Information display method, device and electronic device

Abstract

The embodiments of this specification propose an information display method, device and electronic device, wherein in the above-mentioned information display method, after obtaining the information of the target IoT device and the information between the target IoT device and the neighbor IoT device, the first group to which the target IoT device belongs is determined based on the above-mentioned information, and then the transfer probability of the neighbor IoT device included in the first group to the target IoT device is obtained; and the information expenditure weight corresponding to the neighbor IoT device included in the first group is obtained, and finally, based on the transfer probability and the information expenditure weight, the information push weight of the neighbor IoT device included in the first group on the target IoT device is determined, and based on the information push weight, the promotional information corresponding to the neighbor IoT device included in the first group is displayed on the target IoT device, so that the advertisements in a business district can be reasonably distributed and displayed, and a better effect of mutual drainage in the business district dimension can be achieved.

Description

[Technical field]

[0001] The embodiments of this specification relate to the field of Internet technology, and in particular, to an information display method, device and electronic device. [Background technology]

[0002] In recent years, Internet of Things (IoT) devices have been widely popularized and developed. Devices such as smart speakers and / or smart cash registers have been widely used. However, for some IoT devices, such as face recognition IoT cash register devices, there is a problem of difficulty in monetization.

[0003] In the existing related technologies, the common monetization solution is to operate advertisements through the screen of IoT devices, and then collect advertisement display fees to realize the monetization. There are two common advertising operation modes: the first is a centralized operation method, that is, the equipment manufacturer of IoT devices acts as a central node, receives the advertising needs of merchants (or the equipment manufacturer's own advertising needs), designs advertisements, and then distributes them to different equipment manufacturers. The second is a decentralized operation method, that is, the merchants operate the advertising content of IoT devices themselves, and merchants can freely change their own advertising pages without paying for it. Both methods have obvious disadvantages: the first method requires the equipment manufacturer to design the merchant's advertising needs, the design cost is very high, and because the advertising needs vary, it is difficult to scale; the second method, when the merchant operates by himself, often only places advertisements related to his own store, and cannot attract traffic to other stores, which loses the value of advertising, and this model is difficult to realize because the advertising content is generally designed and placed by the merchant himself.

[0004] Therefore, it is necessary to provide a solution to reasonably allocate and display advertisements, which can not only solve the problem of IoT device monetization, but also achieve the effect of attracting traffic between shops. [Summary of the invention]

[0005] The embodiments of this specification provide an information display method, device, and electronic device to achieve reasonable distribution and display of advertisements, which can not only solve the problem of IoT device monetization, but also achieve the effect of attracting traffic between shops.

[0006] In a first aspect, an embodiment of the present specification provides an information display method, comprising: obtaining information of a target Internet of Things (IoT) device and information between the target IoT device and neighbor IoT devices; wherein the neighbor IoT devices include IoT devices whose distance from the target IoT device is less than or equal to a predetermined distance threshold; determining a first group to which the target IoT device belongs based on the information of the target IoT device and the information between the target IoT device and the neighbor IoT devices; obtaining a transfer probability of the neighbor IoT devices included in the first group to the target IoT device; and obtaining information expenditure weights corresponding to the neighbor IoT devices included in the first group; determining, based on the transfer probability and the information expenditure weight, an information push weight of the neighbor IoT devices included in the first group on the target IoT device; and displaying, on the target IoT device, promotion information corresponding to the neighbor IoT devices included in the first group.

[0007] In the above information display method, after obtaining the information of the target IoT device and the information between the target IoT device and the neighbor IoT devices, the first group to which the target IoT device belongs is determined according to the information of the target IoT device and the information between the target IoT device and the neighbor IoT devices, and then the transfer probability of the neighbor IoT devices included in the first group to the target IoT device is obtained; and the information expenditure weight corresponding to the neighbor IoT devices included in the first group is obtained, and finally, according to the above transfer probability and the above information expenditure weight, the information push weight of the neighbor IoT devices included in the first group on the target IoT device is determined, and according to the above information push weight, the promotion information corresponding to the neighbor IoT devices included in the first group is displayed on the target IoT device, so that the advertisements in a business district can be reasonably distributed and displayed, which can not only solve the problem of IoT device monetization, but also achieve a better effect of mutual drainage in the business district dimension.

[0008] In one possible implementation, determining the first group to which the target IoT device belongs based on the information of the target IoT device and the information between the target IoT device and the neighbor IoT devices includes: constructing a graph model using the information of the target IoT device as a node and the information between the target IoT device and the neighbor IoT devices as an edge connecting the nodes; wherein the information of the target IoT device includes the transaction volume of the target IoT device, the location information of the target IoT device and the type of location of the target IoT device; the information between the target IoT device and the neighbor IoT devices includes the distance between the target IoT device and the neighbor IoT devices and the transition probability between the target IoT device and the neighbor IoT devices; training the graph model to obtain feature vectors of the nodes in the graph model; and clustering the nodes in the graph model based on the feature vectors to obtain the groups to which the nodes in the graph model belong.

[0009] In one possible implementation, obtaining the transfer probability of the neighbor IoT devices included in the first group to the target IoT device includes: obtaining the transfer probability between the IoT devices included in the first group; establishing a transfer probability matrix corresponding to the first group based on the transfer probability between the IoT devices included in the first group; and obtaining the transfer probability of the neighbor IoT devices included in the first group to the target IoT device based on the transfer probability matrix corresponding to the first group.

[0010] In one possible implementation, displaying the promotion information corresponding to the neighbor IoT devices included in the first group on the target IoT device according to the information push weight includes: sorting the information push weights; selecting a first predetermined number of neighbor IoT devices in the first group according to the sorting results; obtaining the promotion information corresponding to the first predetermined number of neighbor IoT devices; and displaying the promotion information corresponding to the first predetermined number of neighbor IoT devices on the target IoT device.

[0011] In one possible implementation, after obtaining the transfer probability between the IoT devices included in the first group, it also includes: sorting the transfer probability between the IoT devices included in the first group and the transfer probability between the IoT devices included in other groups except the first group; selecting a second predetermined number of transfer probabilities based on the sorting result; combining the second predetermined number of transfer probabilities with the type of place where the associated IoT devices are located to obtain a common user behavior pattern.

[0012] In one possible implementation, obtaining the transfer probability of the neighbor IoT device included in the first group to the target IoT device includes: if the transfer probability of the first neighbor IoT device in the first group to the target IoT device is a first predetermined probability, and the user behavior pattern corresponding to the first predetermined probability belongs to the user general behavior pattern, then adjusting the transfer probability of the first neighbor IoT device to the target IoT device to a second predetermined probability; wherein the first predetermined probability and the second predetermined probability are non-negative numbers, and the first predetermined probability is less than the second predetermined probability; the user behavior pattern corresponding to the first predetermined probability is obtained by combining the first predetermined probability with the type of place where the neighbor IoT device and the target IoT device are located.

[0013] In one possible implementation, before displaying the promotion information corresponding to the neighbor IoT devices included in the first group on the target IoT device based on the information push weight, it also includes: obtaining the promotion information uploaded by the IoT devices in the first group; reviewing the promotion information; the promotion information displayed on the target IoT device includes the promotion information that has passed the review.

[0014] In a second aspect, an embodiment of the present specification provides an information display device, comprising: an information acquisition module, used to acquire information of a target Internet of Things (IoT) device and information between the target IoT device and neighbor IoT devices; wherein the neighbor IoT devices include IoT devices whose distance from the target IoT device is less than or equal to a predetermined distance threshold; a group determination module, used to determine the first group to which the target IoT device belongs based on the information of the target IoT device and the information between the target IoT device and the neighbor IoT devices; a probability acquisition module, further used to acquire the transfer probability of the neighbor IoT devices included in the first group to the target IoT device; and to acquire the information expenditure weights corresponding to the neighbor IoT devices included in the first group; a weight determination module, used to determine the information push weights of the neighbor IoT devices included in the first group on the target IoT device based on the transfer probability and the information expenditure weights; and a display module, used to display the promotion information corresponding to the neighbor IoT devices included in the first group on the target IoT device based on the information push weights.

[0015] In one possible implementation, the group determination module includes: a construction submodule, which is used to construct a graph model using the information of the target IoT device as a node and the information between the target IoT device and the neighbor IoT devices as an edge connecting the nodes; wherein the information of the target IoT device includes the transaction volume of the target IoT device, the location information of the target IoT device and the type of place where the target IoT device is located; the information between the target IoT device and the neighbor IoT device includes the distance between the target IoT device and the neighbor IoT device and the transition probability between the target IoT device and the neighbor IoT device; a training submodule, which is used to train the graph model and obtain the feature vectors of the nodes in the graph model; and a clustering submodule, which is used to cluster the nodes in the graph model according to the feature vectors and obtain the groups to which the nodes in the graph model belong.

[0016] In one possible implementation, the probability acquisition module includes: an acquisition submodule, used to acquire the transfer probability between the IoT devices included in the first group; an establishment submodule, used to establish a transfer probability matrix corresponding to the first group based on the transfer probability between the IoT devices included in the first group; the acquisition submodule is also used to obtain the transfer probability of the neighbor IoT devices included in the first group to the target IoT device based on the transfer probability matrix corresponding to the first group.

[0017] In one possible implementation, the display module includes: a sorting submodule, used to sort the information push weights; a selection submodule, used to select a first predetermined number of neighbor IoT devices in the first group according to the sorting results; an information acquisition submodule, used to obtain the promotion information corresponding to the first predetermined number of neighbor IoT devices; and an information display submodule, used to display the promotion information corresponding to the first predetermined number of neighbor IoT devices on the target IoT device.

[0018] In one possible implementation, the device includes: a probability sorting module, which is used to sort the transition probabilities between the IoT devices included in the first group and the transition probabilities between the IoT devices included in other groups except the first group after the acquisition submodule acquires the transition probabilities between the IoT devices included in the first group; a probability selection module, which is used to select a second predetermined number of transition probabilities based on the sorting result; and a pattern acquisition module, which is used to combine the second predetermined number of transition probabilities with the type of place where the associated IoT device is located to obtain a common user behavior pattern.

[0019] In one possible implementation, the probability acquisition module is specifically used to adjust the transfer probability of the first neighbor IoT device to the target IoT device to a second predetermined probability when the transfer probability of the first neighbor IoT device in the first group to the target IoT device is a first predetermined probability and the user behavior pattern corresponding to the first predetermined probability belongs to the user common behavior pattern; wherein the first predetermined probability and the second predetermined probability are non-negative numbers, and the first predetermined probability is less than the second predetermined probability; the user behavior pattern corresponding to the first predetermined probability is obtained by combining the first predetermined probability with the type of place where the neighbor IoT device and the target IoT device are located.

[0020] In one possible implementation, the device also includes: an audit module; the information acquisition module is also used to obtain the promotion information uploaded by the IoT devices in the first group before the display module displays the promotion information corresponding to the neighbor IoT devices included in the first group; the audit module is used to audit the promotion information; the promotion information displayed on the target IoT device includes the promotion information approved by the audit module.

[0021] In a third aspect, an embodiment of the present specification provides an electronic device, comprising: at least one processor; and at least one memory communicatively connected to the processor, wherein: the memory stores program instructions executable by the processor, and the processor calls the program instructions to execute the method provided in the first aspect.

[0022] In a fourth aspect, an embodiment of the present specification provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions enable the computer to execute the method provided in the first aspect.

[0023] It should be understood that the second to fourth aspects of the embodiments of this specification are consistent with the technical solutions of the first aspect of the embodiments of this specification, and the beneficial effects achieved by each aspect and the corresponding feasible implementation methods are similar and will not be repeated here.

Brief Description of the Drawings

[0024] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 A flowchart of an information display method provided for one embodiment of this specification;

[0026] Figure 2 A flowchart of an information display method provided in another embodiment of this specification;

[0027] Figure 3 A flowchart of an information display method provided in yet another embodiment of this specification;

[0028] Figure 4 A flowchart of an information display method provided in yet another embodiment of this specification;

[0029] Figure 5 A flowchart of an information display method provided in yet another embodiment of this specification;

[0030] Figure 6 A schematic diagram of the structure of an information display device provided in one embodiment of this specification;

[0031] Figure 7 A schematic diagram of the structure of an information display device provided in another embodiment of this specification;

[0032] Figure 8 A schematic diagram of the structure of an electronic device provided in one embodiment of this specification. [Specific implementation method]

[0033] In order to better understand the technical solution of this specification, the embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0034] It should be clear that the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this specification.

[0035] The terms used in the embodiments of this specification are only for the purpose of describing specific embodiments, and are not intended to limit this specification. The singular forms "a", "said" and "the" used in the embodiments of this specification and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0036] In the existing related technologies, there are two common advertising operation modes for IoT devices: centralized operation method and decentralized operation method.

[0037] 1) IoT device-centralized advertising method: This method prepares advertisements in the cloud in advance (usually equipment vendors’ advertisements), and then directly sends them to different merchants’ IoT devices for display through cloud-based operating rules. For example, equipment vendors place advertisements on IoT devices to sell related IoT devices. Since this method places almost all advertisements from equipment vendors, the advertisements are all related to equipment vendors, and merchants cannot obtain traffic monetization from the advertisements, so they will not pay for them;

[0038] 2) Merchant-operated IoT device advertising method: IoT devices open the interface for advertising to merchants. Merchants need to design, upload and review the specific advertising content and display images themselves, but this type of electronic advertising requires merchants to have strong advertising design capabilities and is not convenient. In addition, this type of self-operated advertising often only designs the merchant's own products and cannot attract traffic from other stores to form economies of scale. Finally, since this type of advertising cannot bring good traffic-attracting effects, the probability of merchants paying for this service is also low.

[0039] In order to solve the problems existing in centralized solutions and decentralized solutions, the embodiments of this specification propose an information display method, namely, an IoT device network advertising delivery method based on intelligent regional advertising sharing. The above information display method combines the advantages of centralization and self-operation, that is, it allows merchants to upload, create advertisements and obtain display opportunities, and reasonably distributes and displays advertisements within a geographical business district at a central node (for example: cloud server), so as to achieve a better effect of mutual drainage in the business district dimension. Specifically, the information display method provided in the embodiments of this specification first delineates the "geographical business district" through a model, and the IoT devices of merchants in the same geographical business district will share advertisements, that is, the advertisements of merchant A can be delivered on the IoT devices of merchant B in the same business district. The specific advertising distribution method is calculated and recommended by the central node (advertisements are provided by merchants). In this method, the advantages of merchants designing advertisements by themselves in the decentralized solution and the global allocation of the center in the centralized solution are combined to maximize the advertising value. For example, the information display method provided in the embodiments of this specification can intelligently place advertisements in a region by analyzing user behavior patterns, allowing stores to attract traffic to each other and realize merchant value (for example, a large number of users habitually go to fruit store B to buy fruit after dining at restaurant A, so the advertisement of fruit store B can be displayed on the IoT device of restaurant A to attract more users to consume at fruit store B).

[0040] Figure 1 This is a flowchart of an information display method provided in one embodiment of this specification. The above information display method can be applied to a cloud server, such as Figure 1 As shown, the above information display method mainly includes the following steps:

[0041] Step 102: Locate the geographical business district of IoT devices.

[0042] Specifically, the cloud server can use the geographic location information of the IoT device and map information to define the business district for the IoT device; IoT devices belonging to the same business district will share their respective advertisements, thereby attracting traffic to other IoT devices and stores.

[0043] Step 104: Upload the advertisement content.

[0044] Specifically, the cloud server obtains the advertisement content uploaded by the merchant, and the cloud server reviews the advertisement content.

[0045] Step 106: User behavior pattern analysis.

[0046] Specifically, the cloud server can analyze the user behavior patterns of different business districts, and obtain the main user behavior patterns within the business district and the user behavior models that can be migrated between business districts.

[0047] Step 108, intelligent advertisement distribution.

[0048] Specifically, the cloud server can use the user's behavior model and the merchant's advertising expenditure as a guide to intelligently distribute different advertisements on different IoT devices, thereby achieving better traffic generation effects.

[0049] Figure 2 This is a flowchart of an information display method provided in another embodiment of this specification. The above information display method can be applied to a cloud server, such as Figure 2 As shown, the above information display method may include:

[0050] Step 202, obtaining information of the target IoT device and information between the target IoT device and neighbor IoT devices; wherein the neighbor IoT devices include IoT devices whose distance to the target IoT device is less than or equal to a predetermined distance threshold.

[0051] The above-mentioned predetermined distance threshold may be set according to system performance and / or implementation requirements during specific implementation, and this embodiment does not limit the size of the above-mentioned predetermined distance threshold.

[0052] In this embodiment, the information of the above-mentioned target IoT device includes the transaction volume of the target IoT device, the location information of the target IoT device and the type of place where the target IoT device is located; the information between the above-mentioned target IoT device and the neighboring IoT device includes the distance between the target IoT device and the neighboring IoT device and the transfer probability between the target IoT device and the neighboring IoT device.

[0053] The above-mentioned location information may be expressed by longitude and latitude.

[0054] The above transfer probability can be the probability of mutual traffic diversion between IoT devices. For example, assuming that the target IoT device is device A and the neighbor IoT device is device B, then the transfer probability between device A and device B can be the probability that the user consumes at the merchant where device A is located and then consumes at the merchant where device B is located; this transfer probability describes a user's behavior pattern. For example, if device A is in a restaurant and device B is in a fruit store, then the transfer probability between device A and device B can describe the probability that the user will go to the fruit store where device B is located to buy fruit after eating at the restaurant where device A is located.

[0055] Step 204: Determine the first group to which the target IoT device belongs based on the information of the target IoT device and the information between the target IoT device and the neighbor IoT devices.

[0056] The first group to which the target IoT device belongs may be the business district to which the target IoT device belongs. IoT devices belonging to the same business district will share their respective advertisements, thereby attracting traffic to other IoT devices and stores.

[0057] Step 206, obtaining the transfer probability of the neighbor IoT devices included in the first group to the target IoT device; and obtaining the information expenditure weights corresponding to the neighbor IoT devices included in the first group.

[0058] Step 208: Determine the information push weight of the neighbor IoT devices included in the first group on the target IoT device according to the above transfer probability and the above information expenditure weight.

[0059] Specifically, taking device A as the target IoT device, assume that there are M neighbor IoT devices in the business district to which device A belongs. The transfer probabilities of these M neighbor IoT devices to device A are [P1, P2, …, PM], respectively. P1, P2, …, PM should all be greater than zero. The corresponding information expenditure weights of these neighbor IoT devices are alpha1, alpha2, …, alphaM, respectively. Then, the information push weights of these neighbor IoT devices on device A are [P1*alpha1, P2*alpha2, …, PM*alphaM] respectively.

[0060] Step 210: Display promotion information corresponding to neighbor IoT devices included in the first group on the target IoT device according to the above information push weight.

[0061] Specifically, according to the above-mentioned information push weights, displaying the promotional information corresponding to the neighbor IoT devices included in the first group on the target IoT device can be: sorting the above-mentioned information push weights, and according to the sorting results, selecting a first predetermined number of neighbor IoT devices in the first group; obtaining the promotional information corresponding to the first predetermined number of neighbor IoT devices; and displaying the promotional information corresponding to the first predetermined number of neighbor IoT devices on the target IoT device.

[0062] During specific implementation, the first predetermined number may be set according to system performance and / or implementation requirements. This embodiment does not limit the size of the first predetermined number. For example, the first predetermined number may be 3.

[0063] Still taking device A as the target IoT device, after calculating and obtaining the information push weights of M neighbor IoT devices on device A, the above information push weights can be sorted, and then 3 neighbor IoT devices can be selected from the M neighbor IoT devices in order from high to low. In this way, the promotion information corresponding to these 3 neighbor IoT devices can be displayed on device A, for example: advertisements of the merchants corresponding to these 3 neighbor IoT devices. Of course, when displaying the promotion information corresponding to these 3 neighbor IoT devices on device A, the promotion information corresponding to these 3 neighbor IoT devices can also be allocated on device A according to the information push weights corresponding to these 3 neighbor IoT devices.

[0064] Furthermore, before step 210, the promotion information uploaded by the IoT devices in the first group may be obtained first, and the above promotion information may be reviewed. In this way, the promotion information displayed on the target IoT device includes the promotion information that has passed the review. That is to say, in this embodiment, the merchant to which the IoT device belongs can design the promotion information by itself and upload it to the cloud server through the application (application, APP) installed on the IoT device; or, the merchant to which the IoT device belongs can propose design requirements through the APP installed on the IoT device. After the equipment manufacturer completes the design of the promotion information according to the design requirements, the promotion information will be handed over to the merchant, and then the merchant will upload it to the cloud server through the APP installed on the IoT device. After the cloud server obtains the promotion information uploaded by the IoT device, it can use the classification model to determine whether the above promotion information contains illegal information such as pornography and / or violence. Only the promotion information that has passed the review can be sent to the target IoT device for display, otherwise it needs to be returned to the merchant for rectification.

[0065] In the above information display method, after obtaining the information of the target IoT device and the information between the target IoT device and the neighbor IoT devices, the first group to which the target IoT device belongs is determined according to the information of the target IoT device and the information between the target IoT device and the neighbor IoT devices, and then the transfer probability of the neighbor IoT devices included in the first group to the target IoT device is obtained; and the information expenditure weight corresponding to the neighbor IoT devices included in the first group is obtained, and finally, according to the above transfer probability and the above information expenditure weight, the information push weight of the neighbor IoT devices included in the first group on the target IoT device is determined, and according to the above information push weight, the promotion information corresponding to the neighbor IoT devices included in the first group is displayed on the target IoT device, so that the advertisements in a business district can be reasonably distributed and displayed, which can not only solve the problem of IoT device monetization, but also achieve a better effect of mutual drainage in the business district dimension.

[0066] Figure 3 A flowchart of an information display method provided in yet another embodiment of this specification, such as Figure 3 As shown in this manual Figure 2 In the illustrated embodiment, step 204 may include:

[0067] Step 302 , constructing a graph model using the information of the target IoT device as nodes and the information between the target IoT device and neighbor IoT devices as edges connecting the above nodes.

[0068] Specifically, this embodiment may use a graph model to cluster different IoT devices, with each category being a group (ie, a business district).

[0069] When constructing a graph model, the information of the target IoT device can be used as a node, and the information between the target IoT device and the neighbor IoT devices can be used as an edge connecting the above nodes to construct the graph model.

[0070] Step 304: train the graph model to obtain feature vectors of nodes in the graph model.

[0071] Step 306: Cluster the nodes in the graph model according to the feature vector to obtain the groups to which the nodes in the graph model belong.

[0072] Specifically, the more similar the feature vectors are, the closer the physical distance between the nodes is and the stronger the mutual drainage effect is. Therefore, by clustering the nodes in the graph model according to the feature vectors, the groups to which the nodes in the graph model belong can be obtained.

[0073] Figure 4 A flowchart of an information display method provided in yet another embodiment of this specification, such as Figure 4 As shown in this manual Figure 2 In the illustrated embodiment, step 206 may include:

[0074] Step 402: Obtain the transition probability between IoT devices included in the first group.

[0075] Step 404: Establish a transition probability matrix corresponding to the first group according to the transition probabilities between the IoT devices included in the first group.

[0076] Step 406: Obtain the transfer probability of the neighbor IoT devices included in the first group to the target IoT device according to the transfer probability matrix corresponding to the first group.

[0077] Specifically, after obtaining the transition probabilities between the IoT devices included in the first group, a transition probability matrix corresponding to the first group can be established. For example, for a first group including N IoT devices, an N*N transition probability matrix corresponds to the first group, and then, from the transition probability matrix corresponding to the first group, the transition probabilities of the neighbor IoT devices included in the first group to the target IoT device can be obtained.

[0078] Step 408: Obtain information expenditure weights corresponding to neighbor IoT devices included in the first group.

[0079] Among them, step 408 and steps 402 to 406 can be executed in parallel, or executed one after another. This embodiment does not limit the execution order of step 408 and steps 402 to 406.

[0080] Figure 5 A flowchart of an information display method provided in yet another embodiment of this specification, such as Figure 5 As shown in this manual Figure 4 In the illustrated embodiment, after step 402, the following may also be included:

[0081] Step 502: sort the transition probabilities between IoT devices included in the first group and the transition probabilities between IoT devices included in other groups except the first group.

[0082] Specifically, assuming that a group is a business district, this step is to sort the transfer probabilities between IoT devices in all business districts.

[0083] Step 504: Select a second predetermined number of transition probabilities according to the sorting result.

[0084] The second predetermined number may be set during specific implementation according to system performance and / or implementation requirements. This embodiment does not limit the size of the second predetermined number. For example, the second predetermined number may be 10.

[0085] Step 506 , combining the second predetermined number of transition probabilities with the type of location where the associated IoT device is located to obtain a common user behavior pattern.

[0086] Among them, the associated IoT devices include IoT devices associated with the second predetermined number of transfer probabilities. For example, assuming that one of the second predetermined number of transfer probabilities is the transfer probability of device B to device A, then the IoT devices associated with the transfer probability are device A and device B.

[0087] In specific implementation, after sorting the transfer probabilities between IoT devices in all business districts, 10 transfer probabilities can be selected in descending order, and then these 10 transfer probabilities are combined with the types of places where the IoT devices associated with these 10 transfer probabilities are located to obtain the common user behavior patterns. For example, the common user behavior patterns may include: users go to a fruit store after eating in a restaurant, users go to a cosmetics store after eating in a restaurant, and so on.

[0088] In this embodiment, the transfer probability of the neighbor IoT device included in the first group to the target IoT device obtained in step 206 can be: if the transfer probability of the first neighbor IoT device in the first group to the target IoT device is a first predetermined probability, and the user behavior pattern corresponding to the first predetermined probability belongs to the user's general behavior pattern, then the transfer probability of the first neighbor IoT device to the target IoT device is adjusted to a second predetermined probability; wherein the first predetermined probability and the second predetermined probability are non-negative numbers, and the first predetermined probability is less than the second predetermined probability.

[0089] The user behavior pattern corresponding to the first predetermined probability is obtained by combining the first predetermined probability with the types of places where the neighbor IoT device and the target IoT device are located.

[0090] That is, when the user behavior pattern corresponding to the first predetermined probability belongs to the general user behavior pattern, additional weighting will be performed when the promotion information corresponding to the first neighbor IoT device is delivered, thereby introducing a new behavior pattern in the first group.

[0091] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0092] Figure 6This is a schematic diagram of the structure of an information display device provided in one embodiment of this specification, such as Figure 6 As shown, the above-mentioned information display device may include: an information acquisition module 61, a group determination module 62, a probability acquisition module 63, a weight determination module 64 and a display module 65;

[0093] The information acquisition module 61 is used to acquire information of the target IoT device and information between the target IoT device and the neighbor IoT device; wherein the neighbor IoT device includes an IoT device whose distance to the target IoT device is less than or equal to a predetermined distance threshold;

[0094] A group determination module 62, configured to determine a first group to which the target IoT device belongs based on information of the target IoT device and information between the target IoT device and neighbor IoT devices;

[0095] The probability acquisition module 63 is further used to obtain the transfer probability of the neighbor IoT devices included in the first group to the target IoT device; and obtain the information expenditure weight corresponding to the neighbor IoT devices included in the first group;

[0096] A weight determination module 64, configured to determine the information push weight of the neighbor IoT devices included in the first group on the target IoT device according to the above-mentioned transfer probability and the above-mentioned information expenditure weight;

[0097] The display module 65 is used to display the promotion information corresponding to the neighbor IoT devices included in the first group on the target IoT device according to the above information push weight.

[0098] Figure 6 The information display device provided in the embodiment shown can be used to implement the present invention. Figure 2 The technical solution of the method embodiment shown, its implementation principle and technical effects can be further referred to the relevant description in the method embodiment.

[0099] Figure 7 A schematic diagram of the structure of an information display device provided in another embodiment of this specification, and Figure 6 Compared with the information display device shown, Figure 7 In the information display device shown, the group determination module 62 may include: a construction submodule 621, a training submodule 622 and a clustering submodule 623;

[0100] Among them, the construction submodule 621 is used to construct a graph model using the information of the target IoT device as a node and the information between the target IoT device and the neighbor IoT device as an edge connecting the above nodes; wherein the information of the target IoT device includes the transaction volume of the target IoT device, the location information of the target IoT device and the type of the location of the above target IoT device; the information between the target IoT device and the neighbor IoT device includes the distance between the target IoT device and the neighbor IoT device and the transfer probability between the target IoT device and the neighbor IoT device;

[0101] A training submodule 622 is used to train the graph model to obtain feature vectors of nodes in the graph model;

[0102] The clustering submodule 623 is used to cluster the nodes in the above-mentioned graph model according to the above-mentioned feature vectors, and obtain the groups to which the nodes in the above-mentioned graph model belong.

[0103] In this embodiment, the probability acquisition module 63 may include: an acquisition submodule 631 and an establishment submodule 632;

[0104] Wherein, the acquisition submodule 631 is used to obtain the transfer probability between the IoT devices included in the first group;

[0105] An establishment submodule 632 is used to establish a transition probability matrix corresponding to the first group according to the transition probabilities between the IoT devices included in the first group;

[0106] The acquisition submodule 631 is further configured to obtain the transfer probability of the neighbor IoT devices included in the first group to the target IoT device according to the transfer probability matrix corresponding to the first group.

[0107] In this embodiment, the display module 65 may include: a sorting submodule 651, a selection submodule 652, an information acquisition submodule 653 and an information display submodule 654;

[0108] Among them, the sorting submodule 651 is used to sort the above information push weights;

[0109] A selection submodule 652, configured to select a first predetermined number of neighbor IoT devices in the first group according to the sorting result;

[0110] The information acquisition submodule 653 is used to acquire promotion information corresponding to a first predetermined number of neighbor IoT devices;

[0111] The information display submodule 654 is used to display the promotion information corresponding to the first predetermined number of neighbor IoT devices on the target IoT device.

[0112] Furthermore, in this embodiment, the information display device may further include: a probability sorting module 66, a probability selection module 67 and a mode acquisition module 68;

[0113] The probability sorting module 66 is used to sort the transition probabilities between the IoT devices included in the first group and the transition probabilities between the IoT devices included in other groups except the first group after the acquisition submodule 631 acquires the transition probabilities between the IoT devices included in the first group;

[0114] A probability selection module 67, configured to select a second predetermined number of transition probabilities according to the sorting result;

[0115] The pattern acquisition module 68 is used to combine the second predetermined number of transition probabilities with the type of location where the associated IoT device is located to obtain a common user behavior pattern.

[0116] In this embodiment, the probability acquisition module 63 is specifically used to adjust the transfer probability of the first neighbor IoT device to the target IoT device to a second predetermined probability when the transfer probability of the first neighbor IoT device to the target IoT device in the first group is a first predetermined probability and the user behavior pattern corresponding to the first predetermined probability belongs to the user general behavior pattern; wherein the first predetermined probability and the second predetermined probability are non-negative numbers, and the first predetermined probability is less than the second predetermined probability;

[0117] The user behavior pattern corresponding to the first predetermined probability is obtained by combining the first predetermined probability with the types of places where the neighbor IoT device and the target IoT device are located.

[0118] Furthermore, in this embodiment, the information display device may further include: an audit module 69;

[0119] The information acquisition module 61 is further configured to acquire the promotion information uploaded by the IoT devices in the first group before the display module 65 displays the promotion information corresponding to the neighbor IoT devices included in the first group;

[0120] The review module 69 is used to review the above promotion information;

[0121] In this way, the promotion information displayed on the target IoT device includes the promotion information approved by the review module 69 .

[0122] Figure 7 The information display device provided in the embodiment shown can be used to implement the present invention. Figure 2 to Figure 5 The technical solution of the method embodiment shown, its implementation principle and technical effects can be further referred to the relevant description in the method embodiment.

[0123] Figure 8A schematic diagram of the structure of an electronic device provided in one embodiment of this specification, such as Figure 8 As shown, the electronic device may include at least one processor; and at least one memory connected to the processor in communication, wherein: the memory stores program instructions executable by the processor, and the processor calls the program instructions to execute the instructions of this specification. Figure 2 to Figure 5 The information display method provided by the illustrated embodiment.

[0124] The electronic device may be a server, such as a cloud server. This embodiment does not limit the form of the electronic device.

[0125] Figure 8 A block diagram of an exemplary electronic device suitable for implementing the embodiments of the present description is shown. Figure 8 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of this specification.

[0126] like Figure 8 As shown, the electronic device is in the form of a general computing device. The components of the electronic device may include, but are not limited to: one or more processors 410, a communication interface 420, a memory 430, and a communication bus 440 connecting different components (including the memory 430, the communication interface 420 and the processing unit 410).

[0127] The communication bus 440 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, or a local bus using any of a variety of bus structures. For example, the communication bus 440 may include, but is not limited to, an industry standard architecture (ISA) bus, a micro channel architecture (MAC) bus, an enhanced ISA bus, a video electronics standards association (VESA) local bus, and a peripheral component interconnection (PCI) bus.

[0128] Electronic devices typically include a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device, including volatile and non-volatile media, removable and non-removable media.

[0129] The memory 430 may include a computer system readable medium in the form of a volatile memory, such as a random access memory (RAM) and / or a cache memory. The memory 430 may include at least one program product having a set (e.g., at least one) of program modules configured to execute the instructions of the present invention. Figure 2 to Figure 5 Functionality of the illustrated embodiment.

[0130] A program / utility having a set (at least one) of program modules may be stored in the memory 430, such program modules including - but not limited to - an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include the implementation of a network environment. The program modules generally execute the instructions in this specification. Figure 2 to Figure 5 The functions and / or methods in the described embodiments.

[0131] The processor 410 executes various functional applications and data processing by running the programs stored in the memory 430, such as implementing the present specification. Figure 2 to Figure 5 The information display method provided by the illustrated embodiment.

[0132] The embodiment of the present specification provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, wherein the computer instructions enable the computer to execute the present specification. Figure 2 to Figure 5 The information display method provided by the illustrated embodiment.

[0133] The above-mentioned non-transient computer-readable storage medium can adopt any combination of one or more computer-readable media. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable storage media can be, for example, - but not limited to - electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples (non-exhaustive lists) of computer-readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (read only memory, ROM), erasable programmable read-only memories (erasable programmable read only memory, EPROM) or flash memory, optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this document, computer-readable storage media can be any tangible medium containing or storing programs, which can be used by instruction execution systems, devices or devices or used in combination with them.

[0134] Computer-readable signal media may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0135] The program code embodied on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wire, optical cable, radio frequency (RF), etc., or any suitable combination of the foregoing.

[0136] Computer program code for performing the operations of the present specification may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving 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 may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0137] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0138] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of this specification. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0139] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this specification, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0140] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of this specification includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of this specification belong.

[0141] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0142] It should be noted that the terminals involved in the embodiments of this specification may include but are not limited to personal computers (PCs), personal digital assistants (PDAs), wireless handheld devices, tablet computers, mobile phones, MP3 players, MP4 players, etc.

[0143] In the several embodiments provided in this specification, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0144] In addition, each functional unit in each embodiment of this specification may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0145] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform some steps of the method described in each embodiment of this specification. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, and other media that can store program codes.

[0146] The above description is only a preferred embodiment of this specification and is not intended to limit this specification. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of this specification should be included in the scope of protection of this specification.

Claims

1. An information display method, comprising: Acquire information of a target IoT device and information between the target IoT device and neighbor IoT devices; wherein the neighbor IoT devices include IoT devices whose distance to the target IoT device is less than or equal to a predetermined distance threshold; Determine a first group to which the target IoT device belongs according to the information of the target IoT device and the information between the target IoT device and a neighbor IoT device; Obtaining the transfer probability of the neighbor IoT devices included in the first group to the target IoT device; and obtaining the information expenditure weights corresponding to the neighbor IoT devices included in the first group; Determine, according to the transfer probability and the information expenditure weight, an information push weight of the neighbor IoT devices included in the first group on the target IoT device; According to the information push weight, promotion information corresponding to the neighbor IoT devices included in the first group is displayed on the target IoT device.

2. The method according to claim 1, wherein: The determining, according to the information of the target IoT device and the information between the target IoT device and the neighbor IoT device, the first group to which the target IoT device belongs includes: A graph model is constructed using the information of the target IoT device as a node and the information between the target IoT device and the neighbor IoT device as an edge connecting the nodes; wherein the information of the target IoT device includes the transaction volume of the target IoT device, the location information of the target IoT device and the type of location of the target IoT device; the information between the target IoT device and the neighbor IoT device includes the distance between the target IoT device and the neighbor IoT device and the transition probability between the target IoT device and the neighbor IoT device; Training the graph model to obtain feature vectors of nodes in the graph model; The nodes in the graph model are clustered according to the feature vector to obtain the groups to which the nodes in the graph model belong.

3. The method according to claim 1, wherein: The obtaining of the transfer probability of the neighbor IoT device included in the first group to the target IoT device includes: Obtaining a transition probability between IoT devices included in the first group; Establishing a transition probability matrix corresponding to the first group according to the transition probabilities between the IoT devices included in the first group; According to the transition probability matrix corresponding to the first group, the transition probability of the neighbor IoT devices included in the first group to the target IoT device is obtained.

4. The method according to claim 1, wherein: The displaying, on the target IoT device, the promotion information corresponding to the neighbor IoT devices included in the first group according to the information push weight includes: Sorting the information push weights; According to the sorting result, selecting a first predetermined number of neighbor IoT devices in the first group; Obtaining promotion information corresponding to the first predetermined number of neighbor IoT devices; The promotion information corresponding to the first predetermined number of neighbor IoT devices is displayed on the target IoT device.

5. The method according to claim 3, wherein: After obtaining the transition probability between IoT devices included in the first group, the method further includes: sorting the transition probabilities between the IoT devices included in the first group and the transition probabilities between the IoT devices included in other groups except the first group; Selecting a second predetermined number of transition probabilities according to the sorting result; The second predetermined number of transition probabilities is combined with the type of location where the associated IoT device is located to obtain a common user behavior pattern.

6. The method according to claim 5, wherein: The obtaining of the transfer probability of the neighbor IoT device included in the first group to the target IoT device includes: If the transfer probability of the first neighbor IoT device in the first group to the target IoT device is a first predetermined probability, and the user behavior pattern corresponding to the first predetermined probability belongs to the user general behavior pattern, the transfer probability of the first neighbor IoT device to the target IoT device is adjusted to a second predetermined probability; wherein the first predetermined probability and the second predetermined probability are non-negative numbers, and the first predetermined probability is less than the second predetermined probability; The user behavior pattern corresponding to the first predetermined probability is obtained by combining the first predetermined probability with the types of places where the neighbor IoT device and the target IoT device are located.

7. The method according to any one of claims 1 to 6, wherein: Before displaying the promotion information corresponding to the neighbor IoT devices included in the first group on the target IoT device according to the information push weight, the method further includes: Obtaining promotion information uploaded by IoT devices in the first group; Review the promotional information; The promotion information displayed on the target IoT device includes the promotion information that has been approved.

8. An information display device, comprising: An information acquisition module, used to acquire information of a target IoT device and information between the target IoT device and a neighbor IoT device; wherein the neighbor IoT device includes an IoT device whose distance to the target IoT device is less than or equal to a predetermined distance threshold; A group determination module, used to determine the first group to which the target IoT device belongs according to the information of the target IoT device and the information between the target IoT device and the neighbor IoT device; The probability acquisition module is further used to obtain the transfer probability of the neighbor IoT devices included in the first group to the target IoT device; and obtain the information expenditure weights corresponding to the neighbor IoT devices included in the first group; A weight determination module, configured to determine, based on the transfer probability and the information expenditure weight, an information push weight of the neighbor IoT devices included in the first group on the target IoT device; A display module is used to display the promotion information corresponding to the neighbor IoT devices included in the first group on the target IoT device according to the information push weight.

9. The device according to claim 8, wherein: The grouping determination module comprises: A construction submodule is used to construct a graph model using the information of the target IoT device as a node and the information between the target IoT device and the neighbor IoT device as an edge connecting the nodes; wherein the information of the target IoT device includes the transaction volume of the target IoT device, the location information of the target IoT device and the type of the location of the target IoT device; the information between the target IoT device and the neighbor IoT device includes the distance between the target IoT device and the neighbor IoT device and the transition probability between the target IoT device and the neighbor IoT device; A training submodule, used to train the graph model to obtain feature vectors of nodes in the graph model; The clustering submodule is used to cluster the nodes in the graph model according to the feature vector to obtain the groups to which the nodes in the graph model belong.

10. The device according to claim 8, wherein: The probability acquisition module includes: An acquisition submodule, used to acquire the transition probability between IoT devices included in the first group; Establishing a submodule, used to establish a transition probability matrix corresponding to the first group according to the transition probabilities between the IoT devices included in the first group; The acquisition submodule is further used to obtain the transfer probability of the neighbor IoT devices included in the first group to the target IoT device according to the transfer probability matrix corresponding to the first group.

11. The device according to claim 8, wherein: The display module comprises: A sorting submodule, used to sort the information push weights; A selection submodule, configured to select a first predetermined number of neighbor IoT devices in the first group according to the sorting result; An information acquisition submodule, used to acquire promotion information corresponding to the first predetermined number of neighbor IoT devices; The information display submodule is used to display the promotion information corresponding to the first predetermined number of neighbor IoT devices on the target IoT device.

12. The device according to claim 10, wherein: Also includes: a probability sorting module, configured to sort the transition probabilities between the IoT devices included in the first group and the transition probabilities between the IoT devices included in other groups except the first group after the acquisition submodule acquires the transition probabilities between the IoT devices included in the first group; A probability selection module, used for selecting a second predetermined number of transition probabilities according to the sorting result; The pattern acquisition module is used to combine the second predetermined number of transition probabilities with the type of location where the associated IoT device is located to obtain a common user behavior pattern.

13. The device according to claim 12, wherein: The probability acquisition module is specifically used to adjust the transfer probability of the first neighbor IoT device to the target IoT device to a second predetermined probability when the transfer probability of the first neighbor IoT device in the first group to the target IoT device is a first predetermined probability and the user behavior pattern corresponding to the first predetermined probability belongs to the user general behavior pattern; wherein the first predetermined probability and the second predetermined probability are non-negative numbers, and the first predetermined probability is less than the second predetermined probability; The user behavior pattern corresponding to the first predetermined probability is obtained by combining the first predetermined probability with the types of places where the neighbor IoT device and the target IoT device are located.

14. The device according to any one of claims 8 to 13, wherein: Also includes: Audit module; The information acquisition module is further configured to acquire the promotion information uploaded by the IoT devices in the first group before the display module displays the promotion information corresponding to the neighbor IoT devices included in the first group; The review module is used to review the promotion information; The promotion information displayed on the target IoT device includes the promotion information approved by the review module.

15. An electronic device, comprising: at least one processor; as well as at least one memory in communication with the processor, wherein: The memory stores program instructions executable by the processor, and the processor can execute the method according to any one of claims 1 to 7 by calling the program instructions. 16 . A non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions enable the computer to execute the method according to claim 1 .

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