Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings. The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 is a schematic diagram of an application scenario of a shelf placement method based on user behavior according to some embodiments of the present disclosure.
In the application scenario of fig. 1, first, the computing device 101 may perform a gridding process on the target area 102, resulting in a grid area set 103. Secondly, the computing device 101 may obtain the user hotspot information of each grid area in the grid area set 103, which is shot by the thermal imaging sensing apparatus within a preset time period, to obtain a user hotspot information set 104. Wherein the user hotspot information comprises a hotspot value. Then, the computing device 101 may select, from the user hotspot information set 104, user hotspot information with a hotspot value greater than or equal to a preset threshold as target user hotspot information, to obtain a target user hotspot information group 105. Then, the computing device 101 may determine a grid area corresponding to each target user hotspot information in the target user hotspot information group 105 as a target grid area, so as to obtain a target grid area group 106. Then, the computing device 101 may obtain the shelf information corresponding to each target grid area in the target grid area group 106 to obtain the shelf information group 107. Finally, the computing device 101 may perform a sort-in process on each shelf corresponding to each shelf information in the shelf information group 107 according to each hot-point value included in the target user hot-point information group 105.
The computing device 101 may be hardware or software. When the computing device is hardware, it may be implemented as a distributed cluster composed of multiple servers or terminal devices, or may be implemented as a single server or a single terminal device. When the computing device is embodied as software, it may be installed in the hardware devices enumerated above. It may be implemented, for example, as multiple software or software modules to provide distributed services, or as a single software or software module. And is not particularly limited herein.
It should be understood that the number of computing devices in FIG. 1 is merely illustrative. There may be any number of computing devices, as implementation needs dictate.
With continued reference to fig. 2, a flow 200 of some embodiments of a user behavior-based shelving method in accordance with the present disclosure is illustrated. The method may be performed by the computing device 101 of fig. 1. The shelf placing method based on the user behaviors comprises the following steps:
step 201, performing gridding processing on the target area to obtain a grid area set.
In some embodiments, referring to fig. 3, an executing entity (e.g., computing device 101 shown in fig. 1) of the user behavior-based shelving method may perform gridding processing on the target area to obtain a grid area set. Here, the gridding process may refer to a gridding division process. Here, the target area may refer to a shelving area in a store. As an example, the target area "a" may be subjected to a gridding process to obtain a grid area set "a, b, c, d, e, f, g, h, s".
Step 202, obtaining user hotspot information of each grid area in the grid area set, which is shot by the thermal imaging induction device within a preset time period, to obtain a user hotspot information set.
In some embodiments, the execution subject may obtain, from the device terminal, user hotspot information of each grid area in the set of grid areas captured by the thermal imaging sensing apparatus within a preset time period in a wired connection manner or a wireless connection manner, to obtain a user hotspot information set. Wherein the user hotspot information comprises a hotspot value. Here, the thermal imaging sensing device may be a camera having a thermal imaging function. Here, the setting of the preset time period is not limited. Here, the hotspot value may characterize the activity level of the user within the grid area.
As an example, the user hotspot information of each grid area in the grid area set captured by the thermal imaging sensing device in 2021-01-05 to 2021-01-10 may be obtained, and the obtained user hotspot information set may be: [ a grid region, hotspot value: 7 ]; [ b grid area, hotspot value: 9 ]; [ c grid area, hotspot value: 8 ]; [ d grid area, hotspot value: 8 ]; [ e grid area, hotspot value: 10 ]; [ f grid area, hotspot value: 5 ]; [ f grid area, hotspot value: 4 ]; [ g grid area, hotspot value: 5 ]; [ h grid area, hotspot value: 4 ]; [ s grid area, hotspot value: 6].
Step 203, selecting the user hotspot information with the hotspot value greater than or equal to the preset threshold from the user hotspot information set as target user hotspot information to obtain a target user hotspot information group.
In some embodiments, the execution main body may select, from the user hotspot information set, user hotspot information having a hotspot value greater than or equal to a preset threshold as target user hotspot information, to obtain a target user hotspot information group. Here, the setting of the preset threshold is not limited.
As an example, the user hotspot information with the hotspot value greater than or equal to the preset threshold "8" may be selected from the user hotspot information set illustrated in step 202 as the target user hotspot information, so as to obtain a target user hotspot information group: [ b grid area, hotspot value: 9 ]; [ c grid area, hotspot value: 8 ]; [ d grid area, hotspot value: 8 ]; [ e grid area, hotspot value: 10].
Step 204, determining the grid area corresponding to each target user hotspot information in the target user hotspot information group as a target grid area, and obtaining a target grid area group.
In some embodiments, the execution subject may determine a grid area corresponding to each target user hotspot information in the target user hotspot information group as a target grid area, so as to obtain a target grid area group.
As an example, the grid area corresponding to each target user hotspot information in the target user hotspot information group illustrated in step 203 may be determined as a target grid area, so as to obtain a target grid area group: [ b grid region ]; [ c grid region ]; [ d grid region ]; [ e grid region ].
Step 205, obtaining shelf information corresponding to each target grid area in the target grid area group to obtain a shelf information group.
In some embodiments, the execution subject may obtain, from the device terminal, shelf information corresponding to each target grid area in the target grid area group in a wired connection manner or a wireless connection manner, to obtain the shelf information group. Here, the shelf information may refer to attribute information of the shelf, and may include, but is not limited to, at least one of: shelf name.
As an example, the shelf information group may be: [ b shelf ]; [ c shelf ]; [ d shelf ]; [ e shelf ].
And step 206, performing a placement process on each shelf corresponding to each shelf information in the shelf information group according to each hot point value included in the target user hot point information group.
In some embodiments, first, the executing entity may perform descending order processing on each hotspot value included in the target user hotspot information group, and generate a hotspot value sequence. Then, the execution subject may sequentially place the shelves corresponding to the shelf information in the shelf information group according to the magnitude of the hot spot value in the hot spot value sequence. Here, the placing process may refer to a placing/moving process. For example, [ e-shelf ] can be put to the b-grid area.
In some optional implementation manners of some embodiments, the executing body may further perform a process of arranging shelves corresponding to the shelf information in the shelf information group by:
firstly, ordering the hot spot information of each target user in the hot spot information group of the target user according to the sequence of hot spot values from large to small to obtain a hot spot information sequence of the target user.
And secondly, sequencing the shelf information in the shelf information group according to the target user hotspot information sequence to obtain a shelf information sequence. Here, the execution subject may sort the shelf information in the shelf information group according to an order of the target user hotspot information in the target user hotspot information sequence, so as to obtain the shelf information sequence. Here, the shelf information in the shelf information sequence further includes a shelf length and width attribute value.
And thirdly, based on a preset shelf placement area group, performing arrangement processing on each shelf corresponding to each shelf information in the shelf information sequence.
In practice, the above-mentioned third step may comprise the following sub-steps:
the first substep is to determine the area length and width attribute value of each shelf placement area in the shelf placement area group to obtain an area length and width attribute value group. Here, the area length and width attribute value may refer to a length attribute value and a width attribute value of the shelving area.
A second substep of executing, for each shelf corresponding to shelf information in the shelf information sequence, the following processing steps based on the region length/width attribute value group:
1. and selecting an area length/width attribute value matching the shelf length/width attribute value included in the shelf information from the area length/width attribute value group as a candidate area length/width attribute value, thereby obtaining a candidate area length/width attribute value group. Here, the area length/width attribute value that matches the shelf length/width attribute value included in the shelf information may be an area length/width attribute value whose area length/width attribute value is equal to or greater than the shelf length/width attribute value.
2. And determining the matching degree of the shelf length and width attribute value and each candidate area length and width attribute value in the candidate area length and width attribute value set to obtain a matching degree set. Here, the sum of the ratio of the shelf length attribute value to the candidate area length attribute value and the ratio of the shelf width attribute value to the candidate area width attribute value may be determined as the degree of matching. Here, the value of the ratio can be retained to two significant digits after the decimal point. For example, the shelf length attribute value may be "2 meters" and the shelf width attribute value may be "1 meter". The candidate region length attribute value may be "2.1 meters" and the candidate region width attribute value may be "1.1 meters". Thus, the ratio "0.95" of "2 meters" to "2.1 meters" and the sum "1.85" of the ratio "0.9" of "1 meter" to "1.1 meters" can be determined as the degree of matching.
3. And selecting the matching degree with the maximum matching degree from the matching degree group as the target matching degree.
4. And determining the shelf placing area corresponding to the target matching degree as the shelf placing area corresponding to the shelf information.
5. And performing a deletion process on an area length/width attribute value corresponding to the shelf placement area among the area length/width attribute value groups to update the area length/width attribute value groups.
6. The updated region length/width attribute value group is determined as a region length/width attribute value group, and the above-described processing steps are executed again.
And a third substep of placing the shelf corresponding to each shelf information in the shelf information sequence according to the shelf placing area corresponding to the shelf information.
The above embodiments of the present disclosure have the following advantages: through the shelf placing method based on the user behaviors, reasonable layout of the shelves can be achieved according to the behaviors of the user, and therefore circulation efficiency of articles is improved. Furthermore, the shopping experience of the user is improved, and the flow loss of the user is reduced. Specifically, the reason for the loss of user traffic in the offline distribution store is: the goods shelves are not reasonably arranged according to the behaviors of the users, so that the circulation efficiency of the goods is low, and the shopping experience of the users is poor. Based on this, in the shelf placement method based on user behaviors of some embodiments of the present disclosure, first, a target area is subjected to gridding processing to obtain a grid area set. Therefore, the shelf areas in the stores can be divided, and the shelf areas with high hot spot degree can be conveniently divided in the follow-up process. And secondly, acquiring user hotspot information of each grid area in the grid area set, which is shot by the thermal imaging induction device within a preset time period, so as to obtain a user hotspot information set. Thus, the user hotspot level of each grid area can be determined. And then, selecting the user hotspot information with the hotspot value greater than or equal to a preset threshold value from the user hotspot information set as target user hotspot information to obtain a target user hotspot information group. Therefore, the labor cost for resetting the shelf can be reduced, and the shelf in the hot spot area can be conveniently and reasonably reset subsequently. And then, determining a grid area corresponding to each target user hotspot information in the target user hotspot information group as a target grid area to obtain a target grid area group. And then, acquiring shelf information corresponding to each target grid area in the target grid area group to obtain a shelf information group. Thus, data support is provided for subsequent re-staging of shelves within the target grid area. And finally, according to each hot point value included in the target user hot point information group, performing arrangement processing on each shelf corresponding to each shelf information in the shelf information group. Therefore, the shelves can be reasonably arranged according to the behaviors of the user. Thereby, the circulation efficiency of article has been promoted. Furthermore, the shopping experience of the user is improved, and the flow loss of the user is reduced.
With further reference to fig. 4, a flow 400 of further embodiments of a user behavior-based shelving method in accordance with the present disclosure is illustrated. The method may be performed by the computing device 101 of fig. 1. The shelf placing method based on the user behaviors comprises the following steps:
step 401, performing gridding processing on the target area to obtain a grid area set.
Step 402, obtaining user hotspot information of each grid area in a grid area set shot by the thermal imaging induction device within a preset time to obtain a user hotspot information set.
Step 403, selecting the user hotspot information with the hotspot value greater than or equal to the preset threshold from the user hotspot information set as target user hotspot information, and obtaining a target user hotspot information group.
Step 404, determining a grid area corresponding to each target user hotspot information in the target user hotspot information group as a target grid area, so as to obtain a target grid area group.
Step 405, shelf information of each target grid area in the corresponding target grid area group is obtained, and a shelf information group is obtained.
And 406, performing arrangement processing on each shelf corresponding to each shelf information in the shelf information group according to each hot point value included in the target user hot point information group.
In some embodiments, the specific implementation manner and technical effects of steps 401 and 406 may refer to steps 201 and 206 in the embodiments corresponding to fig. 2, which are not described herein again.
Step 407 is to perform placement processing for an article corresponding to each item information included in each item information in the item information sequence.
In some embodiments, the shelf information further includes an item information group. The shelf information further includes a micro-bin shelf information group, the article information in the article information group includes an article name, an article number corresponding to the article name, an article length, width and height attribute value, and an article unit mass, the micro-bin shelf information in the micro-bin shelf information group includes a micro-bin shelf length, width and height attribute value, and the article information in the article information group corresponds to the micro-bin shelf information in the micro-bin shelf information group. An executing subject of the shelf placement method based on the user behavior (for example, the computing device 101 shown in fig. 1) may perform placement processing on an item corresponding to each item information included in each shelf information in the above-described shelf information sequence by various methods. Here, the micro-bin shelf information in the micro-bin shelf information group may further include a micro-bin shelf number. Here, the micro-warehouse shelf may refer to a shelf that is independent and places the same kind of goods.
In some optional implementation manners of some embodiments, the executing body may further perform placement processing on an item corresponding to each item information included in each item information in the shelf information sequence by:
the method comprises the steps of firstly, setting a bottom plate front shaft starting point of a micro-bin shelf corresponding to micro-bin shelf information corresponding to the article information as a coordinate origin, setting a long shaft corresponding to a micro-bin shelf length attribute value included in the micro-bin shelf information as a vertical shaft, setting a horizontal shaft corresponding to a micro-bin shelf width attribute value included in the micro-bin shelf information as a horizontal shaft, and setting a vertical shaft corresponding to a micro-bin shelf height attribute value included in the micro-bin shelf information as a vertical shaft, so as to establish a micro-bin shelf space coordinate system.
And secondly, determining the object coordinate corresponding to the object by using the length, width and height attribute values of the object included in the object information as a longitudinal coordinate value, a horizontal coordinate value and a vertical coordinate value respectively for the object corresponding to the object name included in the object information.
Thirdly, determining the article placement coordinates of each article corresponding to the article information in the micro-warehouse shelf through the following formula:
wherein the content of the first and second substances,
the vertical axis of the micro-warehouse shelf space coordinate system is shown.
The horizontal axis represents the above-mentioned micro-warehouse shelf space coordinate system.
The vertical axis of the micro-warehouse shelf space coordinate system is shown.
Is shown as
An article along
Ordinate values of axes.
Is shown as
An article along
The abscissa value of the axis.
Is shown as
An article along
Vertical coordinate values of the axes.
Indicating inclusion of said item informationThe number of items.
Is shown as
Item unit mass of an individual item.
Is shown as
An article longitudinal attribute value of the individual article.
Is shown as
An item horizontal property value of the individual item.
Is shown as
An item vertical attribute value for each item.
Indicating the article placement coordinates.
Fourthly, determining the placement distance of each article in the micro-warehouse shelf through the following formula:
wherein the content of the first and second substances,
indicating the placement distance.
And a vertical coordinate representing the origin in the micro-warehouse shelf space coordinate system.
And the abscissa represents the origin in the micro-warehouse shelf space coordinate system.
And the vertical coordinate of the origin in the micro-warehouse shelf space coordinate system is represented.
And fifthly, placing the articles according to the placing distance. Here, the execution body may control the placing robot to place the article according to the placing distance.
The formula and the related content in step 407 are used as an invention point of the present disclosure, and a technical problem mentioned in the background art is solved, namely "the user experiences poor feeling when obtaining the articles due to unreasonable placement of the articles in the shelf, and further the loss of the user flow rate". The factors that contribute to the loss of user traffic are often as follows: the articles in the shelf are not reasonably placed, so that the user has poor experience when obtaining the articles. If the above factors are solved, the effect of improving the user flow can be achieved. To achieve this effect, the present disclosure utilizes the length, width, and height attribute values of the micro-warehouse shelf to establish a spatial coordinate system of the micro-warehouse shelf. Therefore, the placing space of the micro-bin shelf can be divided in detail. In addition, the placing coordinates of the articles in the micro-warehouse shelf space coordinate system can be obtained through the length, width and height attribute values of the articles and the unit mass of the articles. Finally, the placing distance of the articles can be determined through a formula for solving the placing distance. Therefore, the articles can be reasonably placed by confirming the placing distance between the articles. Therefore, the user can take articles conveniently, the experience of the user is improved, and the loss of the user flow is reduced.
As can be seen from fig. 4, compared with the description of some embodiments corresponding to fig. 2, the process 400 of the shelf placement method based on user behavior in some embodiments corresponding to fig. 4 can reasonably place the items by confirming the placement distance between the items. Therefore, the user can take articles conveniently, the experience of the user is improved, and the loss of the user flow is reduced.
With further reference to fig. 5, as an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a shelf placement device based on user behavior, which correspond to those of the method embodiments described above in fig. 2, and which may be applied in various electronic devices.
As shown in fig. 5, the shelving device 500 based on user behavior of some embodiments includes: a gridding unit 501, a first acquisition unit 502, a selection unit 503, a determination unit 504, a second acquisition unit 505, and a homing unit 506. The gridding unit 501 is configured to perform gridding processing on a target area to obtain a grid area set; the first obtaining unit 502 is configured to obtain user hotspot information of each grid area in the grid area set, which is shot by the thermal imaging sensing device within a preset time, to obtain a user hotspot information set, where the user hotspot information includes a hotspot value; the selecting unit 503 is configured to select, from the user hotspot information sets, user hotspot information with a hotspot value greater than or equal to a preset threshold as target user hotspot information, to obtain a target user hotspot information set; the determining unit 504 is configured to determine a grid area corresponding to each target user hotspot information in the target user hotspot information group as a target grid area, so as to obtain a target grid area group; the second obtaining unit 505 is configured to obtain shelf information corresponding to each target grid area in the target grid area group, so as to obtain a shelf information group; the sorting unit 506 is configured to perform sorting processing on each shelf corresponding to each shelf information in the shelf information group according to each hot-point value included in the target user hot-point information group.
It will be understood that the elements described in the apparatus 500 correspond to various steps in the method described with reference to fig. 2. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 500 and the units included therein, and are not described herein again.
Referring now to FIG. 6, a block diagram of an electronic device (e.g., computing device 101 of FIG. 1) 600 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 6, electronic device 600 may include a processing means (e.g., central processing unit, graphics processor, etc.) 601 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage means 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the electronic apparatus 600 are also stored. The processing device 601, the ROM602, and the RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
Generally, the following devices may be connected to the I/O interface 605: input devices 606 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 607 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 608 including, for example, tape, hard disk, etc.; and a communication device 609. The communication means 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. While fig. 6 illustrates an electronic device 600 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 6 may represent one device or may represent multiple devices as desired.
In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network through the communication device 609, or installed from the storage device 608, or installed from the ROM 602. The computer program, when executed by the processing device 601, performs the above-described functions defined in the methods of some embodiments of the present disclosure.
It should be noted that the computer readable medium described above in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the apparatus; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: carrying out gridding processing on the target area to obtain a grid area set; acquiring user hotspot information of each grid area in the grid area set, which is shot by a thermal imaging induction device within a preset time, to obtain a user hotspot information set, wherein the user hotspot information comprises a hotspot value; selecting user hotspot information with a hotspot value greater than or equal to a preset threshold from the user hotspot information set as target user hotspot information to obtain a target user hotspot information group; determining a grid area corresponding to each target user hotspot information in the target user hotspot information group as a target grid area to obtain a target grid area group; acquiring shelf information corresponding to each target grid area in the target grid area group to obtain a shelf information group; and according to each hot point value included in the target user hot point information group, performing arrangement processing on each shelf corresponding to each shelf information in the shelf information group.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in some embodiments of the present disclosure may be implemented by software, and may also be implemented by hardware. The described units may also be provided in a processor, and may be described as: a processor includes a gridding unit, a first acquisition unit, a selection unit, a determination unit, a second acquisition unit, and a homing unit. For example, the selection unit may be further described as a unit that selects user hotspot information with a hotspot value greater than or equal to a preset threshold from the user hotspot information set as target user hotspot information to obtain a target user hotspot information group.
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.