CN108174350B - Positioning method and device - Google Patents
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- CN108174350B CN108174350B CN201711243057.4A CN201711243057A CN108174350B CN 108174350 B CN108174350 B CN 108174350B CN 201711243057 A CN201711243057 A CN 201711243057A CN 108174350 B CN108174350 B CN 108174350B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/023—Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
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- H—ELECTRICITY
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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Abstract
The embodiment of the invention provides a positioning method and a positioning device. The method comprises the following steps: collecting the position information of the user generated in the relevant time period of the merchant triggering to store behaviors; and determining the position information of the commercial tenant according to the position information of the user. By the embodiment of the invention, the accurate position of the merchant can be obtained, so that the problem that the manual marking of the merchant has a large error is solved, the distance between the user and the merchant can be accurately calculated, and the accuracy of o2o searching can be improved.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a positioning method and apparatus.
Background
With the rapid development of mobile terminals and communication technologies, location-based service needs are becoming more extensive, for example, a batch of o2o (Online to Offline) search services are emerging at present, and users can search for living information such as food and entertainment near the current location of the user by performing o2o search through an APP (Application program) in the mobile terminal, thereby greatly facilitating the life of the user.
The specific process of the o2o search is as follows: firstly, performing GPS (Global Positioning System) Positioning on a mobile terminal of a user to acquire a current position of the user; then, calculating the distance between the current position of the user and a nearby merchant; and finally, displaying the merchant information with the distance meeting the user screening range to the user.
In the process of calculating the distance between the current location of the user and the nearby business, location information of the business, such as longitude and latitude coordinates of the business, is needed. However, the longitude and latitude coordinates of the merchant are usually manually marked and uploaded by the merchant, and there are often large errors, which cause the distance between the user and the merchant to be inaccurate, and further affect the accuracy of the o2o search. In addition, the longitude and latitude coordinates of the merchant can be obtained in a manual street sweeping mode, but a large amount of labor and time cost are consumed.
Disclosure of Invention
In view of the above, the present invention has been made to provide a positioning method and apparatus that overcomes or at least partially solves the above problems.
According to an aspect of the present invention, there is provided a positioning method including:
collecting the position information of the user generated in the relevant time period of the merchant triggering to store behaviors;
and determining the position information of the commercial tenant according to the position information of the user.
Optionally, the relevant time period comprises: a preset time period before and/or after the store arrival behavior occurs.
Optionally, the store-to-store behavior comprises at least one of: pre-consumption behavior, post-consumption behavior, non-timed behavior; the relevant time period comprises at least one of: the pre-consumption period is a first time period after the occurrence of the behaviors, a second time period after the occurrence of the behaviors after the consumption, and a third time period before and after the occurrence of the non-timing behaviors.
Optionally, the determining the location information of the merchant according to the location information of the user includes:
clustering the collected position information of the user according to a preset clustering algorithm to obtain at least one cluster class;
taking the cluster class with the maximum number of the position information of the user as a clustering result;
and averaging the position information of the users in the clustering result, and taking the average value as the position information of the commercial tenant.
Optionally, the method further comprises:
when a current user triggers a store-to-store behavior for a merchant, determining the position information of the current user according to the determined position information of the merchant.
Optionally, the method further comprises:
and calculating the distance between the current user and the commercial tenant according to the position information of the current user and the determined position information of the commercial tenant.
According to another aspect of the present invention, there is provided a positioning apparatus comprising:
the system comprises a collecting module, a storage module and a processing module, wherein the collecting module is used for collecting the position information of a user generated in a relevant time period when the user triggers a merchant to store behavior;
and the first positioning module is used for determining the position information of the commercial tenant according to the position information of the user.
Optionally, the relevant time period comprises: a preset time period before and/or after the store arrival behavior occurs.
Optionally, the store-to-store behavior comprises at least one of: pre-consumption behavior, post-consumption behavior, non-timed behavior; the relevant time period comprises at least one of: the pre-consumption period is a first time period after the occurrence of the behaviors, a second time period after the occurrence of the behaviors after the consumption, and a third time period before and after the occurrence of the non-timing behaviors.
Optionally, the positioning module includes:
the clustering submodule is used for clustering the collected position information of the user according to a preset clustering algorithm to obtain at least one cluster;
the result determining submodule is used for taking the cluster class containing the maximum number of the position information of the user as a clustering result;
and the position calculation submodule is used for averaging the position information of the users in the clustering result and taking the average value as the position information of the commercial tenant.
Optionally, the apparatus further comprises:
and the second positioning module is used for determining the position information of the current user according to the determined position information of the merchant when the current user triggers the behavior of the merchant to the store.
Optionally, the apparatus further comprises:
and the distance calculation module is used for calculating the distance between the current user and the commercial tenant according to the position information of the current user and the determined position information of the commercial tenant.
According to yet another aspect of the present invention, there is provided a computing device comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor when executing the program implementing the steps of:
collecting position information generated in a relevant time period when a user triggers a merchant to store behavior;
and determining the position information of the commercial tenant according to the position information of the user.
According to yet another aspect of the present invention, there is provided a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
collecting position information generated in a relevant time period when a user triggers a merchant to store behavior;
and determining the position information of the commercial tenant according to the position information of the user.
According to the positioning method and the positioning device provided by the embodiment of the invention, the position information of the merchant can be determined according to the collected position information of the user generated in the relevant time period of triggering the merchant to store behaviors by the user, so that the accurate position of the merchant can be obtained, the problem that the manual marking of the merchant has a large error is solved, the distance between the user and the merchant can be accurately calculated, and the accuracy of o2o searching can be improved. In addition, the embodiment of the invention determines the position information of the merchant, does not need to allocate a large amount of manpower to sweep streets, and can save the manpower and time cost.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the alternative embodiments. The drawings are only for purposes of illustrating alternative embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 shows a flow chart of a first embodiment of a positioning method of the present invention;
fig. 2 shows a flow chart of a second embodiment of a positioning method of the present invention;
fig. 3 shows a flow chart of a third embodiment of a positioning method of the present invention;
FIG. 4 is a block diagram of a positioning device of the present invention;
FIG. 5 illustrates a block diagram of a computing device 1500 of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Referring to fig. 1, a flowchart of a first embodiment of a positioning method according to the present invention is shown, which may specifically include the following steps:
and step 102, determining the position information of the commercial tenant according to the position information of the user.
The embodiment of the invention can be suitable for application scenes of positioning through the mobile terminal. The mobile terminal may be any mobile terminal such as a mobile phone, a tablet computer, and a notebook computer, and the embodiment of the present invention does not limit the specific mobile terminal. For convenience of description, the embodiment of the present invention mainly takes a mobile phone as an example for description, and application scenarios of other mobile terminals may be referred to each other.
At present, the location information of the merchant is usually manually marked and actively uploaded by the merchant, and there are often large errors, which cause the distance between the user and the merchant obtained through calculation to be inaccurate, and further affect the accuracy of o2o search. In order to solve the problem, the embodiment of the invention can collect a large amount of user position information generated in a relevant time period when a user triggers a store behavior to a certain business, and determine the position information of the business according to the collected user position information to obtain the accurate position of the business, so that when the current user searches for o2o, the distance between the current user and the business can be accurately calculated, and the accuracy of o2o searching can be improved.
In practical applications, some user behaviors can be executed only when the user needs to arrive at a corresponding merchant, such as conducting purchase orders, group purchase ticket checking, self-service ordering, number taking queuing, booking to a store, user check-in, connecting with a wireless network of the merchant and the like through a mobile terminal. Embodiments of the present invention refer to these user behaviors as store-to behaviors, and as long as the user triggers any one of the store-to behaviors, it can be determined that the user is currently located in the store that triggered the store-to behavior. Therefore, the location information of the merchant can be determined according to the current location information of the user.
In an optional embodiment of the present invention, the relevant time period may specifically include: a preset time period before and/or after the store arrival behavior occurs.
In order to make the determined location information of the merchant more accurate, the location information of the user collected by the embodiment of the present invention is generated in the relevant time period of the trigger-to-store behavior of the user for the merchant, where the relevant time period is used to represent a shorter time range from the trigger-to-store behavior, and the probability that the user is located in the merchant in the relevant time period is higher, so that it can be ensured that the user is also located in the merchant corresponding to the trigger-to-store behavior when the user performs positioning and generates the location information. Specifically, the relevant time period may specifically include: a preset time period before and/or after the store arrival behavior occurs. For example, a user triggers an in-store action for a purchase order within a merchant, and since the user is typically located within the merchant for a period of time prior to the purchase order, location information may be collected for the user within 10 minutes prior to triggering the purchase order action.
In practical applications, there is typically a greater probability that the user is located within the merchant before the purchase order and leaves the merchant after the purchase order; the probability that the user is located within the store after booking to the store is high, etc., it can be seen that different store arrival behaviors may correspond to different associated time periods. Therefore, the store-to-store behaviors are classified according to the consumption time of the user, so that the related time periods are further subdivided, and the more accurate related time periods corresponding to the store-to-store behaviors triggered by the user are obtained.
In an optional embodiment of the present invention, the store-to-store behavior may specifically include at least one of: pre-consumption behavior, post-consumption behavior, non-timed behavior; the relevant time period may specifically include at least one of: the pre-consumption period is a first time period after the occurrence of the behaviors, a second time period after the occurrence of the behaviors after the consumption, and a third time period before and after the occurrence of the non-timing behaviors.
According to the embodiment of the invention, the behavior of arriving at the store is classified according to the consumption time of the user, and the behavior can be specifically classified into pre-consumption behavior, post-consumption behavior and non-timing behavior. The pre-consumption behavior refers to a store-to behavior triggered before the user uses the mobile terminal to consume in the merchant, for example: the actions of queuing for getting a number, booking to a store and ordering by self-service belong to pre-consumption actions. The relevant time period before consumption as corresponding to may specifically be: consumption proceeds as the first period of time after occurrence. The post-consumption behavior refers to a behavior triggered by a user after consuming the post-consumption behavior by using a mobile terminal in a merchant, such as: the buying bill and the group buying ticket are the behaviors after consumption. The relevant time period corresponding to the post-consumption behavior may specifically be: a second time period after the post-consumer behavior occurs. Non-timed behavior refers to an arrival behavior that does not determine whether it occurs before or after consumption by the user, such as: the wireless network of the user signing in and connecting with the merchant belongs to non-timing behavior. The relevant time period corresponding to the non-timed behavior may specifically be: a third time period before and after the occurrence of the non-timed behavior.
It is to be understood that, in practical applications, the embodiment of the present invention does not limit specific values of the first time period, the second time period, and the third time period, for example, the specific values may be 5 minutes, 10 minutes, half an hour, and the like, and the first time period, the second time period, and the third time period may be the same or different.
After determining the store-to-store behavior and the corresponding relevant time period, the embodiment of the invention can collect the position information of the user generated in the relevant time period when the user triggers the store-to-store behavior to the merchant. Wherein the location information may include: the user uses the position information of the user generated by the positioning operation triggered and executed by the application in the mobile terminal, or the position information of the user actively uploaded by the mobile terminal in real time, and the like. It can be understood that, in the embodiment of the present invention, the obtaining manner of the location information of the user is not limited, and for example, the location information may be GPS location information of the mobile terminal obtained by the mobile terminal through GPS positioning, or may also be location information of the mobile terminal obtained by the mobile terminal performing triangulation according to connected or scanned wireless network information.
Because the o2o search has a characteristic of large magnitude, and the o2o search is usually initiated by the user actively, which can avoid forcing the user to upload the location information thereof, in the embodiment of the present invention, the location information of the user generated when the user performs the o2o search using the mobile terminal is taken as an example for description, and it can be understood that the specific manner for acquiring the location information of the user is not limited in the embodiment of the present invention.
The embodiment of the invention can collect the position information of the user generated in the relevant time period of the merchant triggering to store behavior by the user through the following steps: firstly, collecting all the store-to-store behaviors triggered by a certain merchant in a historical time period and time information of the store-to-store behaviors triggered by a user; then, determining a relevant time period of the store-arriving behavior according to the type of the store-arriving behavior and the time information; and finally, filtering the position information of all the users in the historical time period according to the related time period to obtain the position information of the users in the related time period. The location information of the user may specifically be latitude and longitude information.
In practical application, the position information of the user is a GPS coordinate obtained by performing GPS positioning through a mobile terminal, however, since a merchant is usually located in an indoor and high-rise standing urban environment, and a GPS signal is easily blocked, so that an error exists in the position information of the user, noise data may exist in the collected position information of the user, and in order to improve accuracy of determining the location of the merchant, the embodiment of the present invention may perform denoising processing on the collected position information of the user generated in a relevant time period in which the merchant triggers a store behavior to filter out the noise data therein.
In an optional embodiment of the present invention, the determining the location information of the merchant according to the location information of the user may specifically include:
s11, clustering the collected user position information according to a preset clustering algorithm to obtain at least one cluster;
in the embodiment of the invention, firstly, a large amount of user position information generated in a relevant time period when a certain merchant triggers a store behavior can be collected, and the collected user position information is subjected to denoising processing.
And then, clustering the position information of the user after denoising according to a preset clustering algorithm to obtain at least one clustering result.
In the embodiment of the present invention, the preset Clustering algorithm may be DBScan (Density-Based Clustering of Applications with Noise), and the DBScan algorithm is a typical Density Clustering algorithm. The DBScan algorithm can find clusters of arbitrary shapes and does not need to determine the number of clusters formed in advance, and moreover, the DBScan algorithm can recognize noise point data. Therefore, the embodiment of the invention clusters the collected user position information by adopting the DBSCAn algorithm, can automatically clean abnormal position information data, and can improve the positioning accuracy.
The DBScan algorithm has the following two parameters: scanning radius eps and minimum point number minPts, that is, in the embodiment of the present invention, a DBScan algorithm is used to cluster the collected location information of the users, so as to obtain at least one cluster, where each cluster at least includes location information of minPts users, and a distance between the location information of the users in any two clusters is greater than eps. In the embodiment of the present invention, the distance between the location information of the user may specifically refer to an actual geographic straight-line distance between two longitude and latitude landmarks.
In an application example of the present invention, the scanning radius eps may be set to be 30 meters, and the minimum contained point number minPts may be 3, so that each cluster obtained after clustering at least contains location information of 3 users, and a distance between the location information of users in any two clusters is greater than 30 meters.
It is understood that, in practical applications, the specific values of the scan radius eps and the minimum contained number minPts are not limited by the embodiments of the present invention. In addition, the embodiment of the present invention does not limit the type of the preset clustering algorithm, and for example, clustering algorithms based on a partition method, a hierarchy method, a density method, a graph theory clustering method, a grid algorithm, a model algorithm, and the like may also be used.
Step S12, using the cluster class with the maximum number of the position information of the user as the clustering result;
the embodiment of the invention selects the cluster with the largest number of the position information of the users as the clustering result, and the position information of the users in other clusters can be filtered out as noise data.
And step S13, averaging the position information of the users in the clustering result, and taking the average as the position information of the commercial tenant.
After determining the clustering result, the position information of the user in the clustering result may be averaged, for example, the clustering result includes the following n position information: p is a radical of1(x1，y1)、p2(x2，y2)，…，pn(xn，yn). Wherein p isn(xn，yn) Indicates the nth position informationThe longitude and latitude coordinates of (c). The n position information may be averaged to obtain the position information of the merchant ((x)1+x2+…+xn)/n，(y1+y2+…+yn)/n)。
In the embodiment of the invention, if the position information of the merchant is unknown in advance, the position information of the merchant can be determined by the positioning method of the embodiment of the invention; if the location information of the merchant is known in advance, after the location information of the merchant is determined by the location method of the embodiment of the present invention, the accurate location of the merchant determined by the embodiment of the present invention may be compared with the original location of the merchant, and if the distance between the two is greater than a preset threshold, the original location of the merchant is replaced by the accurate location of the present invention, so as to correct the location of the merchant. If the distance between the two is greater than the preset threshold, it can be considered that the original position of the merchant has a large error, and the original position can be corrected. It can be understood that, in the embodiment of the present invention, a specific value of the preset threshold is not limited, and for example, the preset threshold may be set to 30 meters.
In an application example of the present invention, location information of a large number of users generated in a relevant time period in which a store behavior is triggered for a certain merchant in a historical time period (e.g., within a half year) may be collected, so that the collected location information of the large number of users may be clustered, and an average value of the location information of the users in the clustering result is used as the location information of the merchant.
The location information of each merchant can be determined and stored through the location method of the embodiment of the invention, for example, a merchant information base can be established for storing the mapping relationship between the merchant identifier and the merchant location, and in the subsequent process of using the merchant information base, the location information of the user generated in the relevant time period when the user triggers the merchant to store behavior is regularly collected, and the location information of the merchant is re-determined according to the newly collected location information of the user, so that the location information in the merchant information base is continuously updated in an iterative manner, and the accuracy of the location information of the merchant is continuously optimized and improved.
Therefore, according to the embodiment of the invention, the position information of the merchant is determined according to the collected position information of the user generated in the relevant time period when the user triggers the merchant to the store behavior, so that the accurate position of the merchant can be obtained, the problem that the merchant has a large error in manual marking is solved, the distance between the user and the merchant can be accurately calculated, and the accuracy of o2o searching can be improved. In addition, the embodiment of the invention determines the position information of the merchant, does not need to allocate a large amount of manpower to sweep streets, and can save the manpower and time cost.
Method embodiment two
By the embodiment of the invention, the accurate position of the merchant can be determined, and the manually marked original position of the merchant is corrected, so that the accurate position of the merchant can be used in the operation needing to use the merchant position information. In addition, when the current user is located in the business, the position of the user cannot be positioned due to poor GPS signals, or when a large error exists in a GPS positioning result due to poor GPS signals, the current user in the business can be positioned by utilizing the position information of the business determined by the embodiment of the invention, so that the accurate positioning of the user is realized.
Referring to fig. 2, a flowchart of a second embodiment of the positioning method of the present invention is shown, which may specifically include the following steps:
In an application example of the present invention, it is assumed that the current user is user a, and the current GPS signal of user a is poor, and the location of user a cannot be located, but at this time, user a triggers an arrival behavior of merchant a, and can determine that user a is currently located in merchant a, and then can determine the location information of user a by using the location information of merchant a determined by the positioning method of the present invention.
Therefore, by the embodiment of the invention, the position information of the merchant can be determined according to the collected position information of the user generated in the relevant time period when the user triggers the merchant to the store behavior, so as to obtain the accurate position of the merchant. Conversely, when the current user triggers a store-to-store behavior for the merchant, the location information of the current user can be determined by using the location information of the merchant determined by the positioning method of the invention, so that the problem that the location cannot be determined by using a GPS or the GPS has a large positioning error can be solved, and the accuracy of the location of the user can be improved.
Method embodiment three
By the embodiment of the invention, the accurate position of the merchant can be determined, and the manually marked original position of the merchant is corrected, so that the accurate position of the merchant can be used in the operation needing to use the merchant position information. For example, when the current user triggers an operation of o2o search or triggers an operation that requires calculation of a distance between the location of the current user and a location of a nearby business, the location information of the business determined by the positioning method of the present invention and the location information of the current user may be used to calculate the distance between the current user and the business, so as to improve the accuracy of calculating the distance between the user and the business.
Referring to fig. 3, a flowchart of a third embodiment of the positioning method of the present invention is shown, which may specifically include the following steps:
In an application example of the present invention, assuming that the current user is user B, when the user B triggers an o2o search operation, a merchant information base of the embodiment of the present invention may be queried, where the merchant information base stores location information of merchants determined by using the location method of the embodiment of the present invention, and calculates a distance between the user B and a merchant according to the location information of each merchant in the merchant information base and the current location information of the user B, and presents merchant information in which the distance between the user B and the merchant satisfies a user screening range to the user B. For example, if the filtering range set by the user B is 500 meters nearby, the information of the business less than 500 meters away from the current location of the user B may be presented to the user B.
In the process of calculating the distance between the current user and the merchant, the position information of the current user may be position information obtained by the mobile terminal of the current user through an existing arbitrary positioning mode, or, if the current user currently triggers a store-to-store behavior for the merchant, the position information of the current user may be determined by using the position information of the merchant determined by the positioning method of the present invention, so as to improve the accuracy of the position information of the user.
In summary, the embodiment of the present invention may calculate the distance between the current user and the merchant by using the location information of the merchant and the location information of the current user determined by the positioning method of the present invention, and display the merchant information whose distance satisfies the screening range of the current user to the current user.
The position information of the merchant is determined according to the collected position information of the user generated in the relevant time period when the user triggers the merchant to store behavior, so that the problem that the manual marking of the merchant has a large error can be solved, and the accuracy of the merchant position positioning can be improved; in addition, the location information of the user can be the location information of the merchant determined by the positioning method of the invention, so that the problem that the GPS cannot be used for positioning or the GPS has larger positioning error can be solved, and the accuracy of the user location positioning can be improved. To improve the accuracy of the o2o search.
Therefore, the embodiment of the invention can greatly improve the accuracy of calculating the distance between the user and the merchant, and further can greatly improve the accuracy of o2o search.
Device embodiment
Referring to fig. 4, a block diagram of a positioning apparatus of the present invention is shown, which may specifically include the following modules:
the collecting module 401 is configured to collect the location information of the user generated in the relevant time period when the user triggers the merchant to store behavior;
a first positioning module 402, configured to determine the location information of the merchant according to the location information of the user.
Optionally, the relevant time period may specifically include: a preset time period before and/or after the store arrival behavior occurs.
Optionally, the behavior to the store may specifically include at least one of: pre-consumption behavior, post-consumption behavior, non-timed behavior; the relevant time period may specifically include at least one of: the pre-consumption period is a first time period after the occurrence of the behaviors, a second time period after the occurrence of the behaviors after the consumption, and a third time period before and after the occurrence of the non-timing behaviors.
Optionally, the positioning module 402 may specifically include:
the clustering submodule is used for clustering the collected position information of the user according to a preset clustering algorithm to obtain at least one cluster;
the result determining submodule is used for taking the cluster class containing the maximum number of the position information of the user as a clustering result;
and the position calculation submodule is used for averaging the position information of the users in the clustering result and taking the average value as the position information of the commercial tenant.
Optionally, the apparatus may further include:
and the second positioning module is used for determining the position information of the current user according to the determined position information of the merchant when the current user triggers the behavior of the merchant to the store.
Optionally, the apparatus may further include:
and the distance calculation module is used for calculating the distance between the current user and the commercial tenant according to the position information of the current user and the determined position information of the commercial tenant.
Referring to fig. 5, a schematic structural diagram of a computing device 1500 of the present invention is shown, which may specifically include: at least one processor 1501, memory 1502, at least one network interface 1504, and a user interface 1503. The various components in computing device 1500 are coupled together by a bus system 1505. It is understood that bus system 1505 is used to enable communications among the components by way of connections. Bus system 1505 includes a power bus, a control bus, and a status signal bus, in addition to a data bus. For clarity of illustration, however, the various buses are labeled as bus system 1505 in figure 5.
The user interface 1503 may include, among other things, a display, a keyboard, or a pointing device (e.g., a mouse, trackball, touch pad, or touch screen, etc.).
It is to be understood that the memory 1502 in embodiments of the present invention can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The non-volatile memory may be a Read-only memory (ROM), a programmable Read-only memory (PROM), an erasable programmable Read-only memory (erasabprom, EPROM), an electrically erasable programmable Read-only memory (EEPROM), or a flash memory. The volatile memory may be a Random Access Memory (RAM) which functions as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (staticiram, SRAM), dynamic random access memory (dynamic RAM, DRAM), synchronous dynamic random access memory (syncronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM ), Enhanced Synchronous DRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and direct memory bus RAM (DRRAM). The memory 1502 of the systems and methods described in connection with the embodiments of the invention is intended to comprise, without being limited to, these and any other suitable types of memory.
In some embodiments, memory 1502 stores the following elements, executable modules or data structures, or a subset thereof, or an expanded set thereof: an operating system 15021 and application programs 15022.
The operating system 15021 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, for implementing various basic services and processing hardware-based tasks. The application 15022 contains various applications such as a media player (MediaPlayer), a Browser (Browser), and the like, for implementing various application services. A program implementing a method according to an embodiment of the present invention may be included in application program 15022.
In the embodiment of the present invention, the processor 1501 is configured to collect the location information of the user generated in the relevant time period of the user triggering the merchant to store behavior by calling the program or instruction stored in the memory 1502, specifically, the program or instruction stored in the application program 15022; and determining the position information of the commercial tenant according to the position information of the user.
The method disclosed in the above embodiments of the present invention may be applied to the processor 1501 or implemented by the processor 1501. Processor 1501 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 1501. The processor 1501 may be a general-purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 1502, and the processor 1501 reads the information in the memory 1502 and, in conjunction with its hardware, performs the steps of the above-described method.
It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described herein, or a combination thereof.
For a software implementation, the techniques described in this embodiment of the invention may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described in this embodiment of the invention. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
Optionally, the processor 1501 is further configured to: determining the location information of the merchant according to the location information of the user by the following steps:
clustering the collected position information of the user according to a preset clustering algorithm to obtain at least one cluster class;
taking the cluster class with the maximum number of the position information of the user as a clustering result;
and averaging the position information of the users in the clustering result, and taking the average value as the position information of the commercial tenant.
Optionally, the processor 1501 is further configured to: when a current user triggers a store-to-store behavior for a merchant, determining the position information of the current user according to the determined position information of the merchant.
Optionally, the processor 1501 is further configured to: and calculating the distance between the current user and the commercial tenant according to the position information of the current user and the determined position information of the commercial tenant.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. Moreover, the present invention is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components of the positioning method and apparatus according to embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet platform or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
Claims (8)
1. A method of positioning, the method comprising:
collecting the position information of the user generated in the relevant time period of the merchant triggering to store behaviors;
determining the position information of the commercial tenant according to the position information of the user;
the store-to-store behavior comprises at least one of: pre-consumption behavior, post-consumption behavior, non-timed behavior;
the relevant time period comprises at least one of: the pre-consumption period is a first time period after the occurrence of the behavior, a second time period after the occurrence of the behavior after the consumption, and a third time period before and after the occurrence of the non-timing behavior;
wherein the determining the location information of the merchant according to the location information of the user includes:
clustering the collected position information of the user according to a preset clustering algorithm to obtain at least one cluster class;
taking the cluster class with the maximum number of the position information of the user as a clustering result;
and averaging the position information of the users in the clustering result, and taking the average value as the position information of the commercial tenant.
2. The method of claim 1, further comprising:
when a current user triggers a store-to-store behavior for a merchant, determining the position information of the current user according to the determined position information of the merchant.
3. The method according to any one of claims 1 to 2, further comprising:
and calculating the distance between the current user and the commercial tenant according to the position information of the current user and the determined position information of the commercial tenant.
4. A positioning device, the device comprising:
the system comprises a collecting module, a storage module and a processing module, wherein the collecting module is used for collecting the position information of a user generated in a relevant time period when the user triggers a merchant to store behavior;
the first positioning module is used for determining the position information of the commercial tenant according to the position information of the user;
the store-to-store behavior comprises at least one of: pre-consumption behavior, post-consumption behavior, non-timed behavior;
the relevant time period comprises at least one of: the pre-consumption period is a first time period after the occurrence of the behavior, a second time period after the occurrence of the behavior after the consumption, and a third time period before and after the occurrence of the non-timing behavior;
wherein, the positioning module comprises:
the clustering submodule is used for clustering the collected position information of the user according to a preset clustering algorithm to obtain at least one cluster;
the result determining submodule is used for taking the cluster class containing the maximum number of the position information of the user as a clustering result;
and the position calculation submodule is used for averaging the position information of the users in the clustering result and taking the average value as the position information of the commercial tenant.
5. The apparatus of claim 4, further comprising:
and the second positioning module is used for determining the position information of the current user according to the determined position information of the merchant when the current user triggers the behavior of the merchant to the store.
6. The apparatus of any of claims 4 to 5, further comprising:
and the distance calculation module is used for calculating the distance between the current user and the commercial tenant according to the position information of the current user and the determined position information of the commercial tenant.
7. A computing device, comprising: memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of:
collecting position information generated in a relevant time period when a user triggers a merchant to store behavior;
determining the position information of the commercial tenant according to the position information of the user;
the store-to-store behavior comprises at least one of: pre-consumption behavior, post-consumption behavior, non-timed behavior;
the relevant time period comprises at least one of: the pre-consumption period is a first time period after the occurrence of the behavior, a second time period after the occurrence of the behavior after the consumption, and a third time period before and after the occurrence of the non-timing behavior;
wherein the determining the location information of the merchant according to the location information of the user includes:
clustering the collected position information of the user according to a preset clustering algorithm to obtain at least one cluster class;
taking the cluster class with the maximum number of the position information of the user as a clustering result;
and averaging the position information of the users in the clustering result, and taking the average value as the position information of the commercial tenant.
8. A computer-readable storage medium, on which a computer program is stored, which program, when executed by a processor, carries out the steps of:
collecting position information generated in a relevant time period when a user triggers a merchant to store behavior;
determining the position information of the commercial tenant according to the position information of the user;
the store-to-store behavior comprises at least one of: pre-consumption behavior, post-consumption behavior, non-timed behavior;
the relevant time period comprises at least one of: the pre-consumption period is a first time period after the occurrence of the behavior, a second time period after the occurrence of the behavior after the consumption, and a third time period before and after the occurrence of the non-timing behavior;
wherein the determining the location information of the merchant according to the location information of the user includes:
clustering the collected position information of the user according to a preset clustering algorithm to obtain at least one cluster class;
taking the cluster class with the maximum number of the position information of the user as a clustering result;
and averaging the position information of the users in the clustering result, and taking the average value as the position information of the commercial tenant.
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| CN113837755A (en) * | 2018-07-05 | 2021-12-24 | 创新先进技术有限公司 | Offline transaction distinguishing method and device and computer equipment |
| CN110969483B (en) * | 2019-11-29 | 2023-10-10 | 支付宝实验室(新加坡)有限公司 | Method and device for identifying merchant position and electronic equipment |
| CN111784467B (en) * | 2020-07-01 | 2022-06-24 | 支付宝(杭州)信息技术有限公司 | Method and system for processing geographical position |
| CN112529744A (en) * | 2020-11-10 | 2021-03-19 | 成都佳发教育科技有限公司 | Method for positioning classroom to realize accurate attendance by utilizing position information of student mobile equipment |
| CN115226205B (en) * | 2022-07-13 | 2024-08-16 | 拉扎斯网络科技（上海）有限公司 | Data processing method, device, computer equipment and storage medium |
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