the second channel weight is taken as the second node weight.

3. The method of claim 1, wherein, The first node weight of the first OneID node and the second node weight of the second OneID node are determined according to the current weight mechanism in the preset multi-dimensional weight mechanism, including: If the user information in the first information node and the second information node comes from the same channel, and the second information node is an information node newly associating the first target user information, the relationship pair times weight mechanism is taken as the current weight mechanism; Based on the current weight mechanism, a first information quantity of the first target user information newly associated to the first information node is obtained, and a second information quantity of the first target user information newly associated to the second information node is obtained; The first node weight and the second node weight are determined according to the first information quantity and the second information quantity respectively.

4. A data integration apparatus based on a multi-dimensional weight mechanism, characterized by, Including: A transceiving unit, which is configured to obtain first target user information newly associated by a first information node; The processing unit is configured to determine whether a second information node corresponding to the first target user information exists in the graph database when a first information node in the graph database newly associates the first target user information, the graph database comprising a plurality of OneID nodes, different OneID nodes being connected with at least one information node belonging to a same user, and different information nodes under a same OneID node storing different user information of the same user, the second information node being an information node storing the first target user information or newly associating the first target user information; if the second information node exists, determining a first node weight of a first OneID node and a second node weight of a second OneID node according to a current weight mechanism in a preset multi-dimensional weight mechanism, the first OneID node being a OneID node currently associated with the first information node, the second OneID node being a OneID node currently associated with the second information node, the multi-dimensional weight mechanism comprising a source credibility weight mechanism, a relationship pair number weight mechanism, a user information weight mechanism, and a data timeliness weight mechanism; and determining a target OneID node from the first OneID node and the second OneID node according to the first node weight and the second node weight; associating the first target user information to the target OneID node and canceling the association between the first target user information and a non-target OneID node, the non-target OneID node being a OneID node other than the target OneID node among the first OneID node and the second OneID node; wherein, when the weight of the first target user information is greater than the weight of a corresponding information node, and the association between the first target user information and a corresponding OneID node needs to be canceled, canceling the association between the first target user information and the corresponding OneID node, canceling the association between the corresponding information node and the corresponding OneID node, and associating the canceled information node to the target OneID node. When the user information in the first information node and the second information node comes from different channels, the second information node is an information node currently storing the first target user information, and the second information node does not newly associate user information at present, the current weight mechanism includes the source credibility weight mechanism and / or the user information weight mechanism; when the user information in the first information node and the second information node comes from the same channel, and the second information node newly associates the first target user information, the current weight mechanism is the relationship pair times weight mechanism; when the user information in the first information node and the second information node comes from different channels, the second information node is an information node currently storing the first target user information, and the second information node newly associates the second target user information same as the first information node, the current weight mechanism is the data timeliness weight mechanism; When the current weight mechanism includes the user information weight mechanism, the processing unit, when performing the step of determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the current weight mechanism, is specifically configured to: obtain a first data type corresponding to the first information node, and obtain a second data type corresponding to the second information node; determine a first data type weight of the first data type and a second data type weight of the second data type according to a preset corresponding relationship between data types and weights, and take the first data type weight as the first node weight and take the second data type weight as the second node weight; When the current weight mechanism includes the source credibility weight mechanism and the user information weight mechanism, the processing unit, when performing the step of determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the current weight mechanism in the preset multi-dimensional weight mechanism, is specifically configured to: obtain a first channel identifier corresponding to the first information node, and obtain a second channel identifier corresponding to the second information node; determine a first channel weight of the first channel identifier and a second channel weight of the second channel identifier according to a preset corresponding relationship between channel identifiers and weights; obtain a first data type corresponding to the first information node, and obtain a second data type corresponding to the second information node; determine a first data type weight of the first data type and a second data type weight of the second data type according to a preset corresponding relationship between data types and weights; determine a first data type weight of the first data type and a second data type weight of the second data type according to a preset corresponding relationship between data types and weights; The first node weight is determined according to the first channel weight and the first data type weight, including: first node weight = first channel weight * first weight + first data type weight * second weight, and the second node weight is determined according to the second channel weight and the second data type weight, including: second node weight = second channel weight * first weight + second data type weight * second weight. When the processing unit executes the step of determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the current weight mechanism in the preset multi-dimensional weight mechanism, it is specifically used for: If the user information in the first information node and the second information node comes from different channels, the second information node is an information node currently storing the first target user information, and the second information node newly associates the second target user information same as the first information node, the data timeliness weight mechanism is taken as the current weight mechanism; A first association time when the first information node newly associates the first target user information is obtained, and a second association time when the second information node newly associates the second target user information is obtained; A third data type of the second target user information in the first information node is obtained, and a fourth data type of the first target user information in the second target user information is obtained; The first node weight and the second node weight are determined according to the first association time, the second association time, the third data type, the fourth data type, a first timeliness weight rule of the third data type and a second timeliness weight rule of the fourth data type, the first association time is the time length between the time when the first information node newly associates the first target user information and the creation time of the first information node, and the second association time is the time length between the time when the second information node newly associates the second target user information and the creation time of the second information node.

5. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to realize the data integration method based on the multi-dimensional weight mechanism in any one of claims 1-3.

6. A storage medium, characterized by The storage medium stores a computer program, the computer program includes program instructions, and the program instructions make the processor execute the data integration method based on the multi-dimensional weight mechanism in any one of claims 1-3 when the processor executes the computer program.

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