Equipment information pushing method and system

Abstract

The invention relates to the technical field of equipment information pushing, and particularly discloses an equipment information pushing method and system, and the method comprises the steps: receiving individual information sent by an equipment user, carrying out the statistics of the equipment use condition of the equipment user based on the individual information, and creating an identity portrait of the equipment user; receiving equipment information uploaded by an equipment provider, and determining the pushing probability of each equipment user based on the identity portrait of the equipment user; and pushing the equipment information to the equipment user based on the pushing probability, and forwarding a response request of the equipment user to the equipment provider when the response request is received. According to the method and the device, the pushing probability of the device user is determined through the information of the device user, and the device information is pushed to each device user based on the pushing probability when the device information is pushed, so that the randomness of the pushing process is greatly improved, the fixed pushing phenomenon is effectively avoided, and the anti-sensitivity of the device user is reduced from a certain aspect.

Description

Technical Field

[0001] The present invention relates to the technical field of device information push, and in particular to a device information push method and system. Background Art

[0002] Equipment leasing is a common activity in production activities. Equipment provided by equipment providers are rarely fully put into use. In different production cycles, there are often idle moments. Therefore, there are gradually more equipment leasing platforms, and equipment users can search for the equipment they need on these platforms.

[0003] When a device user makes a query on the platform, he needs to query a certain device. Generally, the device provider is not unique, and the device user will query multiple devices. This requires a device information push process. The existing push process is mostly a fixed matching push process. The device user obtains the corresponding device information based entirely on preset rules. If the device user queries multiple times and only obtains the fixed device information, the device user will easily think that this is a pure advertising platform and will no longer use the platform. This shows a phenomenon that the platform provider does not want to see. Therefore, how to improve the variability of the device information push process and reduce the aversion of the device user is the technical problem that the technical solution of the present invention wants to solve. Summary of the Invention

[0004] The purpose of the present invention is to provide a device information push method and system to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A device information push method, the method comprising:

[0007] Receive individual information sent by the device user, collect statistics on the device user's device usage based on the individual information, and create an identity profile of the device user;

[0008] Obtain the identity profiles of all device users within a preset time range corresponding to each device, compare the identity profiles of all device users, and self-adjust the identity profile of each device user;

[0009] Receive device information uploaded by device providers and determine the push probability for each device user based on the self-adjusted identity profile of the device user;

[0010] The device information is pushed to the device user based on the push probability, and when a response request is received from the device user, it is forwarded to the device provider.

[0011] As a further solution of the present invention, the step of receiving the individual information sent by the device user, collecting statistics on the device user's device usage based on the individual information, and creating an identity profile of the device user includes:

[0012] Sending a preset template to the device user and receiving the device user's filled-in information; the template at least includes the establishment years, credit capacity and guarantor information;

[0013] Obtain the device usage record of the device user; the device usage record is the device status containing the time node; the time node is a relative time point based on the rental time,

[0014] Compare each item of information in the filled information with the preset standard information, and determine the evaluation score based on the comparison results;

[0015] Determine the radius according to the evaluation score and construct a circle;

[0016] The circle is expanded at its cusp according to the device status containing the time node, and the circle after the cusp expansion is used as the identity portrait of the device user.

[0017] As a further solution of the present invention, the content of expanding the cusp of the circle according to the device status containing the time node and using the circle after the cusp expansion as the identity portrait of the device user includes:

[0018] Compare the device status with the preset standard device status and calculate the similarity;

[0019] Arrange similarities according to time nodes to obtain a similarity sequence;

[0020] Calculate the difference sequence of the similarity sequence and regularize the difference sequence according to the preset difference threshold; the regularization process is: set the difference greater than the preset difference threshold to zero;

[0021] The segmentation step is determined according to the number of non-zero elements in the difference sequence, and the circle is divided into arc segments according to the segmentation step;

[0022] Read the differential values ​​in sequence, randomly select isolated segments in the arc segment, determine the arc segment radius based on the read differential values, and correct the arc segment;

[0023] Fit the corrected arc segment as a circle after the cusp is expanded, and use the circle after the cusp is expanded as the identity portrait of the device user;

[0024] The process of determining the segmentation step length is as follows:

[0025] S = αlnN; where S is the segmentation step size and N is the number of non-zero elements in the difference sequence;

[0026] The process of determining the arc radius is:

[0027] Where R ′ is the arc radius after correction, R is the arc radius before correction, A is a preset constant, and d is the differential value, which is the latter value in the differential sequence minus the former value.

[0028] As a further solution of the present invention, the steps of obtaining identity portraits of all device users within a preset time range corresponding to each device, comparing the identity portraits of all device users, and self-adjusting the identity portrait of each device user include:

[0029] Based on the device, obtain the identity portrait of all device users within the preset time range corresponding to each device;

[0030] Read the radius of the circle corresponding to each identity portrait, compare it with a preset radius threshold, determine the scaling ratio, and scale the identity portrait based on the scaling ratio;

[0031] Compare the scaled identity profiles of all device users to determine an average identity profile, and adjust the identity profile of each device user based on the average identity profile;

[0032] The adjusted identity portrait is restored based on the scaling ratio to obtain the identity portrait of each device user.

[0033] As a further solution of the present invention, the step of receiving device information uploaded by a device provider and determining the push probability of each device user based on the self-adjusted identity profile of the device user includes:

[0034] Receive device information uploaded by the device provider;

[0035] Obtain the target user of the device information and read the self-adjusted identity profile of each target user;

[0036] Obtaining the delivery costs of the device provider and the target user, and determining the push probability of each target user based on the delivery costs and the identity profile;

[0037] The process of determining the push probability is as follows:

[0038] Where P is the push probability, S is the area of ​​the target user's identity portrait, S0 is the preset area threshold, and β is the preset correction coefficient.

[0039] As a further solution of the present invention, the step of pushing device information to the device user based on the push probability and forwarding it to the device provider upon receiving a response request from the device user includes:

[0040] Build a buffer pool;

[0041] Push device information to device users based on push probability in the buffer pool;

[0042] Query the device information received by each device user, compare the device information, and determine the floating device information based on the comparison results;

[0043] Push the floating device information to other device users besides the original device user for a second time;

[0044] The process is executed in a loop until the device information received by each device user meets the preset information conditions;

[0045] The push results in the execution buffer pool are forwarded to the device provider when a response request is received from the device user.

[0046] The technical solution of the present invention also provides a device information push system, the system comprising:

[0047] An identity profile creation module is used to receive individual information sent by the device user, collect statistics on the device user's device usage based on the individual information, and create an identity profile of the device user;

[0048] A self-adjustment module is used to obtain the identity portraits of all device users within a preset time range corresponding to each device, compare the identity portraits of all device users, and self-adjust the identity portrait of each device user;

[0049] A push probability determination module is used to receive device information uploaded by device providers and determine the push probability of each device user based on the self-adjusted identity profile of the device user;

[0050] The device information forwarding module is used to push device information to the device user based on the push probability, and forward it to the device provider when receiving a response request from the device user.

[0051] As a further solution of the present invention: the identity portrait creation module includes:

[0052] A filling information receiving unit is used to send a preset template to the device user and receive the filling information of the device user; the template at least includes the establishment years, credit capacity and guarantor information;

[0053] The record acquisition unit is used to acquire the device usage record of the device user; the device usage record is the device status containing the time node; the time node is a relative time point based on the lease time,

[0054] An evaluation score calculation unit is used to compare each piece of information in the filled information with the preset standard information and determine the evaluation score based on the comparison result;

[0055] a construction unit, configured to determine a radius according to the evaluation score and construct a circle;

[0056] The expansion unit is used to expand the circle at the cusp according to the device status containing the time node, and use the circle after the cusp expansion as the identity portrait of the device user.

[0057] As a further solution of the present invention, the content of expanding the cusp of the circle according to the device status containing the time node and using the circle after the cusp expansion as the identity portrait of the device user includes:

[0058] Compare the device status with the preset standard device status and calculate the similarity;

[0059] Arrange similarities according to time nodes to obtain a similarity sequence;

[0060] Calculate the difference sequence of the similarity sequence and regularize the difference sequence according to the preset difference threshold; the regularization process is: set the difference greater than the preset difference threshold to zero;

[0061] The segmentation step is determined according to the number of non-zero elements in the difference sequence, and the circle is divided into arc segments according to the segmentation step;

[0062] Read the differential values ​​in sequence, randomly select isolated segments in the arc segment, determine the arc segment radius based on the read differential values, and correct the arc segment;

[0063] Fit the corrected arc segment as a circle after the cusp is expanded, and use the circle after the cusp is expanded as the identity portrait of the device user;

[0064] The process of determining the segmentation step length is as follows:

[0065] S = αlnN; where S is the segmentation step size and N is the number of non-zero elements in the difference sequence;

[0066] The process of determining the arc radius is:

[0067] Where R ′ is the arc radius after correction, R is the arc radius before correction, A is a preset constant, and d is the differential value, which is the latter value in the differential sequence minus the former value.

[0068] As a further solution of the present invention: the self-regulating module includes:

[0069] A portrait acquisition unit, configured to acquire, based on the device, the identity portraits of all device users within a preset time range corresponding to each device;

[0070] A portrait scaling unit, configured to read the radius of the circle corresponding to each identity portrait, compare it with a preset radius threshold, determine a scaling ratio, and scale the identity portrait based on the scaling ratio;

[0071] A profile adjustment unit, configured to compare the scaled identity profiles of all device users, determine an average identity profile, and adjust the identity profile of each device user based on the average identity profile;

[0072] The portrait restoration unit is used to restore the adjusted identity portrait based on the scaling ratio to obtain the identity portrait of each device user.

[0073] Compared with the prior art, the beneficial effects of the present invention are: the present invention determines the push probability of the device user through the information of the device user, and when pushing device information, pushes the device information to each device user based on the push probability, which greatly improves the randomness of the push process, effectively avoids the phenomenon of fixed push, and in a certain aspect, reduces the aversion of the device user. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention.

[0075] Figure 1 This is a flowchart of the device information push method.

[0076] Figure 2 This is a flowchart of the first sub-process of the device information push method.

[0077] Figure 3 This is a second sub-flow diagram of the device information push method.

[0078] Figure 4 This is the third sub-flow diagram of the device information push method.

[0079] Figure 5 This is a fourth sub-flow diagram of the device information push method.

[0080] Figure 6 This is a structural block diagram of the device information push system. DETAILED DESCRIPTION

[0081] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0082] Figure 1 This is a flowchart of a device information push method. In an embodiment of the present invention, a device information push method includes:

[0083] Step S100: receiving individual information sent by the device user, collecting statistics on the device user's device usage based on the individual information, and creating an identity profile of the device user;

[0084] The equipment user refers to the party that needs to lease the equipment. The individual information of the equipment user is obtained. The individual information is used to characterize the status of the equipment user, including its basic qualifications, financial capabilities and relevant guarantors, etc. Based on the individual information, the equipment user's equipment usage is obtained and counted, that is, the equipment usage record, and an identity portrait of the equipment user can be created.

[0085] Step S200: Obtain identity portraits of all device users within a preset time range corresponding to each device, compare the identity portraits of all device users, and self-adjust the identity portrait of each device user;

[0086] Taking each device as a benchmark, query the identity portraits of all device users corresponding to the device, and compare the identity portraits of all device users corresponding to the same device to determine an average identity portrait, and then self-adjust the identity portrait of each device user to reduce its randomness; each device user will face different scenarios when using the device, and there will often be various sudden events. This application clusters the identity portraits of all device users of the same device into one category, and then balances these identity portraits, trying to retain only sudden events with higher frequency. Some special sudden events will be eliminated and not counted.

[0087] In layman's terms, for any device, a relatively average usage situation is determined based on the device's usage by all device users, and then the usage record of the device is adjusted for each device user. The purpose of the adjustment is to reduce event records, which is equivalent to "beautifying" the usage records of each device user in disguise.

[0088] Step S300: receiving device information uploaded by the device provider, and determining the push probability of each device user based on the self-adjusted identity profile of the device user;

[0089] The device provider is the party that provides the device. The device information uploaded by the device provider is received. The device information includes the device type, device service life, and performance parameters of each module in the device, etc. The existing data statistical caliber can be used. Once determined, the evaluation standards for the device information involved in all devices in this application are the same.

[0090] Read the self-adjusted identity portrait of the device user. The identity portrait is a simplified and abstract feature of the device provider. The process of obtaining the identity portrait is the feature extraction process. Based on the self-adjusted identity portrait of the device user, the push probability of each device user is determined, and the device information can be pushed to the device user.

[0091] It should be noted that the push process for each device user is independent, and each device user needs to make a judgment to determine whether to push the device information. This also means that device information can be pushed to multiple device users at the same time.

[0092] Step S400: Pushing device information to the device user based on the push probability, and forwarding it to the device provider upon receiving a response request from the device user;

[0093] The device information is pushed to the device user based on the push probability. When the device user receives the device information, it feeds back the response information. When the execution subject of this method receives the response request from the device user, it forwards it to the device provider, thereby establishing a connection channel between the device user and the device provider.

[0094] Figure 2 This is a flowchart of the first sub-process of the device information push method. The steps of receiving individual information sent by the device user, collecting statistics on the device user's device usage based on the individual information, and creating an identity profile of the device user include:

[0095] Step S101: Sending a preset template to the device user and receiving the device user's filled information; the template at least includes the establishment years, creditworthiness and guarantor information;

[0096] Step S102: Obtain the device usage record of the device user; the device usage record is the device status containing time nodes; the time node is a relative time point based on the rental time,

[0097] Step S103: Compare each item of information in the filled information with the preset standard information, and determine the evaluation score based on the comparison result;

[0098] Step S104: Determine the radius according to the evaluation score and construct a circle;

[0099] Step S105: Expand the circle at the cusp according to the device status containing the time node, and use the circle after the cusp expansion as the identity portrait of the device user.

[0100] In an example of the technical solution of the present invention, a specific identity portrait creation solution is provided, in which a preset template is sent to a device user, and the device user's filled-in information is received. The template is pre-set and is known data to the subject executing this method. After receiving the template, the device user can fill in the information in the template.

[0101] Then, the device usage record of the device user is obtained. This process is a data interaction process. A record acquisition request is sent to the device user, and the device user sends the device usage record. The device usage record is the device status containing time nodes. The simplest type of device usage record is the device image at each moment, and the moment is based on the relative moment of the lease; the various information in the filled information is compared with the preset standard information, and the evaluation score is determined according to the comparison result. Since the information in the template is basically in string format, the comparison process can be implemented with the help of the existing string comparison model. The output of the string comparison model is the evaluation score. The evaluation score is converted into a radius to construct a circle. The size of the circle reflects whether the filled information meets the standard.

[0102] Furthermore, the circle is expanded at the cusp according to the device status containing the time node, the device user's device usage record is filled into the created circle, and the circle after the cusp expansion is used as the identity portrait of the device user.

[0103] Specifically, the content of expanding the cusp of a circle according to the device status containing the time node and using the circle after the cusp expansion as the identity portrait of the device user includes:

[0104] Compare the device status with the preset standard device status and calculate the similarity;

[0105] Arrange similarities according to time nodes to obtain a similarity sequence;

[0106] Calculate the difference sequence of the similarity sequence and regularize the difference sequence according to the preset difference threshold; the regularization process is: set the difference greater than the preset difference threshold to zero;

[0107] The segmentation step is determined according to the number of non-zero elements in the difference sequence, and the circle is divided into arc segments according to the segmentation step;

[0108] Read the differential values ​​in sequence, randomly select isolated segments in the arc segment, determine the arc segment radius based on the read differential values, and correct the arc segment;

[0109] The corrected arc segment is fitted as a circle after the cusp is expanded, and the circle after the cusp is expanded is used as the identity portrait of the device user.

[0110] In an example of the technical solution of the present invention, the expansion process of the identity portrait is described. The purpose of this process is to convert the circular identity portrait into an irregular shape; first, the device state is compared with the preset standard device state, the similarity is calculated, the similarity is arranged according to the time node, a similarity sequence is obtained, the differential sequence of the similarity sequence is calculated, and the differential sequence is regularized according to the preset differential threshold; the regularization process is: the differences greater than the preset differential threshold are set to zero, that is, only the larger differences are retained.

[0111] Then, the segmentation step is determined according to the number of non-zero elements in the differential sequence, and the circle is divided into arc segments according to the segmentation step. The differential values ​​are read in sequence, and isolated segments are randomly extracted from the arc segments. The arc segment radius is determined according to the read differential values, and the arc segments are corrected. Finally, the corrected arc segments are fitted as the circle after the cusp is expanded, and the circle after the cusp is expanded is used as the identity portrait of the device user.

[0112] Regarding the meaning of the difference in the above content, since the similarity is the degree of similarity between the equipment state and the standard state, the greater the similarity, the more standard the equipment. However, as time goes by, the usage time of the equipment continues to increase, the equipment state is likely to continue to deteriorate, and the similarity continues to decrease. Therefore, the similarity sequence is likely to be a decreasing sequence. Of course, if a maintenance process is introduced, there may be some similarities in the similarity sequence that increase in similarity. Combined with this explanation, the values ​​in the difference sequence are likely to be negative, and the smaller the negative value (the larger the absolute value), the greater the degree of deterioration of the equipment.

[0113] The process of determining the segmentation step length is as follows:

[0114] S=αlnN; where S is the segmentation step size and N is the number of non-zero elements in the difference sequence.

[0115] The segmentation step is proportional to the number of non-zero elements in the difference sequence, but as the number of non-zero elements in the difference sequence increases, the increase in the segmentation step decreases continuously; the segmentation step means that the circle is divided into segments at certain intervals. The larger the segmentation step, the larger each arc segment obtained by segmentation, and the greater the impact of an adjustment process (adjusting one arc segment); in layman's terms, the more non-zero elements in the difference sequence, the more times it has deteriorated, and the greater the degree of adjustment of the identity portrait.

[0116] The process of determining the arc radius is:

[0117] Where R ′is the arc radius after correction, R is the arc radius before correction, A is a preset constant, and d is the differential value, which is the latter value in the differential sequence minus the former value.

[0118] The arc segment radius refers to the adjustment process of each arc segment. Every time a differential value is read, an arc segment is randomly selected from all arc segments. This isolated segment has a radius, and the radius is adjusted. The smaller the differential value, the larger the (Ad) item. The larger the term is and the value is in the range of 0 to 1, the smaller the radius is. Its practical meaning is that the smaller the difference is, the greater the degree of deterioration of the device is, and the smaller the corrected radius is. The (Ad) term indicates the degree of deterioration of the device.

[0119] It is worth mentioning that the A value is pre-set by the staff to adjust the value range of (Ad). Different value ranges correspond to different growth rates.

[0120] Figure 3 This is a second sub-flow diagram of the device information push method, wherein the steps of obtaining identity portraits of all device users within a preset time range corresponding to each device, comparing the identity portraits of all device users, and self-adjusting the identity portrait of each device user include:

[0121] Step S201: Based on the device, obtain the identity portraits of all device users within a preset time range corresponding to each device;

[0122] Step S202: Reading the radius of the circle corresponding to each identity portrait, comparing it with a preset radius threshold, determining a scaling ratio, and scaling the identity portrait based on the scaling ratio;

[0123] Step S203: Compare the scaled identity portraits of all device users to determine an average identity portrait, and adjust the identity portrait of each device user based on the average identity portrait;

[0124] Step S204: Restore the adjusted identity portrait based on the scaling ratio to obtain the identity portrait of each device user.

[0125] In an example of the technical solution of the present invention, the self-adjustment process of the identity portrait is explained. Taking the device as the benchmark, the identity portraits of all device users within a preset time range corresponding to each device are obtained, that is, the identity portraits of all device users are clustered based on the same device or the same type of device. The same device may be leased to different device users, and the qualifications of these device users may vary greatly. Therefore, it is necessary to perform statistics first and normalize the scale, that is, read the radius of the circle corresponding to each identity portrait, compare it with the preset radius threshold, determine the scaling ratio, and scale the identity portrait based on the scaling ratio. At this time, all identity portraits are at the same scale, and the extended parts of the identity portraits at the same scale are compared and then adjusted. The adjustment goal is to eliminate part of the extended part. After the identity portrait of each device user is adjusted, the adjusted identity portrait is restored based on the scaling ratio. The restored identity portrait is the identity portrait of each device user.

[0126] Among them, regarding step S203, step S203 is actually a simple graphic analysis process, which calculates the average graphic of a bunch of graphics (such as the average state of the capability graph), and then adjusts each image based on the average graphic.

[0127] Figure 4 This is a third sub-flow diagram of the device information push method. The steps of receiving device information uploaded by a device provider and determining the push probability of each device user based on the self-adjusted identity profile of the device user include:

[0128] Step S301: receiving device information uploaded by the device provider;

[0129] Step S302: Obtain the target user of the device information and read the self-adjusted identity portrait of each target user;

[0130] Step S303: Obtain the delivery costs of the device provider and the target user, and determine the push probability of each target user based on the delivery cost and the identity profile.

[0131] In an example of the technical solution of the present invention, the process of determining the push probability is explained, receiving device information uploaded by the device provider, and obtaining the target user of the device information. The target user is the device user whose production field overlaps with the device. With the help of a conventional word recognition model, the target user acquisition process can be realized, which is equivalent to matching a limited number of device users among various device users based on the device information, called target users.

[0132] After obtaining the target user, the self-adjusted identity portrait of each target user is read, the delivery cost of the device provider and the target user is obtained, and the push probability of each target user is determined based on the delivery cost and the identity portrait.

[0133] The process of determining the push probability is as follows:

[0134] Where P is the push probability, S is the area of ​​the target user's identity portrait, S0 is the preset area threshold, and β is the preset correction coefficient.

[0135] In an example of the technical solution of the present invention, the process of determining the push probability is explained. From the above content, it can be concluded that the more times the device deteriorates and the greater the degree of deterioration, the more the identity portrait will shrink. Therefore, the area of ​​the identity portrait is read, divided by the preset area threshold, and a correction coefficient is introduced to obtain the push probability.

[0136] Figure 5 This is a fourth sub-flow diagram of the device information push method, wherein the step of pushing device information to the device user based on the push probability and forwarding it to the device provider upon receiving a response request from the device user includes:

[0137] Step S401: constructing a buffer pool;

[0138] Step S402: Pushing device information to the device user based on the push probability in the buffer pool;

[0139] Step S403: querying the device information received by each device user, comparing the device information, and determining the floating device information based on the comparison result;

[0140] Step S404: Pushing the floating device information to other device users except the original device user for a second time;

[0141] Step S405: Execute in a loop until the device information received by each device user meets the preset information conditions;

[0142] Step S406: Execute the push results in the buffer pool, and forward them to the device provider when receiving a response request from the device user.

[0143] In an example of the technical solution of the present invention, in the process of pushing device information based on push probability, a buffer process is added and a buffer pool is constructed. In the buffer pool, device information is pushed to the device user based on the push probability, which is equivalent to simulating the push process. At the same time, the device information received by each device user is queried, the device information is compared, and the similarity of the device information is determined. If the similarity reaches a preset similarity threshold, one device information is selected from the two device information as floating device information. Each device user can obtain some floating device information, and these floating device information are pushed a second time to other device users; this process is executed in a loop so that the device information received by each device user is as different as possible, thereby expanding its device receiving surface; when the device information received by each device user meets the preset information conditions, the push result in the buffer pool is executed, and when a response request from the device user is received, it is forwarded to the device provider.

[0144] It should be noted that there are many types of information conditions, one of which is the standard deviation condition:

[0145] Obtain all device information of each device user, compare them pairwise, calculate similarity, and then calculate the mean similarity. Each device user will have a mean similarity. Calculate the standard deviation of all similarity means. When the standard deviation is less than the preset standard deviation threshold, it is considered that the preset information condition is met.

[0146] There is also a simpler condition, which is the number condition. In actual applications, the loop process is executed two or three times, and basically the device information obtained by each device user is very different. Therefore, the information condition is directly set to the number threshold. When the number of cycles reaches the number threshold, the loop can be jumped out; under extreme conditions, step S405 can be directly omitted because the corresponding effect has been achieved after two information push processes.

[0147] Figure 6 FIG. 1 is a structural block diagram of a device information push system. In an embodiment of the present invention, a device information push system 10 includes:

[0148] The identity profile creation module 11 is used to receive individual information sent by the device user, collect statistics on the device user's device usage based on the individual information, and create an identity profile of the device user;

[0149] The self-adjustment module 12 is used to obtain the identity profiles of all device users within a preset time range corresponding to each device, compare the identity profiles of all device users, and self-adjust the identity profile of each device user;

[0150] The push probability determination module 13 is configured to receive device information uploaded by the device provider and determine the push probability of each device user based on the self-adjusted identity profile of the device user;

[0151] The device information forwarding module 14 is configured to push the device information to the device user based on the push probability, and forward the device information to the device provider upon receiving a response request from the device user.

[0152] Furthermore, the identity portrait creation module 11 includes:

[0153] A filling information receiving unit is used to send a preset template to the device user and receive the filling information of the device user; the template at least includes the establishment years, credit capacity and guarantor information;

[0154] The record acquisition unit is used to acquire the device usage record of the device user; the device usage record is the device status containing the time node; the time node is a relative time point based on the lease time,

[0155] An evaluation score calculation unit is used to compare each piece of information in the filled information with the preset standard information and determine the evaluation score based on the comparison result;

[0156] a construction unit, configured to determine a radius according to the evaluation score and construct a circle;

[0157] The expansion unit is used to expand the circle at the cusp according to the device status containing the time node, and use the circle after the cusp expansion as the identity portrait of the device user.

[0158] Specifically, the content of expanding the cusp of a circle according to the device status containing the time node and using the circle after the cusp expansion as the identity portrait of the device user includes:

[0159] Compare the device status with the preset standard device status and calculate the similarity;

[0160] Arrange similarities according to time nodes to obtain a similarity sequence;

[0161] Calculate the difference sequence of the similarity sequence and regularize the difference sequence according to the preset difference threshold; the regularization process is: set the difference greater than the preset difference threshold to zero;

[0162] The segmentation step is determined according to the number of non-zero elements in the difference sequence, and the circle is divided into arc segments according to the segmentation step;

[0163] Read the differential values ​​in sequence, randomly select isolated segments in the arc segment, determine the arc segment radius based on the read differential values, and correct the arc segment;

[0164] Fit the corrected arc segment as a circle after the cusp is expanded, and use the circle after the cusp is expanded as the identity portrait of the device user;

[0165] The process of determining the segmentation step length is as follows:

[0166] S = αlnN; where S is the segmentation step size and N is the number of non-zero elements in the difference sequence;

[0167] The process of determining the arc radius is:

[0168] Where R ′ is the arc radius after correction, R is the arc radius before correction, A is a preset constant, and d is the differential value, which is the latter value in the differential sequence minus the former value.

[0169] Furthermore, the self-regulating module 12 includes:

[0170] A portrait acquisition unit, configured to acquire, based on the device, the identity portraits of all device users within a preset time range corresponding to each device;

[0171] A portrait scaling unit, configured to read the radius of the circle corresponding to each identity portrait, compare it with a preset radius threshold, determine a scaling ratio, and scale the identity portrait based on the scaling ratio;

[0172] A profile adjustment unit, configured to compare the scaled identity profiles of all device users, determine an average identity profile, and adjust the identity profile of each device user based on the average identity profile;

[0173] The portrait restoration unit is used to restore the adjusted identity portrait based on the scaling ratio to obtain the identity portrait of each device user.

[0174] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A device information push method, characterized in that: The method comprises: Receive individual information sent by the device user, collect statistics on the device user's device usage based on the individual information, and create an identity profile of the device user; Obtain the identity profiles of all device users within a preset time range corresponding to each device, compare the identity profiles of all device users, and self-adjust the identity profile of each device user; Receive device information uploaded by device providers and determine the push probability for each device user based on the self-adjusted identity profile of the device user; The device information is pushed to the device user based on the push probability, and when a response request is received from the device user, it is forwarded to the device provider.

2. The device information push method according to claim 1, characterized in that: The steps of receiving the individual information sent by the device user, collecting statistics on the device user's device usage based on the individual information, and creating an identity profile of the device user include: Sending a preset template to the device user and receiving the device user's filled-in information; the template at least includes the establishment years, creditworthiness and guarantor information; Obtain the device usage record of the device user; the device usage record is the device status containing the time node; the time node is a relative time point based on the rental time, Compare each item of information in the filled information with the preset standard information, and determine the evaluation score based on the comparison results; Determine the radius according to the evaluation score and construct a circle; The circle is expanded at its cusp according to the device status containing the time node, and the circle after the cusp expansion is used as the identity portrait of the device user.

3. The device information push method according to claim 2, characterized in that: The content of expanding the circle according to the device status containing the time node and using the circle after the cusp expansion as the identity portrait of the device user includes: Compare the device status with the preset standard device status and calculate the similarity; Arrange similarities according to time nodes to obtain a similarity sequence; Calculate the difference sequence of the similarity sequence and regularize the difference sequence according to the preset difference threshold; the regularization process is: set the difference greater than the preset difference threshold to zero; The segmentation step is determined according to the number of non-zero elements in the difference sequence, and the circle is divided into arc segments according to the segmentation step; Read the differential values ​​in sequence, randomly select isolated segments in the arc segment, determine the arc segment radius based on the read differential values, and correct the arc segment; Fit the corrected arc segment as a circle after the cusp is expanded, and use the circle after the cusp is expanded as the identity portrait of the device user; The process of determining the segmentation step length is as follows: S = αlnN; where S is the segmentation step size and N is the number of non-zero elements in the difference sequence; The process of determining the arc radius is: Where R ′ is the arc radius after correction, R is the arc radius before correction, A is a preset constant, and d is the differential value, which is the latter value in the differential sequence minus the former value.

4. The device information push method according to claim 3, characterized in that: The steps of obtaining identity portraits of all device users within a preset time range corresponding to each device, comparing the identity portraits of all device users, and self-adjusting the identity portrait of each device user include: Based on the device, obtain the identity portrait of all device users within the preset time range corresponding to each device; Read the radius of the circle corresponding to each identity portrait, compare it with a preset radius threshold, determine the scaling ratio, and scale the identity portrait based on the scaling ratio; Compare the scaled identity profiles of all device users to determine an average identity profile, and adjust the identity profile of each device user based on the average identity profile; The adjusted identity portrait is restored based on the scaling ratio to obtain the identity portrait of each device user.

5. The device information push method according to claim 1, characterized in that: The step of receiving device information uploaded by a device provider and determining a push probability for each device user based on the self-adjusted identity profile of the device user includes: Receive device information uploaded by the device provider; Obtain the target user of the device information and read the self-adjusted identity profile of each target user; Obtaining the delivery costs of the device provider and the target user, and determining the push probability of each target user based on the delivery costs and the identity profile; The process of determining the push probability is as follows: Where P is the push probability, S is the area of ​​the target user's identity portrait, S0 is the preset area threshold, and β is the preset correction coefficient.

6. The device information push method according to claim 1, characterized in that: The step of pushing device information to the device user based on the push probability and forwarding it to the device provider upon receiving a response request from the device user includes: Build a buffer pool; Push device information to device users based on push probability in the buffer pool; Query the device information received by each device user, compare the device information, and determine the floating device information based on the comparison results; Push the floating device information to other device users besides the original device user for a second time; The process is executed in a loop until the device information received by each device user meets the preset information conditions; The push results in the execution buffer pool are forwarded to the device provider when a response request is received from the device user.

7. A device information push system, characterized in that: The system comprises: An identity profile creation module is used to receive individual information sent by the device user, collect statistics on the device user's device usage based on the individual information, and create an identity profile of the device user; A self-adjustment module is used to obtain the identity portraits of all device users within a preset time range corresponding to each device, compare the identity portraits of all device users, and self-adjust the identity portrait of each device user; A push probability determination module is used to receive device information uploaded by device providers and determine the push probability of each device user based on the self-adjusted identity profile of the device user; The device information forwarding module is used to push device information to the device user based on the push probability, and forward it to the device provider when receiving a response request from the device user.

8. The device information push system according to claim 7, characterized in that: The identity portrait creation module includes: A filling information receiving unit is used to send a preset template to the device user and receive the filling information of the device user; the template at least includes the establishment years, credit capacity and guarantor information; The record acquisition unit is used to acquire the device usage record of the device user; the device usage record is the device status containing the time node; the time node is a relative time point based on the lease time, An evaluation score calculation unit is used to compare each piece of information in the filled information with the preset standard information and determine the evaluation score based on the comparison result; a construction unit, configured to determine a radius according to the evaluation score and construct a circle; The expansion unit is used to expand the circle at the cusp according to the device status containing the time node, and use the circle after the cusp expansion as the identity portrait of the device user.

9. The device information push system according to claim 8, characterized in that: The content of expanding the circle according to the device status containing the time node and using the circle after the cusp expansion as the identity portrait of the device user includes: Compare the device status with the preset standard device status and calculate the similarity; Arrange similarities according to time nodes to obtain a similarity sequence; Calculate the difference sequence of the similarity sequence and regularize the difference sequence according to the preset difference threshold; the regularization process is: set the difference greater than the preset difference threshold to zero; The segmentation step is determined according to the number of non-zero elements in the difference sequence, and the circle is divided into arc segments according to the segmentation step; Read the differential values ​​in sequence, randomly select isolated segments in the arc segment, determine the arc segment radius based on the read differential values, and correct the arc segment; Fit the corrected arc segment as a circle after the cusp is expanded, and use the circle after the cusp is expanded as the identity portrait of the device user; The process of determining the segmentation step length is as follows: S = αlnN; where S is the segmentation step size and N is the number of non-zero elements in the difference sequence; The process of determining the arc radius is: Where R ′ is the arc radius after correction, R is the arc radius before correction, A is a preset constant, and d is the differential value, which is the latter value in the differential sequence minus the former value.

10. The device information push system according to claim 7, characterized in that: The self-regulating module comprises: A portrait acquisition unit, configured to acquire, based on the device, the identity portraits of all device users within a preset time range corresponding to each device; A portrait scaling unit, configured to read the radius of the circle corresponding to each identity portrait, compare it with a preset radius threshold, determine a scaling ratio, and scale the identity portrait based on the scaling ratio; A profile adjustment unit, configured to compare the scaled identity profiles of all device users, determine an average identity profile, and adjust the identity profile of each device user based on the average identity profile; The portrait restoration unit is used to restore the adjusted identity portrait based on the scaling ratio to obtain the identity portrait of each device user.

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