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

Abstract

The embodiment of the invention discloses a data integration method and device based on a multi-dimensional weight mechanism, equipment and a medium. The method comprises the following steps: when a first information node in a graph database is newly added and associated with first target user information, judging whether a second information node corresponding to the first target user information exists in the graph database or not; if yes, the first node weight of the first OneID node and the second node weight of a second OneID node are determined according to a preset multi-dimensional weight mechanism, and the second OneID node is the 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 cancelling the association between the first target user information and the non-target OneID node. By implementing the method provided by the embodiment of the invention, the data fusion effect can be improved.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and particularly to a data integration method, apparatus, device and medium based on a multi-dimensional weight mechanism. Background Art

[0002] With the development of Internet technology, merchants have more and more marketing channels. Understanding consumer data helps merchants further understand consumers in depth, so as to optimize marketing strategies and improve business performance.

[0003] However, due to the non-interoperability of user data from different channels, and there may be overlapping data in user data from the same channel (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 this user information should be associated with through existing technologies, affecting the data fusion effect. Summary of the Invention

[0004] Embodiments of this application provide a data integration method, apparatus, device and medium based on a multi-dimensional weight mechanism, which can accurately identify the OneID node to which the newly added associated user information belongs, and improve the data fusion effect.

[0005] In a first aspect, embodiments of this application provide a data integration method based on a multi-dimensional weight mechanism, which includes: When a first information node in a graph database newly associates with a first target user information, determine whether there is a second information node corresponding to the first target user information in the graph database. The graph database includes multiple OneID nodes, and different OneID nodes are connected with at least one information node belonging to the same user, and different user information of the same user is stored in different information nodes under the same OneID node; If the second information node exists, determine 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 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 relationship pair times weight mechanism, a user information weight mechanism, and a data timeliness weight mechanism; Determine 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; Associate the first target user information with the target OneID node, and cancel the association between the first target user information and non-target OneID nodes. The non-target OneID nodes are the OneID nodes other than the target OneID node among the first OneID node and the second OneID node.

[0006] In a second aspect, an embodiment of the present application further provides a data integration device based on a multi-dimensional weight mechanism, which includes: A transceiver unit for obtaining the first target user information newly associated with the first information node by a user; A processing unit, configured to, when the first information node in the graph database newly associates with the first target user information, determine whether there is a second information node corresponding to the first target user information 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, and different user information of the same user is stored in different information nodes under the same OneID node. If the second information node exists, determine a first node weight of the first OneID node and a second node weight of the second OneID node 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 relationship pair number weight mechanism, a user information weight mechanism, and a data timeliness weight mechanism. Determine 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. Associate the first target user information with the target OneID node, and cancel the association between the first target user information and non-target OneID nodes. The non-target OneID nodes are the OneID nodes other than the target OneID node among the first OneID node and the second OneID node.

[0007] In a third aspect, an embodiment of the present application further provides a computer device, which includes a memory and a processor. A computer program is stored on the memory, and when the processor executes the computer program, the above method is implemented.

[0008] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium. The storage medium stores a computer program, and the computer program includes program instructions. When the program instructions are executed by a processor, the above method can be implemented.

[0009] The embodiments of the present application provide a data integration method, apparatus, device and medium based on a multi-dimensional weight mechanism. Among them, the method includes: when a first information node in a graph database newly associates with first target user information, determining whether there is a second information node corresponding to the first target user information in the graph database, where 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 user information of the same user is stored in different information nodes under the same OneID node; 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 preset multi-dimensional weight mechanism, where 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, and the multi-dimensional weight mechanism includes a source credibility weight mechanism, a relationship pair times 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 non-target OneID nodes, where the non-target OneID nodes are the OneID nodes other than the target OneID node among the first OneID node and the second OneID node. Through the multi-dimensional weight mechanism, the embodiments of the present application can accurately identify the OneID node to which the newly associated user information currently belongs, and improve the data fusion effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0011] Figure 1 It is a schematic diagram of ordinary integration calculation in a graph database; Figure 2 It is a schematic flowchart of the data integration method based on the multi-dimensional weight mechanism provided by the embodiments of the present application; Figure 3 It is a schematic sub-flowchart of the data integration method based on the multi-dimensional weight mechanism provided by the embodiments of the present application; Figure 4 It is a schematic diagram of a specific data integration scenario provided by the embodiments of the present application; Figure 5Another schematic diagram of a sub - process of the data integration method based on a multi - dimensional weight mechanism provided by an embodiment of the present application; Figure 6 Another schematic diagram of a specific data integration scenario provided by an embodiment of the present application; Figure 7 Another schematic diagram of a sub - process of the data integration method based on a multi - dimensional weight mechanism provided by an embodiment of the present application; Figure 8 Another schematic diagram of a sub - process of the data integration method based on a multi - dimensional weight mechanism provided by an embodiment of the present application; Figure 9 Another schematic diagram of a specific data integration scenario provided by an embodiment of the present application; Figure 10 Another schematic diagram of a sub - process of the data integration method based on a multi - dimensional weight mechanism provided by an embodiment of the present application; Figure 11 Another schematic diagram of a specific data integration scenario provided by an embodiment of the present application; Figure 12 Schematic block diagram of a data integration device based on a multi - dimensional weight mechanism provided by an embodiment of the present application; Figure 13 Schematic block diagram of a computer device provided by an embodiment of the present application. Detailed implementation manners

[0012] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0013] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprise" indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0014] It should also be understood that the terms used in this specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in this specification of the present application and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0015] It should also be further understood that the term "and / or" used in the specification and appended claims of the present application refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0016] Embodiments of the present application provide a data integration method, device, equipment and medium based on a multi-dimensional weight mechanism.

[0017] The execution subject of the data integration method based on the multi-dimensional weight mechanism may be the data integration device provided by the embodiments of the present application, or a computer device integrated with the data integration device based on the multi-dimensional weight mechanism. Among them, the data integration device based on the multi-dimensional weight mechanism may be implemented in a hardware or software manner, and the computer device may be a terminal or a server.

[0018] As Figure 1 shown, Figure 1 For ordinary integration calculation in the prior art, in the existing graph database, when OpenID: 1 newly associates with mobile phone number 1, during integration, the newly added mobile phone number 1 is directly integrated into the OneID: 1 node corresponding to OpenID: 1. If there are other OneID nodes that also associate with this mobile phone number 1, there will be a situation where different users have the same mobile phone number, and the data fusion effect is poor.

[0019] Therefore, embodiments of the present application provide a data integration method based on a multi-dimensional weight mechanism. Through this method, it can be determined which OneID node the currently newly added user information belongs to, avoiding the situation where the same user information is associated with different OneID nodes and improving the data fusion effect.

[0020] Figure 2 is a schematic flowchart of the data integration method based on the multi-dimensional weight mechanism provided by the embodiments of the present application. As Figure 2 shown, the method includes the following steps S110 - S140.

[0021] S110. When a first information node in the graph database newly associates with first target user information, determine whether there is a second information node corresponding to the first target user information in the graph database. The graph database includes multiple OneID nodes, different OneID nodes are connected with at least one information node belonging to the same user, and different user information of the same user is stored in different information nodes under the same OneID node.

[0022] In this embodiment, when a first information node in the graph database newly associates with 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 corresponding to the first target user information in the graph database. Here, the second information node corresponding to the first target user information refers to a node that stores the first target user information or an information node that also newly associates with the first target user information.

[0023] S120. If there is the second information node, determine 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. 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 relationship pair times weight mechanism, a user information weight mechanism, and a data timeliness weight mechanism.

[0024] In this embodiment, if there is a second information node, it means that there is duplicate user information of the first target user information in the graph database. At this time, it is necessary to clarify which OneID node the first target user information belongs to based on the multi-dimensional weight mechanism.

[0025] Specifically, this embodiment can automatically determine the current weight mechanism from the multi-dimensional weight mechanism according to different preconditions. This embodiment includes at least three preconditions.

[0026] Among them: The first precondition 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 currently storing the first target user information, and the second information node has not newly associated with user information at present. At this time, the current weight mechanism includes the source credibility weight mechanism and / or the user information weight mechanism. Whether to specifically use the source credibility weight mechanism or the user information weight mechanism, or both the source credibility weight mechanism and the user information weight mechanism, can be set according to user selection.

[0027] The second precondition 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 the information node that newly associates with the first target user information. At this time, the current weight mechanism is the relationship pair times weight mechanism.

[0028] 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 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. At this time, the current weight mechanism is the data timeliness weight mechanism.

[0029] The following will describe this step in detail for these three prerequisites respectively.

[0030] The first prerequisite: 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 currently has no newly associated user information, then determine 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. The current weight mechanism includes the source credibility weight mechanism and / or the user information weight mechanism.

[0031] In some embodiments, refer to Figure 3 , when the current weight mechanism includes the source credibility 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 includes: S1201a. Obtain the first channel identifier corresponding to the first information node, and obtain the second channel identifier corresponding to the second information node; S1202a. According to the preset corresponding relationship between the channel identifier and the weight, determine the first channel weight of the first channel identifier and the second channel weight of the second channel identifier respectively, and use the first channel weight as the first node weight and the second channel weight as the second node weight.

[0032] In this embodiment, different weights are defined for different channels in the corresponding relationship between the channel identifier and the weight. For example, channel A corresponds to a weight of 4, and channel B corresponds to a weight of 3.

[0033] For example, as Figure 4As shown, Channel A supplements mobile phone number data and newly associates the obtained mobile phone number data: mobile: 1891111111x with the information node openID: 1 under OneID: 1. The information node openID: 1 under OneID: 1 comes from Channel A, and the information node mobile: 1891111111x under OneID: 2 comes from Channel B. The weight of Channel A can be used as the weight of OneID: 1 node, and the weight of Channel B can be used as the weight of OneID: 2 node. At this time, according to the correspondence between the channel identifier and the weight, obtain the weight of Channel A - Weight 4, and obtain the weight of Channel B - Weight 3, and use Weight 4 as the weight of OneID: 1 node and Weight 3 as the weight of OneID: 2 node. At this time, the weight of OneID: 1 node is greater than the weight of OneID: 2 node. Determine OneID: 1 node as the target OneID node (the step of determining the target OneID node corresponds to step S130), establish an association between mobile: 1891111111x and OneID: 1 node, and cancel the association between mobile: 1891111111x and OneID: 2 node (the step of canceling the association corresponds to step S140).

[0034] In some embodiments, please refer to Figure 5 , 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 includes: S1201b. Obtain the first data type corresponding to the first information node and obtain the second data type corresponding to the second information node; S1202b. According to the preset correspondence between the data type and the weight, respectively 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.

[0035] In this embodiment, different weights are defined for different data types in the correspondence between the data type and the weight. For example, mobile phone number (mobile) Weight 4 > email Weight 3 > unionID Weight 2 > openID Weight 1.

[0036] For example, as Figure 6As shown in the figure, Channel A supplements mobile phone number data, and associates the obtained mobile phone number data: mobile: 1891111111x with the information node openID: 1 under OneID: 1 node. The data type of the information node openID: 1 under OneID: 1 node is openID, and the data type of the information node mobile: 1891111111x under OneID: 2 node is mobile. According to the corresponding relationship between the above data types and weights, it can be known that the weight of mobile 4 > the weight of openID 1. At this time, the weight of openID 1 is used as the weight of OneID: 1 node, and the weight of mobile 4 is used as the weight of OneID: 2 node. It can be seen that the weight of OneID: 2 node is greater than the weight of OneID: 1 node. Determine OneID: 2 node as the target OneID node (the step of determining the target OneID node corresponds to step S130), establish an association between mobile: 1891111111x and OneID: 2 node (since mobile: 1891111111x is already associated with OneID: 2 node, the establishment of the association at this time is to maintain the association between mobile: 1891111111x and OneID: 2 node), and cancel the association between mobile: 1891111111x and OneID: 1 node. Among them, since under OneID: 1 node, mobile: 1891111111x has an association relationship with the information node openID: 1, and the weight of mobile is greater than the weight of openID, at this time, in addition to canceling the association between mobile: 1891111111x and OneID: 1 node, it is also necessary to cancel the association between openID: 1 and OneID: 1 node, and associate openID: 1 with OneID: 2 node, that is, integrate the information of Channel A into OneID: 2 node. (The steps of cancellation and association correspond to step S140).

[0037] In some embodiments, please refer to Figure 7 When the current weight mechanism includes the source credibility weight mechanism and 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 includes: S1201c. Obtain the first channel identifier corresponding to the first information node, and obtain the second channel identifier corresponding to the second information node; S1202c. According to the preset corresponding relationship between the channel identifier and the weight, respectively determine the first channel weight of the first channel identifier and the second channel weight of the second channel identifier; S1203c. Obtain the first data type corresponding to the first information node and the second data type corresponding to the second information node; S1204c. According to the preset correspondence between data types and weights, respectively determine the first data type weight of the first data type and the second data type weight of the second data type; S1205c. 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.

[0038] In this embodiment, determining the first node weight according to 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, setting a first weight for the channel weight in advance and a second weight for the data type weight in advance, and the first node weight = the first channel weight × the first weight + the first data type weight × the second weight; Determining the second node weight according to the second channel weight and the second data type weight includes: taking the higher weight among the second channel weight and the second data type weight as the second node weight; or, setting a first weight for the channel weight in advance and a second weight for the data type weight in advance, and the second node weight = the second channel weight × the first weight + the second data type weight × the second weight.

[0039] The second prerequisite: As Figure 8 shown, determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the preset multi-dimensional weight mechanism includes: 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 an information node newly associated with the first target user information, then use the relationship pair times weight mechanism as the current weight mechanism; S1202d. Based on the current weight 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; S1203d. Determine the first node weight and the second node weight respectively according to the first information quantity and the second information quantity.

[0040] In this embodiment, the correspondence between information quantity and weight can be set, and the more the information quantity (number of items), the greater the corresponding weight.

[0041] For example, as Figure 9 shown, for the information node openID:1 under the OneID:1 node (where the openID indicates not only the corresponding data type but also the corresponding data channel, and the openID is the channel identifier of the WeChat official account), 3 mobile phone numbers 2 are newly associated. For the information node openID:2 under the OneID:2 node, 1 mobile phone number 2 is newly associated. Since the number of mobile phone numbers 2 bound to openID:1 is more than that bound to openID:2, it can be determined that the weight of the OneID:1 node is higher. Specifically, the weight value corresponding to the first information quantity (such as 3) can be determined as the first node weight according to the corresponding relationship between the information quantity and the weight, and the weight value corresponding to the second information quantity (such as 1) can be determined as the second node weight. 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 cancelled (specifically, the association with openID:2 under OneID:2 is cancelled) (the step of cancelling the association corresponds to step S140).

[0042] The third precondition: As Figure 10 shown, determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the preset multi-dimensional weight mechanism includes: 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 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, then the data timeliness weight mechanism is used as the current weight mechanism; S1202e. Obtain the first association time when the first information node newly associates the first target user information, and obtain the second association time when the second information node newly associates the second target user information; 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; S1204e. Determine the first node weight and the second node weight according to the first association time, the second association time, the third data type, the fourth data type, the first timeliness weight rule of the preset third data type, and the second timeliness weight rule of the fourth data type.

[0043] In this embodiment, different timeliness weight rules are preset for different data types. In some embodiments, the above first association time is the duration between the time when the first information node newly associates with the first target user information and the creation time of the first information node, and the second association time is the duration between the time when the second information node newly associates with the second target user information and the creation time of the second information node.

[0044] For example, as Figure 11 shown, under the OneID: 1 node, the information node openID: 1 newly associates with mobile: 1891111111x, and under the OneID: 2 node, the information node mobile: 1891111111x newly associates with openID: 1. When both the first association time and the second association time are within 1 day, the corresponding timeliness weight rules are found according to the corresponding data types. According to the corresponding timeliness weight rules, it can be known that the weight corresponding to the supplementary association data of the mobile phone number (information node mobile) within one day is 3, and the weight of openID: 1 for supplementary association data within one day is 4. At this time, the weight of the information node openID: 1 under the OneID: 1 node is higher, and the OneID: 1 node is determined as the target node. At this time, mobile: 1891111111x is associated to the OneID: 1 node, and the association between mobile: 1891111111x and the OneID: 2 node is cancelled.

[0045] For another example, when the first associated time and the second associated time exceed 1 day, the corresponding timeliness weight rules are found according to the corresponding data types. According to the corresponding timeliness weight rules, the weight for supplementing associated data for a mobile phone number exceeding 1 day is 4, and the weight for supplementing associated data for openID:1 exceeding 1 day is 3. At this time, the weight of the information node mobile: 1891111111x under the OneID: 2 node is relatively high, and 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 establishment of the association at this time is to maintain the association between mobile: 1891111111x and the OneID: 2 node), and the association between mobile: 1891111111x and the OneID: 1 node is cancelled. Among them, since under the OneID: 1 node, mobile: 1891111111x has an association relationship with the information node openID:1, and the weight of mobile is greater than the weight of openID, at this time, in addition to cancelling 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 associate openID:1 with the OneID: 2 node, that is, integrate the information of channel A into the OneID: 2 node. (Cancel the association and the corresponding step of the association step is S140).

[0046] S130. Determine the target OneID node from the first OneID node and the second OneID node according to the first node weight and the second node weight.

[0047] Specifically, if the first node weight is greater than the second node weight, the first OneID node is determined as the target OneID node; if the first node weight is less than the second node weight, the second OneID node is determined as the target OneID node.

[0048] 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, where the non-target OneID node is the OneID node other than the target OneID node among the first OneID node and the second OneID node.

[0049] Specifically, associating the first target user information with the target OneID node means generating an information node corresponding to the first target user information (this information node stores the first target user information), and connecting the generated information node to the target OneID node.

[0050] In some embodiments, in the newly added associated target user information of an information node, when the weight of the target user information is greater than the weight of the corresponding information node, when it is necessary to cancel the association between the target user information and the corresponding OneID node, at this time, 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 associate the canceled information node to the target OneID node (as Figure 6 shown).

[0051] In summary, when a first information node in a graph database newly adds an association with first target user information, it is determined whether there is a second information node corresponding to the first target user information 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, and different information nodes under the same OneID node store different user information of the same user; 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 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 relationship pair count weight mechanism, a user information weight mechanism, and a data timeliness weight mechanism; the 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 to the target OneID node, and the association between the first target user information and non-target OneID nodes is canceled. The non-target OneID nodes are the OneID nodes other than the target OneID node among the first OneID node and the second OneID node. Through the multi-dimensional weight mechanism in the embodiments of the present application, the OneID node to which the newly added associated user information belongs can be accurately identified, and the data fusion effect can be improved.

[0052] Figure 12 is a schematic block diagram of a data integration device 1200 based on a multi-dimensional weight mechanism provided by an embodiment of the present application. As Figure 12 shown, corresponding to the above data integration method based on a multi-dimensional weight mechanism, the present application also provides a data integration device 1200 based on a multi-dimensional weight mechanism. The data integration device 1200 based on a multi-dimensional weight mechanism includes units for executing the above data integration method based on a multi-dimensional weight mechanism. The data integration device 1200 based on a multi-dimensional weight mechanism can be configured in a terminal or a server. Specifically, please refer toFigure 12 , the data integration device 1200 based on the multi-dimensional weight mechanism includes a transceiver unit 1201 and a processing unit 1202, where: The transceiver unit 1201 obtains the first target user information newly associated with the first information node by the user. The processing unit 1202 is configured to, when the first information node in the graph database newly associates the first target user information, determine whether there is a second information node corresponding to the first target user information in the graph database. The graph database includes multiple OneID nodes, and different OneID nodes are connected with at least one information node belonging to the same user, and different user information of the same user is stored in different information nodes under the same OneID node. If the second information node exists, determine the first node weight of the first OneID node and the second node weight of the second OneID node 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 a source credibility weight mechanism, a relationship pair number weight mechanism, a user information weight mechanism, and a data timeliness weight mechanism. Determine the target OneID node from the first OneID node and the second OneID node according to the first node weight and the second node weight. 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. The non-target OneID node is the OneID node other than the target OneID node among the first OneID node and the second OneID node.

[0053] In some embodiments, when the processing unit 1202 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 preset multi-dimensional weight mechanism, it is specifically configured to: 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 no newly associated user information currently, determine 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. The current weight mechanism includes the source credibility weight mechanism and / or the user information weight mechanism.

[0054] In some embodiments, when the current weight mechanism includes the source credibility weight mechanism, when the processing unit 1202 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, it specifically is used for: 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 the channel identifier and the weight, respectively 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 use the second channel weight as the second node weight.

[0055] In some embodiments, when the current weight mechanism includes the user information weight mechanism, when the processing unit 1202 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, it specifically is used for: 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 the data type and the weight, respectively 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 use the second data type weight as the second node weight.

[0056] In some embodiments, when the current weight mechanism includes the source credibility weight mechanism and the user information weight mechanism, when the processing unit 1202 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, it specifically is used for: 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 the channel identifier and the weight, respectively determine the first channel weight of the first channel identifier and the second channel weight of the second channel identifier; 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 the data type and the weight, respectively determine the first data type weight of the first data type and the second data type weight of the second data type; 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.

[0057] In some embodiments, when the processing unit 1202 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 preset multi-dimensional weight mechanism, it is specifically configured to: If the user information in the first information node and the second information node is from the same channel, and the second information node is an information node newly associated with the first target user information, then use the relationship pair frequency weight mechanism as the current weight mechanism; obtain the first information quantity of the first target user information newly associated with the first information node based on the current weight mechanism, and obtain the second information quantity of the first target user information newly associated with the second information node; determine the first node weight and the second node weight according to the first information quantity and the second information quantity respectively.

[0058] In some embodiments, when the processing unit 1202 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 preset multi-dimensional weight mechanism, it is specifically configured to: If the user information in the first information node and the second information node is from different channels, the second information node is the 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, then use the data timeliness weight mechanism as the current weight mechanism; obtain the first association time when the first information node newly associates the first target user information, and obtain the second association time when the second information node newly associates the second target user information; 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; determine the first node weight and the second node weight according to the first association time, the second association time, the third data type, the fourth data type, the first timeliness weight rule of the preset third data type, and the second timeliness weight rule of the fourth data type.

[0059] In summary, through the multi-dimensional weight mechanism in the embodiments of the present application, the OneID node to which the newly associated user information currently belongs can be accurately identified, and the data fusion effect can be improved.

[0060] It should be noted that those skilled in the art can clearly understand that the specific implementation processes of the above data integration device 1200 based on the multi-dimensional weight mechanism and each unit can refer to the corresponding descriptions in the foregoing method embodiments. For the convenience and conciseness of description, they will not be elaborated here.

[0061] The above data integration device based on a multi-dimensional weight mechanism can be implemented in the form of a computer program, which can run on a computer device as shown in Figure 13 below.

[0062] Please refer to Figure 13 , Figure 13 which is a schematic block diagram of a computer device provided by an embodiment of the present application. The computer device 1300 can be a terminal or a server.

[0063] Referring to Figure 13 , the computer device 1300 includes a processor 1302, a memory, and a network interface 1305 connected through a system bus 1301. Among them, the memory can include a non-volatile storage medium 1303 and an internal memory 1304.

[0064] The non-volatile storage medium 1303 can store an operating system 13031 and a computer program 13032. The computer program 13032 includes program instructions, which when executed, can cause the processor 1302 to execute a data integration method based on a multi-dimensional weight mechanism.

[0065] The processor 1302 is used to provide computing and control capabilities to support the operation of the entire computer device 1300.

[0066] The internal memory 1304 provides an environment for the operation of the computer program 13032 in the non-volatile storage medium 1303. When the computer program 13032 is executed by the processor 1302, it can cause the processor 1302 to execute a data integration method based on a multi-dimensional weight mechanism.

[0067] The network interface 1305 is used for network communication with other devices. Those skilled in the art can understand that Figure 13 the structure shown in

[0068] is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device 1300 to which the solution of the present application is applied. The specific computer device 1300 may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout. When a first information node in the graph database newly associates with first target user information, determine whether there is a second information node corresponding to the first target user information 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 user information of the same user is stored in different information nodes under the same OneID node; If there is the second information node, determine 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 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 relationship pair number weight mechanism, a user information weight mechanism, and a data timeliness weight mechanism; Determine 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; Associate the first target user information with the target OneID node, and cancel the association between the first target user information and non-target OneID nodes. The non-target OneID nodes are the OneID nodes other than the target OneID node among the first OneID node and the second OneID node.

[0069] It should be understood that in the embodiment of the present application, the processor 1302 may be a central processing unit (CPU), and the processor 1302 may also 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. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0070] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program includes program instructions, and the computer program 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.

[0071] Therefore, the present application also provides a storage medium. The storage medium can be a computer-readable storage medium. The storage medium stores a computer program, where the computer program includes program instructions. When the program instructions are executed by a processor, the processor performs the following steps: When a first information node in the graph database newly associates with first target user information, determine whether there is a second information node corresponding to the first target user information 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, and different user information of the same user is stored in different information nodes under the same OneID node; If the second information node exists, determine 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 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 relationship pair times weight mechanism, a user information weight mechanism, and a data timeliness weight mechanism; Determine 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; Associate the first target user information with the target OneID node, and cancel the association between the first target user information and non-target OneID nodes. The non-target OneID nodes are the OneID nodes other than the target OneID node among the first OneID node and the second OneID node.

[0072] The storage medium can be various computer-readable storage media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disc that can store program codes.

[0073] Those of ordinary skill in the art will realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0074] In several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of each unit is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0075] The steps in the method embodiments of this application can be adjusted, combined, and deleted according to actual needs. The units in the device embodiments of this application can be combined, divided, and deleted according to actual needs. In addition, the functional units in each embodiment of this application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0076] If the integrated unit is implemented in the form of 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 this 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 for causing a computer device (which can be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of this application.

[0077] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A data integration method based on a multi-dimensional weight mechanism, characterized in that Including: When a first information node in the graph database newly associates with first target user information, determine whether there is a second information node corresponding to the first target user information 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, and different user information of the same user is stored in different information nodes under the same OneID node; If the second information node exists, determine a first node weight of the first OneID node and a second node weight of the second OneID node 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 relationship pair count weight mechanism, a user information weight mechanism, and a data timeliness weight mechanism; Determine 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; Associate the first target user information with the target OneID node, and cancel the association between the first target user information and non-target OneID nodes. The non-target OneID nodes are the OneID nodes other than the target OneID node among the first OneID node and the second OneID node.

2. The method according to claim 1, characterized in that, The 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 includes: 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 no newly associated user information currently, then determine 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. The current weight mechanism includes the source credibility weight mechanism and / or the user information weight mechanism.

3. The method according to claim 2, characterized in that When the current weight mechanism includes the source credibility 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 includes: Obtain a first channel identifier corresponding to the first information node, and obtain a second channel identifier corresponding to the second information node; According to the preset correspondence between the channel identifier and the weight, respectively determine a first channel weight of the first channel identifier and a 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.

4. The method according to claim 2, characterized in that, 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 includes: Obtaining a first data type corresponding to the first information node and obtaining a second data type corresponding to the second information node; According to a preset correspondence between the data type and the weight, respectively determining a first data type weight of the first data type and a second data type weight of the second data type, and using the first data type weight as the first node weight and using the second data type weight as the second node weight.

5. The method according to claim 2, characterized in that, When the current weight mechanism includes the source credibility weight mechanism and 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 includes: Obtaining a first channel identifier corresponding to the first information node and obtaining a second channel identifier corresponding to the second information node; According to a preset correspondence between the channel identifier and the weight, respectively determining a first channel weight of the first channel identifier and a second channel weight of the second channel identifier; Obtaining a first data type corresponding to the first information node and obtaining a second data type corresponding to the second information node; According to a preset correspondence between the data type and the weight, respectively determining a first data type weight of the first data type and a second data type weight of the second data type; Determining the first node weight according to the first channel weight and the first data type weight, and determining the second node weight according to the second channel weight and the second data type weight.

6. The method according to claim 1, characterized in that Determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the preset multi-dimensional weight mechanism includes: 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 associated with the first target user information, then use the relationship pair number weight mechanism as the current weight mechanism; Based on the current weight mechanism, obtaining a first information quantity of the first target user information currently newly associated with the first information node and obtaining a second information quantity of the first target user information currently newly associated with the second information node; Respectively determining the first node weight and the second node weight according to the first information quantity and the second information quantity.

7. The method according to claim 1, wherein Determining the first node weight of the first OneID node and the second node weight of the second OneID node according to the preset multi-dimensional weight mechanism includes: 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 newly associates the same second target user information as the first information node, then the data timeliness weight mechanism is used as the current weight mechanism; Obtain the first association time when the first information node newly associates the first target user information, and obtain the second association time when the second information node newly associates the second target user information; 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; Determine the first node weight and the second node weight according to the first association time, the second association time, the third data type, the fourth data type, the first timeliness weight rule of the preset third data type, and the second timeliness weight rule of the fourth data type.

8. A data integration device based on a multi-dimensional weight mechanism, characterized in that Including: A transceiver unit for a user to obtain the first target user information newly associated by the first information node; A processing unit, when the first information node in the graph database newly associates the first target user information, determines whether there is a second information node corresponding to the first target user information in the graph database. The graph database includes multiple OneID nodes, and 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; if the second information node exists, determine the first node weight of the first OneID node and the second node weight of the second OneID node 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 a source credibility weight mechanism, a relationship pair number weight mechanism, a user information weight mechanism, and a data timeliness weight mechanism; determine the target OneID node from the first OneID node and the second OneID node according to the first node weight and the second node weight; 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. The non-target OneID node is the OneID node other than the target OneID node among the first OneID node and the second OneID node.

9. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that When the processor executes the computer program, it implements the data integration method based on the multi-dimensional weight mechanism according to any one of claims 1-7.

10. A storage medium, characterized in that, The storage medium stores a computer program, and the computer program includes program instructions. When the program instructions are executed by a processor, the processor is caused to execute the multi-dimensional weight mechanism-based data integration method according to any one of claims 1-7.

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