1. A user information generation method includes:

acquiring a user information set and a logic configuration information set;

selecting user information meeting a first preset condition from the user information set as standard user information to obtain a standard user information set;

generating a logic configuration information group set based on the logic configuration information set and the standard user information set;

constructing a user portrait for each standard user information in the standard user information set to obtain a user portrait set;

and determining standard user information corresponding to each user image meeting a second preset condition in the user image set as target user information based on the logic configuration information group set to obtain a target user information set.

2. The method of claim 1, wherein generating a set of logical configuration information groups based on the set of logical configuration information and the set of standard user information comprises:

identifying each standard user information in the standard user information set to generate identification result information to obtain an identification result information set;

and selecting logic configuration information matched with each piece of identification result information in the identification result information set from the logic configuration information set as a logic information group to obtain a logic configuration information group set.

3. The method of claim 2, wherein the identifying each standard user information in the set of standard user information to generate identification result information comprises:

and inputting the standard user information and the logic configuration information set into a preset semantic correlation model to obtain output identification result information matched with the standard user information.

4. The method of claim 1, wherein the standard user information in the set of standard user information comprises a set of user information parameters, a user human resource data value, and a set of user product data values; and

the user portrait construction of each standard user information in the standard user information set comprises:

constructing a user information matrix of the standard user information based on a user information parameter group, a user human resource data value and a user product data value group which are included in the standard user information;

determining the user information matrix as a user representation.

5. The method of claim 1, wherein said determining, based on the set of logical configuration information groups, standard user information corresponding to each user portrait in the set of user portraits that satisfies a second predetermined condition as target user information comprises:

carrying out logic operation model construction on each logic configuration information group in the logic configuration information group set to generate a logic operation model, and obtaining a logic operation model set;

and inputting each user portrait in the user portrait set into a corresponding logic operation model in the logic operation model set to generate a logic operation result, so as to obtain a logic operation result set.

6. The method of claim 5, wherein said determining, based on said set of logical configuration information sets, standard user information corresponding to each user portrait in said set of user portraits that satisfies a second predetermined condition as target user information further comprises:

determining the user portrait corresponding to the logic operation result which is greater than a first preset threshold value in the logic operation result set as a standard user portrait to obtain a standard user portrait set;

and determining the scoring value of each standard user portrait in the standard user portrait set to obtain a scoring value set.

7. The method of claim 6, wherein said determining, based on said set of logical configuration information sets, standard user information corresponding to each user portrait in said set of user portraits that satisfies a second predetermined condition as target user information further comprises:

and determining the standard user information corresponding to each score value which is greater than a second preset threshold value in the score value set as target user information.

8. A user information generation method and device comprises the following steps:

an acquisition unit configured to acquire a user information set and a logic configuration information set;

the selection unit is configured to select user information meeting a first preset condition from the user information set as standard user information to obtain a standard user information set;

a generating unit configured to generate a set of logical configuration information groups based on the set of logical configuration information and the set of standard user information;

the construction unit is configured to perform user portrait construction on each standard user information in the standard user information set to obtain a user portrait set;

and the determining unit is configured to determine standard user information corresponding to each user image meeting a second predetermined condition in the user image set as target user information based on the logic configuration information group set, so as to obtain a target user information set.

9. An electronic device, comprising:

one or more processors;

a storage device having one or more programs stored thereon,

when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-7.

10. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1-7.

Background

User information generation is a technique for selecting desired user information from a large amount of user information. Currently, the common generation manner of user information (e.g., provider information) is: the user data which can be uniformly calculated is obtained by carrying out data processing on a large amount of user information, and then the required user information is generated according to the user data.

However, when the user information generation is performed in the above manner, there are often technical problems as follows:

firstly, different user information comprises data of different data types, and the simultaneous data processing of a large number of types of data can increase the difficulty of data processing to a certain extent, so that the efficiency of data processing is reduced, and further, the efficiency of generating the user information is reduced;

secondly, the consideration of the user data included in the user information is not comprehensive enough, so that the user information generated according to the user data has deviation from the actually required user information, and the accuracy of generating the user information is reduced.

Disclosure of Invention

This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

Some embodiments of the present disclosure propose a user information generation method, apparatus, electronic device, and computer readable medium to solve one or more of the technical problems mentioned in the background section above.

In a first aspect, some embodiments of the present disclosure provide a user information generating method, including: acquiring a user information set and a logic configuration information set; selecting a user information set meeting a first preset condition from the user information sets as standard user information to obtain a standard user information set; generating a logic configuration information group set based on the logic configuration information and the standard user information set; constructing a user portrait for each standard user information in the standard user information set to obtain a user portrait set; and determining standard user information corresponding to each user image meeting a second preset condition in the user image set as target user information based on the logic configuration information group set to obtain a target user information set.

In a second aspect, some embodiments of the present disclosure provide a user information generating apparatus, the apparatus comprising: an acquisition unit configured to acquire a user information set and a logic configuration information set; the selection unit is configured to select user information meeting a first preset condition from the user information set as standard user information to obtain a standard user information set; a generating unit configured to generate a set of logical configuration information groups based on the set of logical configuration information and the set of standard user information; the construction unit is configured to carry out user portrait construction on each standard user information in the standard user information set to obtain a user portrait set; and the determining unit is configured to determine standard user information corresponding to each user image meeting a second preset condition in the user image set as target user information based on the logic configuration information group set, so as to obtain a target user information set.

In a third aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors, cause the one or more processors to implement the method described in any of the implementations of the first aspect.

In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium on which a computer program is stored, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect.

The above embodiments of the present disclosure have the following advantages: by the user information generation method of some embodiments of the present disclosure, the efficiency of generating user information can be improved. Specifically, the reason why the efficiency of generating the user information by the relevant user information generation method is reduced is that: because different user information includes data of different data types, and a large amount of included data of multiple types are processed at the same time, the difficulty of data processing is increased, so that the efficiency of data preprocessing is reduced, and further the efficiency of user information generation is reduced. Based on this, the user information generating method of some embodiments of the present disclosure first obtains a user information set and a logic configuration information set. By introducing the logic configuration information set, different data types included by different user information in the user information set can be correspondingly processed. Therefore, the difficulty of data processing can be reduced, and the efficiency of data processing can be improved. Thus, the efficiency of user information generation can be improved in terms of data processing. Then, the user information meeting the first preset condition is selected from the user information set to serve as standard user information, and a standard user information set is obtained. By introducing the first predetermined condition, the user information which does not meet the condition can be removed preliminarily, and the number of the user information is reduced. Therefore, the difficulty of data processing can be reduced from the perspective of reducing the number of user information, and the efficiency of user data processing can be improved. And then, generating a logic configuration information group set based on the logic configuration information set and the standard user information set. Each logical configuration information group in the generated logical configuration information group set can be used for processing corresponding standard user information in the standard user information set. And then, constructing the user portrait for each standard user information in the standard user information set to obtain a user portrait set. By constructing the user representation, the data dimensions of each standard user information in the standard user information set can be unified. Thus, generation of user information is facilitated. And finally, based on the logic configuration information group set, determining standard user information corresponding to each user image meeting a second preset condition in the user image set as target user information to obtain a target user information set. By introducing a second predetermined condition, the user information can be further filtered according to the user portrait. Therefore, the implementation mode reduces the difficulty of data processing from different aspects. Thus, the efficiency of data processing is improved. Further, the efficiency of user information generation is improved.

Drawings

The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and elements are not necessarily drawn to scale.

FIG. 1 is a schematic diagram of one application scenario of a user information generation method of some embodiments of the present disclosure;

FIG. 2 is a flow diagram of some embodiments of a user information generation method according to the present disclosure;

FIG. 3 is a flow diagram of further embodiments of a user information generation method according to the present disclosure;

FIG. 4 is a schematic block diagram of some embodiments of a user information generation apparatus according to the present disclosure;

FIG. 5 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.

It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings. The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.

It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.

It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.

The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.

The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

Fig. 1 is a schematic diagram of an application scenario of a user information generation method of some embodiments of the present disclosure.

In the application scenario of fig. 1, first, the computing device 101 may obtain a set of user information 102 and a set of logical configuration information 103. Next, the computing device 101 may select user information satisfying a first predetermined condition from the user information sets 102 as standard user information, resulting in a standard user information set 104. The computing device 101 may then generate a set 105 of logical configuration information sets based on the set 103 of logical configuration information and the set 104 of standard user information. Thereafter, the computing device 101 may perform user portrait construction on each standard user information in the standard user information set 104 to obtain a user portrait set 106. Finally, the computing device 101 may determine, as the target user information, the standard user information corresponding to each user image satisfying the second predetermined condition in the user image set 106 based on the set 105 of logical configuration information groups, so as to obtain a target user information set 107.

The computing device 101 may be hardware or software. When the computing device is hardware, it may be implemented as a distributed cluster composed of multiple servers or terminal devices, or may be implemented as a single server or a single terminal device. When the computing device is embodied as software, it may be installed in the hardware devices enumerated above. It may be implemented, for example, as multiple software or software modules to provide distributed services, or as a single software or software module. And is not particularly limited herein.

It should be understood that the number of computing devices in FIG. 1 is merely illustrative. There may be any number of computing devices, as implementation needs dictate.

With continued reference to fig. 2, a flow 200 of some embodiments of a user information generation method in accordance with the present disclosure is shown. The user information generation method comprises the following steps:

step 201, acquiring a user information set and a logic configuration information set.

In some embodiments, the executing entity of the user information generating method (e.g., the computing device 101 shown in fig. 1) may obtain the user information set and the logic configuration information set through a wired connection or a wireless connection. The user information (e.g., the provider information) in the user information set may include a user basic data set. The user basic data set can be used for providing a data base for generating user information. The logic configuration information in the logic configuration information set may include processing logic for processing the user basic data in the user basic data group included in the user information. The logical configuration information in the logical configuration information set may be used to process the user information in the user information set. It should be noted that the wireless connection means may include, but is not limited to, a 3G/4G connection, a WiFi connection, a bluetooth connection, a WiMAX connection, a Zigbee connection, a uwb (ultra wideband) connection, and other wireless connection means now known or developed in the future.

As an example, the user information may be: [ data a:10, data b: 20, data c: 1000]. The logic configuration information may include processing logic that may be one or more of the following: "delete", "sum", "maximum" and "compare", etc.

Step 202, selecting the user information meeting the first predetermined condition from the user information set as standard user information to obtain a standard user information set.

In some embodiments, the execution subject may select, from the user information sets, user information satisfying a first predetermined condition as standard user information, to obtain a standard user information set. The first predetermined condition may be that a preset data item (e.g., data a) exists in the user information.

And step 203, generating a logic configuration information group set based on the logic configuration information set and the standard user information set.

In some embodiments, the execution body may generate a set of logical configuration information groups based on the set of logical configuration information and the set of standard user information. Wherein, the logic configuration information set and the standard user information set may be sent to a standard user information processing server. Then, receiving the logic configuration information group set returned by the standard user information processing server. Each logical configuration information group in the set of logical configuration information groups may correspond to each standard user information in the set of standard user information. The logical configuration information group may be used to process corresponding standard user information (for example, the logical configuration information group includes "delete data c" processing logic, and data c in the standard user information may be deleted according to the logical configuration information).

In some optional implementations of some embodiments, the generating a set of logical configuration information groups based on the set of logical configuration information and the set of standard user information may include:

firstly, identifying each standard user information in the standard user information set to generate identification result information, and obtaining an identification result information set. Wherein the identifying may be confirming a data type of each data included in the standard user information (for example, the type of the data a is a first type). Then, the confirmed data type may be used as the identification result information.

And secondly, selecting logic configuration information matched with each piece of identification result information in the identification result information set from the logic configuration information set as a logic information group to obtain a logic configuration information group set. Wherein the logical configuration information may include a data category designation. The matching may mean that the number included in the logical configuration information set is the same as the data type included in the identification result information. Since the identification result information includes the data type of each data in the above-mentioned standard user information. Thus, at least one logical configuration information corresponding to each recognition result information may constitute a logical configuration information group. Therefore, each piece of recognition result information corresponds to a logical configuration information group.

As an example, the logical configuration information includes a data category labeled "one", and the identification result information includes a data type of "first type". Then, it can be confirmed that the logic configuration information matches the recognition result information.

In some optional implementation manners of some embodiments, the selecting, by the execution main body, logic configuration information that matches each piece of recognition result information in the recognition result information set from the logic configuration information set as a logic information group may include:

and inputting the standard user information and the logic configuration information set into a preset semantic correlation model to obtain output identification result information matched with the standard user information. The preset Semantic relevance model may be DSSM (Deep Structured Semantic Models). The preset semantic relevance model may be used to match user data included in the standard user information with the logic configuration information.

And 204, constructing the user portrait for each standard user information in the standard user information set to obtain a user portrait set.

In some embodiments, the execution subject may perform user portrait construction on each standard user information in the standard user information set to obtain a user portrait set. Wherein, user portrait construction can be carried out in the following modes: first, the standard user information may be vectorized to obtain a user information vector, and then the user information vector is used as a user portrait. The vectorization may be to vectorize each user data included in the standard user information in a dimension with the same number of user data.

In some optional implementations of some embodiments, the standard user information in the standard user information set may include a user information parameter set, a user human resource data value, and a user product data value set. And the executing body constructs the user portrait of each standard user information in the standard user information set, and may include the following steps:

the method comprises the following steps that firstly, a user information matrix of the standard user information is constructed based on a user information parameter group, a user human resource data value and a user product data value group which are included in the standard user information. The user information matrix can be constructed in the following way: first, an empty initial user information matrix may be constructed. The dimension of the initial user information matrix may be the same as the sum of the number of parameters included in the standard user information. For example, the total number of items of user information in the set of user information parameters (e.g., number of different product quality testing personnel), the number of user product data values in the set of user product data values (e.g., production or raw material usage for different products), and one user human resource data value (e.g., number of technicians. And then, inputting the user data included in the standard user information into the initial user information matrix to obtain the user information matrix.

And secondly, determining the user information matrix as a user portrait. Each column of data in the user representation may represent an item of user data included in the standard user information (e.g., a user information parameter in the user information parameter set).

Step 205, based on the set of logic configuration information groups, determining standard user information corresponding to each user image meeting the second predetermined condition in the set of user images as target user information, so as to obtain a set of target user information.

In some embodiments, the executing entity may determine, as the target user information, standard user information corresponding to each user image satisfying a second predetermined condition in the user image set based on the set of logical configuration information groups, to obtain a target user information set. Wherein the second predetermined condition may be: the data for each dimension in the user representation is greater than each data threshold in the set of predetermined data thresholds. First, each user representation may be logically processed according to processing logic included in each logical configuration information in the corresponding logical configuration information set (e.g., processing logic included in the logical configuration information is "delete data a", then the representation dimension in which data a included in each user representation is located may be deleted, and processing logic included in the other logical configuration information is "add data b to data c", then data values corresponding to two dimensions of data b and data c included in each user representation may be added, and the added sums may form a new dimension). Thus, a processed user image can be obtained. Finally, a qualified user representation may be selected from the processed user representations based on a second predetermined condition. Therefore, the user information corresponding to the generated user image can be used as the target user information, and the generated result is the target user information set.

The above embodiments of the present disclosure have the following advantages: by the user information generation method of some embodiments of the present disclosure, the efficiency of generating user information can be improved. Specifically, the reason why the efficiency of generating the user information by the relevant user information generation method is reduced is that: because different user information includes data of different data types, and a large amount of included data of multiple types are processed at the same time, the difficulty of data processing is increased, so that the efficiency of data preprocessing is reduced, and further the efficiency of user information generation is reduced. Based on this, the user information generating method of some embodiments of the present disclosure first obtains a user information set and a logic configuration information set. By introducing the logic configuration information set, different data types included by different user information in the user information set can be correspondingly processed. Therefore, the difficulty of data processing can be reduced, and the efficiency of data processing can be improved. Thus, the efficiency of user information generation can be improved in terms of data processing. Then, the user information meeting the first preset condition is selected from the user information set to serve as standard user information, and a standard user information set is obtained. By introducing the first predetermined condition, the user information which does not meet the condition can be removed preliminarily, and the number of the user information is reduced. Therefore, the difficulty of data processing can be reduced from the perspective of reducing the number of user information, and the efficiency of user data processing can be improved. And then, generating a logic configuration information group set based on the logic configuration information set and the standard user information set. Each logical configuration information group in the generated logical configuration information group set can be used for processing corresponding standard user information in the standard user information set. And then, constructing the user portrait for each standard user information in the standard user information set to obtain a user portrait set. By constructing the user representation, the data dimensions of each standard user information in the standard user information set can be unified. Thus, generation of user information is facilitated. And finally, based on the logic configuration information group set, determining standard user information corresponding to each user image meeting a second preset condition in the user image set as target user information to obtain a target user information set. By introducing a second predetermined condition, the user information can be further filtered according to the user portrait. Therefore, the implementation mode reduces the difficulty of data processing from different aspects. Thus, the efficiency of data processing is improved. Further, the efficiency of user information generation is improved.

With further reference to fig. 3, a flow 300 of further embodiments of a user information generation method is illustrated. The process 300 of the user information generating method includes the following steps:

step 301, acquiring a user information set and a logic configuration information set.

Step 302, selecting the user information meeting the first predetermined condition from the user information set as standard user information, and obtaining a standard user information set.

Step 303, generating a set of logical configuration information groups based on the set of logical configuration information and the set of standard user information.

And 304, constructing the user portrait for each standard user information in the standard user information set to obtain a user portrait set.

In some embodiments, the specific implementation manner and technical effects of steps 301 and 304 may refer to steps 201 and 204 in the embodiments corresponding to fig. 2, which are not described herein again.

Step 305, performing logic operation model construction on each logic configuration information group in the logic configuration information group set to generate a logic operation model, so as to obtain a logic operation model set.

In some embodiments, the execution subject may perform logic operation model construction on each logic configuration information group in the logic configuration information group set to generate a logic operation model, so as to obtain a logic operation model set. The logic operation model building may be to convert each of the above logic configuration information sets into a logic operation code (for example, a python format code or a java format code) to generate a logic operation function, and use the generated logic operation function as the logic operation model.

Step 306, inputting each user portrait in the user portrait set into a corresponding logic operation model in the logic operation model set to generate a logic operation result, so as to obtain a logic operation result set.

In some embodiments, the execution subject may input each user portrait in the user portrait set into a corresponding logic operation model in the logic operation model set to generate a logic operation result, so as to obtain a logic operation result set. The logic operation model can process the user data in the user portrait through a logic function converted by the processing logic included in the logic configuration information, and the obtained processing result is used as a logic operation result. Specifically, the processing of the user data in the user representation may be inputting the user data into a logic function and outputting a logic operation result. For example, the output logical operation result may be: 12.

and 307, determining the user portrait corresponding to the logic operation result which is greater than the first preset threshold value in the logic operation result set as a standard user portrait to obtain a standard user portrait set.

In some embodiments, the execution subject may determine a user portrait corresponding to a logic operation result greater than a first preset threshold in the logic operation result set as a standard user portrait, so as to obtain a standard user portrait set. The logic operation result of the first preset threshold (e.g., 10) is selected and used for screening the user portrait, and the logic operation result of which the corresponding logic operation result is smaller than or equal to the first preset threshold is removed. Thus, user images that do not satisfy the conditions can be removed to reduce the effect of such user images on the generation of user information. Thus, the accuracy of user information generation is improved.

Step 308, determining the scoring value of each standard user portrait in the standard user portrait set to obtain a scoring value set.

In some embodiments, the execution entity may determine a value of credit for each standard user representation in the set of standard user representations to obtain a set of values of credit. Wherein the score value may be generated by: comparing the data of each dimension included in the standard user portrait with a corresponding portrait data threshold in a preset portrait data threshold set. The number of dimensions of data that are greater than the corresponding portrait data threshold may then be scored. The corresponding image data threshold may be associated by a data name. For example, the user data is "data a: 10". The corresponding user data threshold may be "data a: 8".

In some alternative implementations of some embodiments, the value of the credit of the standard user representation may be determined by:

the method comprises the following steps of firstly, determining a first grading parameter according to a first preset grading threshold value. If the minimum user parameter in the user parameter group corresponding to the marked user image is smaller than the first preset scoring threshold, the first scoring parameter may be determined to be 3. If the minimum user parameter in the user parameter group corresponding to the marked user image is greater than or equal to the first preset scoring threshold, the first scoring parameter may be definitely 4.

And secondly, generating a second grading parameter according to a second preset grading threshold value and the user human resource data value included in the marked user information corresponding to the standard user image. If the data value of the user human resource is greater than or equal to the second preset scoring threshold, the second scoring parameter may be 4. If the data value of the user human resource is smaller than the second preset scoring threshold, the second scoring parameter may be 3.

And thirdly, determining the sum of all user product data values in the user product data value group included in the marked user information corresponding to the standard user image, and determining the index value of the sum of all user product data values as a third grading parameter. Wherein the index value for the sum of the individual user product data values may be determined by a base ten index function.

The fourth step may determine an arithmetic square root of the first scoring parameter and the second scoring parameter as a fourth scoring parameter.

In the fifth step, a product of the first scoring parameter and the number of the user parameters in the user parameter group corresponding to the standard user image may be determined as a fifth scoring parameter.

The sixth step may determine a product of the third rating parameter and the fourth rating parameter and a sum of the second rating parameter and the fifth rating parameter as the rating value of the standard user figure. The rounding-up operation may be performed on a product of the third scoring parameter and the fourth scoring parameter. So as to ensure the score value of the standard user image as an integer.

In addition, the first preset score threshold may be 3. The second preset scoring threshold may be 5. The foregoing implementation manner is an inventive point of the embodiment of the present disclosure, and solves a second technical problem mentioned in the background art that "consideration of user data included in the user information is not comprehensive enough, so that the user information generated according to the user data is deviated from actually required user information, thereby reducing accuracy of generating the user information". Factors that lead to a reduction in the accuracy of generating user information tend to be as follows: the consideration of the user data included in the user information is not comprehensive enough, so that the user information generated according to the user data is deviated from the actually required user information. If the above factors are solved, the effect of improving the accuracy of generating the user information can be achieved. To achieve this, the present disclosure scores different categories of data separately. Therefore, the influence of different types of data on the score value is more comprehensively considered. First, the minimum value of each user information parameter in the user information parameter group corresponding to the standard user image can be selected, and whether the minimum value meets the condition or not can be judged. In practice, the user information parameter set (e.g., the number of different product quality testing personnel) may also be an important score item when generating the user information (e.g., supplier information) (e.g., the number of product quality testing personnel is small, there are cases where the product quality is affected). Therefore, the implementation mode adds specific judgment on the user information parameter group so as to ensure that the selected user information meets the preset requirement on the user information parameter group. The user human resources data value (e.g., the number of technicians) corresponding to the standard user profile may then be determined to be greater than a second predetermined scoring threshold. In practice, the selection of user information (vendor information) by the user human resource data values may also be an important option. Therefore, the influence of the user human resource data value on the user information generation is considered, and the judgment of the user human resource data value is added in the implementation mode. Therefore, the accuracy of the user information generation can be improved in the aspect of the data value of the human resources of the user. Finally, the influence of the user product data value group (for example, the raw material usage amount of different products included in the supplier information) included in the standard user information corresponding to the standard user image on the generation of the user information is considered. In practice, the user product data value set is an important consideration for the generation of user information. Therefore, the sum magnitude of the user product data values in the user product data value group is adjusted first, so that the sum magnitude can participate in the score value calculation together with the factors, and the positive correlation influence of the user information parameter group and the user human resource data value on the user product data value score value is considered. Thus, the accuracy of the generated score value can be improved. Further, the accuracy of generating the user information can be improved.

Step 309, determining the standard user information corresponding to each score value larger than the second preset threshold value in the score value set as the target user information.

In some embodiments, the executing entity may determine, as the target user information, standard user information corresponding to each score value greater than a second preset threshold in the score value set. The second preset threshold (e.g., 25) may further screen out standard user information satisfying the condition from the standard user information according to a comparison result with the score value (i.e., the score value greater than the second preset threshold).

As can be seen from fig. 3, compared with the description of some embodiments corresponding to fig. 2, the flow 300 of the data transmission method in some embodiments corresponding to fig. 3 embodies the steps of participating in the generation of the user information through the user representation. Thus, the present disclosure introduces a logical operational model and multiple selection modes (greater than a first preset threshold and greater than a second preset threshold). Firstly, each logic operation model can carry out logic operation on the standard user information in a targeted manner by generating the logic operation model corresponding to each standard user information. Therefore, the influence on the calculation result when different types of data are calculated in the same manner can be reduced. Therefore, the accuracy of the generated logic operation result is improved so as to improve the accuracy of the user information generation. Then, the user images meeting the conditions can be selected by utilizing the first preset threshold value, so that the influence of the user images on user information screening is reduced. Thus, the accuracy of user information generation is improved. And finally, selecting the score value meeting the condition by using a second preset threshold value. Thus, the user information corresponding to the selected score value can be used as the target user information. Therefore, the target user information generated by introducing a logic operation model and a multiple selection mode can meet the requirement better. Thus, the accuracy of generating the user information is improved.

With further reference to fig. 4, as an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a user information generation apparatus, which correspond to those shown in fig. 2, and which may be applied in various electronic devices in particular.

As shown in fig. 4, the data transmission apparatus 400 of some embodiments includes: an acquisition unit 401, a selection unit 402, a generation unit 403, a construction unit 404, and a determination unit 405. The acquiring unit 401 is configured to acquire a user information set and a logic configuration information set; a selecting unit 402, configured to select user information satisfying a first predetermined condition from the user information sets as standard user information, resulting in a standard user information set; a generating unit 403 configured to generate a set of logical configuration information groups based on the set of logical configuration information and the set of standard user information; a constructing unit 404 configured to perform user portrait construction on each standard user information in the standard user information set to obtain a user portrait set; the determining unit 405 is configured to determine, as the target user information, standard user information corresponding to each user image satisfying a second predetermined condition in the user image set based on the set of logical configuration information groups, so as to obtain a target user information set.

It will be understood that the elements described in the apparatus 400 correspond to various steps in the method described with reference to fig. 2. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 400 and the units included therein, and will not be described herein again.

Referring now to FIG. 5, a block diagram of an electronic device 500 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.

As shown in fig. 5, electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.

Generally, the following devices may be connected to the I/O interface 505: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 5 illustrates an electronic device 500 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 5 may represent one device or may represent multiple devices as desired.

In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program, when executed by the processing device 501, performs the above-described functions defined in the methods of some embodiments of the present disclosure.

It should be noted that the computer readable medium described in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.

In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.

The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring a user information set and a logic configuration information set; selecting user information meeting a first preset condition from the user information set as standard user information to obtain a standard user information set; generating a logic configuration information group set based on the logic configuration information set and the standard user information set; constructing a user portrait for each standard user information in the standard user information set to obtain a user portrait set; and determining standard user information corresponding to each user image meeting a second preset condition in the user image set as target user information based on the logic configuration information group set to obtain a target user information set.

Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in some embodiments of the present disclosure may be implemented by software, and may also be implemented by hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, a selection unit, a generation unit, a construction unit, and a determination unit. The names of these units do not in some cases constitute a limitation to the unit itself, and for example, the acquiring unit may also be described as a "unit that acquires a user information set and a logical configuration information set".

The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.