CN112365315A - Commodity display position recommendation method, device and system and storage medium - Google Patents
Commodity display position recommendation method, device and system and storage medium Download PDFInfo
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Abstract
The application provides a commodity display position recommendation method, device and system and a storage medium. The method comprises the following steps: the server can calculate and obtain commodity attention data. And the server determines the ranking information of the attention value of each commodity according to the commodity attention data. The server stores each display position information. And the server recommends the corresponding commodities to each display position according to the ranking information of the attention value and the importance degree of the display position. The method increases the rationality and objectivity of the commodity display planning.
Description
Technical Field
The present application relates to computer technologies, and in particular, to a method, an apparatus, a system, and a storage medium for recommending a merchandise display position.
Background
In an experience store, merchandise is typically placed on a display stand for display. After the customer enters the experience shop, the commodity displayed on the exhibition stand can be experienced. The customer's attention is limited and, therefore, the goods located in the primary display location, typically the goods that the customer experiences, are more.
Currently, merchants typically determine some of the display locations to be primary display areas based on the layout of the experience store. Also, the merchant typically determines the displayed merchandise of the primary display location based on the sales policy for the merchandise. Further, when entering the experience store, the customer is given a priority to pay attention to the product that the merchant wants to push mainly in the main display space.
However, the layout mode of the commodity display mainly depends on the subjective inference of the merchant, and the subjectivity and the uncertainty exist.
Disclosure of Invention
The application provides a commodity display position recommendation method, device, system and storage medium, which are used for solving the problem that the layout mode of commodity display mainly depends on subjective inference of merchants.
In a first aspect, the present application provides a method for recommending a merchandise display position, including:
the method comprises the steps of obtaining commodity attention data, wherein the commodity attention data comprise an attention value of at least one commodity, and the attention value is used for indicating the attention degree of the corresponding commodity in a preset time period;
determining the ranking information of the attention value of each commodity according to the commodity attention data;
and determining display position recommendation information according to the attention value ranking information and the display position information, wherein the display position information comprises characteristic information of each display position, and the display recommendation information comprises commodity information recommended to be displayed on each display position.
Optionally, the acquiring of the commodity attention data includes:
acquiring a first attention index of a commodity, wherein the first attention index is determined according to the total duration that the distance between a target object and the commodity is less than a preset value in the preset time period;
acquiring a second attention index of the commodity, wherein the second attention index is determined according to the duration of the commodity held by the target object in the preset time period;
and determining the attention value of the commodity according to the first attention index and the second attention index.
Optionally, the obtaining a first indicator of interest of the commodity includes:
acquiring a moving track of the target object within the preset time period, wherein the moving track is obtained by positioning according to video information acquired by a visual sensor;
determining a time length when the distance between the commodity and the target object is smaller than the preset value according to the moving track and the preset position of the commodity;
and counting the total time length of the distance between all the target objects and the commodity, which is less than a preset value, in the preset time period, and determining the first attention index according to the total time length.
Optionally, the obtaining the moving track of the target object within the preset time period includes:
acquiring a video information set, wherein the video information set comprises video information of the target object within the preset time period, which is obtained by shooting by each visual sensor;
respectively extracting the outlines of the target objects in the video information, and determining the coordinate sequences of the target objects in the video information according to the outlines;
and selecting the coordinate sequences of the target object in the two videos, and determining the moving track of the target object according to the coordinate sequences of the target object in the two videos.
Optionally, the acquiring a second indicator of interest of the commodity includes:
acquiring positioning information of the commodity in the preset time period, wherein the positioning information is obtained by positioning a Bluetooth beacon device according to a Bluetooth fixed label pasted on the commodity;
comparing the positioning information with a preset position of the commodity to determine whether the commodity is held;
and counting the total duration of the commodity held by the target object, and determining the second attention index of the commodity according to the total duration.
Optionally, the obtaining of the positioning information of the commodity within the preset time period includes:
acquiring a Bluetooth information set, wherein the Bluetooth information set comprises Bluetooth information obtained by positioning each Bluetooth beacon device according to a Bluetooth fixed label pasted on the commodity;
selecting a first group of Bluetooth information, and determining a first coordinate of the commodity according to the first group of Bluetooth information, wherein the first group of Bluetooth information is any three pieces of Bluetooth information in the Bluetooth information set;
selecting a second group of Bluetooth information, and determining a second coordinate of the commodity according to the second group of Bluetooth information, wherein at least one piece of Bluetooth information in the second group of Bluetooth information is different from the Bluetooth information in the first group of Bluetooth information;
and determining the commodity positioning information according to the first coordinate and the second coordinate.
Optionally, the bluetooth information includes a received signal strength indication RSSI signal.
In a second aspect, the present application provides a merchandise display position recommendation device, including:
the attention unit 11 is configured to acquire commodity attention data, where the commodity attention data includes an attention value of at least one commodity, and the attention value is used to indicate an attention degree of a corresponding commodity within a preset time period;
the sorting unit 12 is configured to determine attention value sorting information of each commodity according to the commodity attention data;
and the recommending unit 13 is configured to determine display position recommending information according to the attention value ranking information and the display position information, where the display position information includes feature information of each display position, and the display recommending information includes information of commodities recommended to be displayed at each display position.
Optionally, the acquiring of the commodity attention data includes:
the first obtaining module 111 is configured to obtain a first interest indicator of a commodity, where the first interest indicator is determined according to a total duration that a distance between a target object and the commodity is smaller than a preset value within the preset time period;
a second obtaining module 112, configured to obtain a second interest indicator of the commodity, where the second interest indicator is determined according to a duration that the commodity is held by the target object within the preset time period;
a determining module 113, configured to determine a value of interest of the product according to the first indicator of interest and the second indicator of interest.
Optionally, the obtaining a first indicator of interest of the commodity includes:
the track obtaining sub-module 1111 is configured to obtain a moving track of the target object within the preset time period, where the moving track is obtained by positioning according to video information obtained by a visual sensor;
a first time length statistic submodule 1112, configured to determine, according to the moving trajectory and a preset position of the commodity, a time length for which a distance between the commodity and the target object is smaller than the preset value;
the first index calculation submodule 1113 is configured to count a total duration of distances between all the target objects and the commodity within the preset time period and being smaller than a preset value, and determine the first attention index according to the total duration.
Optionally, the trajectory acquisition sub-module 1111 is specifically configured to acquire a video information set, where the video information set includes video information of the target object within the preset time period, which is obtained by shooting with each visual sensor; respectively extracting the outlines of the target objects in the video information, and determining the coordinate sequences of the target objects in the video information according to the outlines; and selecting the coordinate sequences of the target object in the two videos, and determining the moving track of the target object according to the coordinate sequences of the target object in the two videos.
Optionally, the acquiring a second indicator of interest of the commodity includes:
a positioning obtaining submodule 1121, configured to obtain positioning information of the commodity in the preset time period, where the positioning information is obtained by positioning a bluetooth beacon device according to a bluetooth fixed tag attached to the commodity;
the second duration statistic submodule 1122 is configured to compare the positioning information with a preset position of the commodity, and determine whether the commodity is held;
the second indicator calculation submodule 1123 is configured to count a total duration of holding of the commodity by the target object, and determine the second attention indicator of the commodity according to the total duration.
Optionally, the positioning obtaining sub-module 1121 is specifically configured to obtain a bluetooth information set, where the bluetooth information set includes bluetooth information obtained by positioning each bluetooth beacon device according to a bluetooth fixed tag attached to the commodity; selecting a first group of Bluetooth information, and determining a first coordinate of the commodity according to the first group of Bluetooth information, wherein the first group of Bluetooth information is any three pieces of Bluetooth information in the Bluetooth information set; selecting a second group of Bluetooth information, and determining a second coordinate of the commodity according to the second group of Bluetooth information, wherein at least one piece of Bluetooth information in the second group of Bluetooth information is different from the Bluetooth information in the first group of Bluetooth information; and determining the commodity positioning information according to the first coordinate and the second coordinate.
Optionally, the bluetooth information includes a received signal strength indication RSSI signal.
In a third aspect, the present application provides a server, comprising: the system comprises a server, a visual sensor, a Bluetooth beacon device and a Bluetooth positioning tag;
the Bluetooth positioning label is pasted on the surface of the commodity, and the client feeds back the position information of the commodity to the Bluetooth beacon device;
the Bluetooth beacon device is arranged at a first preset position on a roof in a store and used for acquiring the position information of the commodity sent by the Bluetooth positioning tag;
the visual sensor is arranged at a second preset position of the roof in the store and used for acquiring the position information of the target object;
the server is used for realizing the commodity display position recommendation method in any one of the possible designs of the first aspect and the first aspect.
In a fourth aspect, the present application provides a readable storage medium, where an execution instruction is stored in the readable storage medium, and when the execution instruction is executed by at least one processor of the server, the server executes the method for recommending a merchandise display position in any one of the possible designs of the first aspect and the first aspect.
According to the commodity display position recommendation method, device and system and the storage medium, commodity attention data are obtained through calculation; determining the ranking information of the attention value of each commodity according to the commodity attention data; and according to the arrangement information of the attention value and the importance degree of the display position, recommending the corresponding commodity to each display position by means of the arrangement information and the importance degree of the display position, and realizing reasonable planning of commodity display, wherein the planning is realized by means of big data, and the method has higher objectivity and accuracy.
Drawings
In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a schematic view of a scene of an experience shop according to an embodiment of the present application;
fig. 2 is a flowchart of a method for recommending a merchandise display position according to an embodiment of the present application;
fig. 3 is a flowchart of another method for recommending a merchandise display position according to an embodiment of the present application;
fig. 4 is a flowchart of a method for recommending a merchandise display position according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a merchandise display position recommendation device according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of another merchandise display position recommendation device according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of a further merchandise display position recommendation device according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of a merchandise display position recommendation system according to an embodiment of the present application.
Reference numerals:
1. 2: a vision sensor;
3. 4, 5, 6: a bluetooth beacon device.
Detailed Description
To make the purpose, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be clearly and completely described below with reference to the drawings in the present application, and it is obvious that the described embodiments are some, but not all embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The technical solution of the present application will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
In an experience store, merchandise is typically placed on a display stand for display. After the customer enters the experience shop, the commodity displayed on the exhibition stand can be experienced. The customer's attention is limited and, therefore, the goods located in the primary display location, typically the goods that the customer experiences, are more. Currently, merchants typically determine some of the display locations to be primary display areas based on the layout of the experience store. Also, the merchant typically determines the displayed merchandise of the primary display location based on the sales policy for the merchandise. Further, when entering the experience store, the customer is given a priority to pay attention to the product that the merchant wants to push mainly in the main display space. However, the layout mode of the commodity display mainly depends on the subjective inference of the merchant, and the problems of subjectivity and uncertainty exist. Once the merchant is inexperienced or inaccurate in judgment, resources in the main display area may be wasted, thereby causing sales problems.
In view of the above situation, the present application provides a method, an apparatus, a system and a storage medium for recommending a merchandise display position. According to the method and the system, the commodities which are mainly interested by the consumer are determined by knowing the demand of the consumer and analyzing the interest points of the consumer. Furthermore, according to the layout of the experience store, each commodity is arranged to a proper position, and therefore marketing efficiency is improved. Wherein, in the experience store, the consumer demand and the consumer interest point can be embodied as commodity attention data in the experience store. The commodity attention data in the experience store can be obtained by calculating the short-distance standing time between the user and the commodity and the interaction time between the user and the commodity.
FIG. 1 shows a scene diagram of an experience shop according to an embodiment of the present application. As shown, the experience shop has 2 visual sensors and 4 bluetooth beacon devices installed. Wherein, 2 vision sensors are evenly arranged on the roof (1, 2 in figure 1) inside the experience shop. The vision sensor is used to photograph experience in-store conditions vertically downward. Wherein, 4 bluetooth beacon devices are installed at four angles (3, 4, 5, 6 in fig. 1) on the roof inside the experience shop for acquire the bluetooth signal that the bluetooth positioning label pasted on the surface of the commodity sent.
And after the visual sensor and the Bluetooth beacon device acquire the video information and the Bluetooth information, the video information or the Bluetooth information is sent to a server. And the server realizes the calculation of the commodity attention data according to the video information and the Bluetooth information. And then, according to the commodity attention data, the server determines display position recommendation information to realize recommendation of the commodity display position. Therefore, the present application uses the server as an execution subject to execute the commodity display position recommendation method according to the following embodiment. Specifically, the execution subject may be a hardware device of the server, or a software application implementing the following embodiments in the server, or a computer-readable storage medium installed with a software application implementing the following embodiments.
Fig. 2 shows a flowchart of a method for recommending a merchandise display position according to an embodiment of the present application. On the basis of the embodiment shown in fig. 1, as shown in fig. 2, with a server as an execution subject, the method of this embodiment may include the following steps:
s101, commodity attention data are obtained, wherein the commodity attention data comprise attention values of at least one commodity, and the attention values are used for indicating the attention degrees of the corresponding commodities in a preset time period.
In this embodiment, the server may calculate to obtain the commodity attention data. The commodity attention data is a data set, and the data set comprises attention values of at least one commodity. The server determines the attention value of the target object to the commodity by counting the time of the target object observing the commodity within the preset time interval. Wherein the target object may be a customer group entering the experience shop. The attention value may be determined according to a sum of a time when the user observes the product and a time when the user tries the product.
And S102, determining the attention value ranking information of each commodity according to the commodity attention data.
In this embodiment, after the server determines the attention value of each product in the experience shop according to S101, the server may sort the products according to the attention value. And the server determines the ranking result of the attention value as attention value ranking information. The sorting mode is descending sorting, namely, the commodities with high attention values are in front, and the commodities with low attention values are behind.
S103, determining display recommendation information according to the ranking information and the display position information of the attention value, wherein the display position information comprises characteristic information of each display position, and the display recommendation information comprises commodity information recommended to be displayed at each display position.
In this embodiment, each piece of display position information is stored in the server. The display position information includes a display position and an importance degree of the display position. Wherein the importance of the presentation position can be determined in dependence of the presentation position. Generally, the closer to the experience store center, the more important it is.
And the server recommends the corresponding commodities to each display position according to the ranking information of the attention value and the importance degree of the display position. For example, the server recommends that the item with the highest attention value be placed at the position with the highest degree of importance.
According to the commodity display position recommendation method, the server can calculate and obtain commodity attention data. And the server determines the ranking information of the attention value of each commodity according to the commodity attention data. The server stores each display position information. And the server recommends the corresponding commodities to each display position according to the ranking information of the attention value and the importance degree of the display position. In this application, through the attention value that acquires commodity, confirm the degree of concern of commodity, and then, according to this attention value, will receive the commodity that the degree of concern is high and put in the higher show position of important degree, realize the rational planning to commodity show, this planning relies on big data to realize, has higher objectivity and accurate definite.
Fig. 3 is a flowchart illustrating another merchandise display position recommendation method according to an embodiment of the present application. On the basis of the embodiments shown in fig. 1 and fig. 2, as shown in fig. 3, with a server as an execution subject, the method of the embodiment may include the following steps:
s201, obtaining a first attention index of the commodity, wherein the first attention index is determined according to the total duration that the distance between the target object and the commodity is smaller than a preset value in a preset time period.
In this embodiment, the server counts the total time for observing a certain commodity by the target object within a preset time period. And the server determines a first attention index of the commodity according to the total duration. And the preset time period is used for helping the server to complete the statistics of the total duration. The preset time is generally the time for adjusting the position of one-time commodity display in the experience shop. When a large amount of passenger flows exist in the experience store, it is obviously difficult to acquire the gazing information of each user, and therefore the server determines that the target object observes the commodity when the distance between the target object and the commodity is smaller than a preset value. Wherein the preset value is determined according to the time condition of the experience shop. The value of the preset value should be such that when the target object is at a certain position, the distance between the target object and the plurality of commodities is less than the preset value.
The first attention index can be obtained by calculation according to the total duration and a preset calculation formula. For example, the calculation formula may be:
first target indicator is total duration/10
S202, obtaining a second attention index of the commodity, wherein the second attention index is determined according to the time length of the commodity held by the target object in the preset time period.
In this embodiment, the server counts the total time length of a certain commodity held by the target object. And the server determines a second attention index of the commodity according to the total duration. And the preset time period is used for helping the server to complete the statistics of the total duration. The preset time is generally the time for adjusting the position of one-time commodity display in the experience shop. The server can determine whether the commodity is held by the target object by judging whether the commodity is at the preset position. When the commodity is no longer in the preset position, the commodity is held by the target object, and at this time, the target object may try the commodity or the target object may carefully observe the commodity.
The second attention index can be obtained by calculation according to the total duration and a preset calculation formula. For example, the calculation formula may be:
second target indicator is total duration/10
And S203, determining the attention value of the commodity according to the first attention index and the second attention index.
In this embodiment, the server determines the first attention index and the second attention index according to S201 and S202. The first attention index is the total duration that the distance between the target object and the commodity is smaller than a preset value. And the second attention index is the total duration of holding the commodity by the target object.
In one example, the value of interest for the item may be a sum of the first indicator of interest and the second indicator of interest.
For example, the total time length corresponding to the first attention index is 500s, and the total time length corresponding to the second attention index is 100 s. At this time, the server may calculate that the first interest index is 50 points and the second interest index is 10 points. Further, the server calculates that the value of interest of the product is 60 points.
In another example, the value of interest for the item may be a weighted sum of the first indicator of interest and the second indicator of interest. The value of this weighting may be determined empirically. The server calculates the attention value through weighting, the occupation ratio of the attention index during holding is improved, and therefore the effectiveness of the second attention index during holding is guaranteed.
For example, the first indicator of interest and the second indicator of interest have a specific gravity of 1: 5. The total duration corresponding to the first attention index is 500s, and the total duration corresponding to the second attention index is 100 s. At this time, the server may calculate that the first interest index is 50 points and the second interest index is 10 points. Further, the server calculates that the value of interest of the product is 100 points.
And S204, determining the attention value ranking information of each commodity according to the commodity attention data.
S205, display recommendation information is determined according to the ranking information and the display position information of the attention value, the display position information comprises characteristic information of each display position, and the display recommendation information comprises commodity information recommended to be displayed at each display position.
Steps S204 and S205 are similar to steps S102 and S103 in the embodiment of fig. 2, and are not described again in this embodiment.
According to the commodity display position recommendation method, the server determines the first attention index by counting the total time length that the distance between the target object and the commodity is smaller than the preset value in the preset time period. And the server determines a second attention index by counting the time length of the commodity held by the target object in a preset time period. And the server determines the attention value of the commodity according to the first attention index and the second attention index. Further, the server determines product interest degree data in the experience shop based on the interest degree values of the respective products. And the server determines the ranking information of the attention value of each commodity according to the commodity attention data. The server stores each display position information. And the server recommends the corresponding commodities to each display position according to the ranking information of the attention value and the importance degree of the display position. According to the method and the device, the attention value of the commodity is determined by calculating the first attention index and the second attention index of the commodity, the total duration of the commodity observed and tried by a user in the display process is accurately reflected by the attention value, and the attention degree of the commodity is objectively reflected. Meanwhile, reasonable planning of commodity display is achieved by using the objective commodity attention degree, the planning is achieved by means of big data, and the objective commodity attention degree planning method has higher objectivity and accuracy.
Fig. 4 is a flowchart illustrating a further method for recommending a merchandise display position according to an embodiment of the present application. On the basis of the embodiments shown in fig. 1 to fig. 3, as shown in fig. 4, with a server as an execution subject, the method of the embodiment may include the following steps:
s301, a video information set is obtained, wherein the video information set comprises video information of a target object in a preset time period obtained by shooting of each visual sensor.
In this embodiment, the server acquires video information from the visual sensor. The video information comprises the activity situation of the target object in the experience shop. The experience shop is provided with a plurality of visual sensors, and the visual sensors shoot video information in the experience shop from different angles. The server determines a plurality of received video information shot by the plurality of vision sensors as a video information set. For example, as shown in fig. 1, two vision sensors installed on the roof inside an experience shop capture videos from two different angles and send the videos to a server.
Wherein, the vision sensor can upload the video to the server in real time. Alternatively, the vision sensor may upload videos in a preset time interval to the server. The time interval may be 1 hour, 12 hours, 24 hours, etc.
S302, respectively extracting the outlines of the target objects in the video information, and determining the coordinate sequences of the target objects in the video information according to the outlines.
In this embodiment, the server extracts the contour of the target object in each video. And the server determines the coordinates of the target object in the video picture according to the outline. Because the camera is a fixed camera, the coordinates of the target object in the video picture change as the target object moves around in the experience store. The positions where different vision sensors are installed are different, so that the positions where the target objects appear in different video information are different.
The method for extracting the contour of the target object in each video by the server may be an existing contour extraction method, for example, an inter-frame difference method, an image segmentation method, or the like. Alternatively, the method for extracting the contour of the target object in each video by the server can also be an improved algorithm.
And after the server acquires the contour of each target object in the video information, calculating the centroid of the contour according to the contour. The server determines the centroid as coordinates of the target object.
The server can obtain the video frames in the video information according to the fixed time interval. Further, coordinates of the target object in the frame are acquired, and a coordinate sequence is determined. Wherein the fixed time interval may be one frame acquired every 50ms, or one frame acquired every 1 s.
S303, selecting the coordinate sequences of the target object in the two videos, and determining the moving track of the target object according to the coordinate sequences of the target object in the two videos.
In this embodiment, the video information set acquired by the server includes a plurality of pieces of video information. The server selects two video information and a coordinate sequence of its target object from the plurality of video information. And the server determines the moving track of the target object according to the positions of the two visual sensors of the video information and the coordinate sequence of the target object.
Wherein, a plurality of target objects, namely clients, can be included in one video information. After the server acquires the two pieces of video information, the server acquires the coordinate sequences of the same target object in the two pieces of video information. And then, calculating to obtain the moving track of the target object according to the two coordinate sequences.
The server can judge whether the target objects of different video information are the same target object through a face matching algorithm, a body shape matching algorithm, an action matching algorithm and the like.
After the server determines the coordinate r1 of the target object by using the video information, the server maps the coordinate to a coordinate system corresponding to the Bluetooth positioning, and the coordinate r2 is obtained. The mapping formula from the coordinate r1 to the coordinate r2 is as follows:
r2=NN(r1)|r1
s304, according to the moving track and the preset position of the commodity, determining the time length when the distance between the commodity and the customer is smaller than the preset value.
In this embodiment, the server obtains the preset position of the commodity from the memory. The preset position of the commodity comprises information such as a commodity coordinate, a commodity name and a commodity identification. And after the server acquires the moving track of the target object, judging the time length when the distance between the target object and the commodity is less than a preset value according to the preset position of the commodity. Wherein the preset value is determined according to actual requirements. The selection of the setting is required to ensure that when the distance between the target object and the commodity is smaller than a preset value, the distances between the target object and other commodities are all larger than the preset value. For example, the preset value may be 0.5 meters.
S305, counting the total time length within the preset time period, wherein the distance between all the target objects and the commodity is smaller than the preset value, and determining a first attention index according to the total time length.
In this embodiment, in a preset time period, the target objects whose distance from the commodity is less than the preset value may be a plurality of target objects. And the server counts the total duration that the distances between all the target objects and the commodity are less than a preset value. The first attention index can be obtained by calculation according to the total duration and a preset calculation formula. For example, the calculation formula may be:
first target indicator is total duration/10
S306, a Bluetooth information set is obtained, wherein the Bluetooth information set comprises Bluetooth information obtained by positioning each Bluetooth beacon device according to the Bluetooth fixed label pasted on the commodity.
In this embodiment, the server obtains the bluetooth information fed back by the bluetooth fixed tag through the bluetooth beacon device. Wherein, the bluetooth beacon device can be installed in four corners of the experience shop as shown in fig. 1 at 3, 4, 5 and 6. Wherein, the fixed label of bluetooth is pasted and is gone up with the commodity. When the target object holds the commodity to move, the Bluetooth signal fed back by the Bluetooth fixed tag changes along with the change of the position.
In one example, the bluetooth information includes a received signal strength indication RSSI signal.
After receiving the RSSI signal, the server may determine the distance between the article and the bluetooth beacon device according to the RSSI signal strength.
S307, selecting a first group of Bluetooth information, and determining a first coordinate of the commodity according to the first group of Bluetooth information, wherein the first group of Bluetooth information is any three pieces of Bluetooth information in a Bluetooth information set.
In this embodiment, the server randomly selects three pieces of bluetooth information from the plurality of pieces of bluetooth information, and determines that the three pieces of bluetooth information are the first group of bluetooth information. The server can determine the first coordinate of the commodity according to the distances between the commodity and the three Bluetooth beacon devices in a three-point positioning mode.
S308, selecting a second group of Bluetooth information, and determining a second coordinate of the commodity according to the second group of Bluetooth information, wherein at least one piece of Bluetooth information in the second group of Bluetooth information is different from the Bluetooth information in the first group of Bluetooth information.
In this embodiment, the server randomly selects three pieces of bluetooth information from the plurality of pieces of bluetooth information, and determines that the three pieces of bluetooth information are the second group of bluetooth information. At least one of the second group of Bluetooth information and the first group of Bluetooth information is different Bluetooth information. And the server determines a second coordinate of the commodity according to the distances between the commodity and the three Bluetooth beacon devices in a three-point positioning mode.
And S309, determining the commodity positioning information according to the first coordinate and the second coordinate.
In this embodiment, the servers S308 and S309 calculate a connection line between the first coordinate and the second coordinate, and determine a midpoint of the connection line as a final coordinate of the commodity. The final coordinates of the commodity are included in the commodity positioning information. And the server determines the moving track of the commodity according to the continuous RSSI signals acquired by the Bluetooth beacon device.
S310, comparing the positioning information with the preset position of the commodity, and determining whether the commodity is held.
In one example, the server obtains the commodity positioning information calculated in S309. The server compares the commodity positioning information with a preset position of the commodity. And if the commodity is not at the preset position, determining that the commodity is held by the target object.
In another example, the server acquires the movement trajectory of the target object through S303, and acquires the article location information through S309. The server compares the moving track with the track similarity of the commodity positioning information to judge whether the commodity is held. The method comprises the following specific steps:
step 1, the server determines the Frechet distance between the target object and the commodity according to the moving track of the target object and the commodity positioning information by using a Frechet track similarity measurement algorithm. When the Frechet distance is less than the threshold, the server may determine that the target object holds the item. The mapping process from the moving track of the target object and the commodity positioning information to the Frechet distance may be:
wherein α (t) is a track of the commodity positioning information on a time sequence. Wherein β (t) is a time-series trajectory of the movement trajectory of the target object.
And 2, the server establishes a neural network structure according to the moving track of the target object and the commodity positioning information. The neural network structure comprises an input layer node number 2, an output layer node number 2 and a hidden layer node number 4. And (3) extracting the coordinate point set in the track to be mapped obtained in the step (1) by the server to be used as a training set. After the system is put into use, the server continuously obtains a training set according to the steps and continuously trains the neural network model.
Wherein the neuron activation function is:
wherein the loss function is:
s311, counting the total duration of the commodity held by the target object, and determining a second attention index of the commodity according to the total duration.
In this embodiment, the server counts the total duration of time that the commodity is held by the target object within the preset time period. The second attention index can be obtained by calculation according to the total duration and a preset calculation formula. For example, the calculation formula may be:
second target indicator is total duration/10
And S312, determining the attention value of the commodity according to the first attention index and the second attention index.
And S313, determining the attention value ranking information of each commodity according to the commodity attention data.
And S314, determining display recommendation information according to the ranking information and the display position information of the attention value, wherein the display position information comprises characteristic information of each display position, and the display recommendation information comprises information of commodities recommended to be displayed at each display position.
Steps S312 to S314 are similar to steps S203 to S205 in the embodiment of fig. 3, and are not described herein again.
According to the commodity display position recommendation method, the server acquires video information from the visual sensor. And the server extracts the contour of the target object in each video and determines the coordinates of the target object in the video picture according to the contour. And the server selects the coordinate sequences of the target object in the two videos and determines the moving track of the target object according to the coordinate sequences of the target object in the two videos. And the server determines the time length when the distance between the commodity and the client is less than the preset value according to the moving track and the preset position of the commodity. And the server counts the total time length within a preset time period when the distances between all the target objects and the commodities are less than a preset value, and determines a first attention index according to the total time length. The server acquires the Bluetooth information fed back by the Bluetooth fixed tag through the Bluetooth beacon device. The bluetooth information includes a received signal strength indicator RSSI signal. The server selects a first group of Bluetooth information, and determines a first coordinate of the commodity according to the first group of Bluetooth information, wherein the first group of Bluetooth information is any three pieces of Bluetooth information in a Bluetooth information set. The server selects a second group of Bluetooth information, and determines a second coordinate of the commodity according to the second group of Bluetooth information, wherein at least one piece of Bluetooth information in the second group of Bluetooth information is different from the Bluetooth information in the first group of Bluetooth information. And the server determines the commodity positioning information according to the first coordinate and the second coordinate. And the server compares the positioning information with the preset position of the commodity to determine whether the commodity is held. And the server counts the total duration of the commodity held by the target object and determines a second attention index of the commodity according to the total duration. And the server determines the attention value of the commodity according to the first attention index and the second attention index. Further, the server determines product interest degree data in the experience shop based on the interest degree values of the respective products. And the server determines the ranking information of the attention value of each commodity according to the commodity attention data. The server stores each display position information. And the server recommends the corresponding commodities to each display position according to the ranking information of the attention value and the importance degree of the display position. In the application, the moving track and the commodity positioning information of the target object are obtained through calculation by acquiring the video information and the Bluetooth information from the visual sensor and the Bluetooth beacon device. Furthermore, the duration of the commodity held by the target object is calculated according to the moving track of the target object and the commodity positioning information, so that the calculation accuracy of the second attention index is improved, and the calculation accuracy of the attention value of the commodity is improved. And then, according to the attention value, the commodity with high attention degree is placed at the display position with higher importance degree, and the reasonable planning of commodity display is realized. Meanwhile, the method for calculating the attention value according to the moving track of the target object and the commodity positioning information avoids the problem of inaccurate calculation caused by space change, and improves the application range of the method.
Fig. 5 is a schematic structural diagram of a product display position recommendation device according to an embodiment of the present application, and as shown in fig. 5, a product display position recommendation device 10 according to this embodiment is used to implement an operation corresponding to a server in any one of the method embodiments described above, where the product display position recommendation device 10 according to this embodiment includes:
the attention unit 11 is configured to acquire commodity attention data, where the commodity attention data includes an attention value of at least one commodity, and the attention value is used to indicate an attention degree of a corresponding commodity within a preset time period.
And the sorting unit 12 is used for determining the attention value sorting information of each commodity according to the commodity attention data.
And the recommending unit 13 is configured to determine display recommendation information according to the ranking information and the display position information of the attention value, where the display position information includes feature information of each display position, and the display recommendation information includes information of commodities recommended to be displayed at each display position.
The commodity display position recommending apparatus 10 provided in the embodiment of the present application may implement the method embodiment, and specific implementation principles and technical effects thereof may refer to the method embodiment, which is not described herein again.
Fig. 6 is a schematic structural diagram of another product display position recommendation device according to an embodiment of the present application, and based on the embodiment shown in fig. 5, as shown in fig. 6, a product display position recommendation device 10 according to this embodiment is used to implement an operation corresponding to a server in any one of the method embodiments described above, where the attention unit 11 according to this embodiment includes:
the first obtaining module 111 is configured to obtain a first indicator of interest of the commodity, where the first indicator of interest is determined according to a total duration of a distance between the target object and the commodity within a preset time period and being smaller than a preset value.
The second obtaining module 112 is configured to obtain a second interest indicator of the commodity, where the second interest indicator is determined according to a duration of time that the commodity is held by the target object within a preset time period.
And the determining module 113 is configured to determine the attention value of the product according to the first attention index and the second attention index.
The commodity display position recommending apparatus 10 provided in the embodiment of the present application may implement the method embodiment, and specific implementation principles and technical effects thereof may refer to the method embodiment, which is not described herein again.
Fig. 7 is a schematic structural diagram of another product display position recommendation device according to an embodiment of the present application, and based on the embodiments shown in fig. 5 and fig. 6, as shown in fig. 7, the product display position recommendation device 10 according to this embodiment is used for implementing operations corresponding to a server in any one of the method embodiments described above, where the first obtaining module 111 and the second obtaining module 112 according to this embodiment include:
and the track acquisition sub-module 1111 is configured to acquire a moving track of the target object within a preset time period, and the moving track is obtained by positioning according to video information acquired by the visual sensor.
The first time length statistic submodule 1112 is configured to determine, according to the moving track and the preset position of the commodity, a time length when the distance between the commodity and the target object is smaller than a preset value.
The first index calculation submodule 1113 is configured to count total time lengths, within a preset time period, when distances between all the target objects and the commodities are smaller than a preset value, and determine a first attention index according to the total time lengths.
In an example, the trajectory acquisition sub-module 1111 is specifically configured to acquire a video information set, where the video information set includes video information of a target object within a preset time period captured by each of the vision sensors. And respectively extracting the outlines of the target objects in the video information, and determining the coordinate sequences of the target objects in the video information according to the outlines. And selecting the coordinate sequences of the target object in the two videos, and determining the moving track of the target object according to the coordinate sequences of the target object in the two videos.
And the positioning obtaining submodule 1121 is configured to obtain positioning information of the commodity within a preset time period, where the positioning information is obtained by positioning a bluetooth beacon device according to a bluetooth fixed tag attached to the commodity.
The second duration statistic submodule 1122 is configured to compare the positioning information with the preset position of the commodity, and determine whether the commodity is held.
The second indicator calculating submodule 1123 is configured to count a total duration of holding of the commodity by the target object, and determine a second attention indicator of the commodity according to the total duration.
In one example, the positioning obtaining sub-module 1121 is specifically configured to obtain a bluetooth information set, where the bluetooth information set includes bluetooth information obtained by positioning each bluetooth beacon device according to a bluetooth fixed tag attached to a commodity. And selecting a first group of Bluetooth information, and determining a first coordinate of the commodity according to the first group of Bluetooth information, wherein the first group of Bluetooth information is any three pieces of Bluetooth information in a Bluetooth information set. And selecting a second group of Bluetooth information, and determining a second coordinate of the commodity according to the second group of Bluetooth information, wherein at least one piece of Bluetooth information in the second group of Bluetooth information is different from the Bluetooth information in the first group of Bluetooth information. And determining the commodity positioning information according to the first coordinate and the second coordinate.
In one example, the bluetooth information includes a received signal strength indication RSSI signal.
Fig. 8 is a schematic structural diagram illustrating a merchandise display position recommendation system according to an embodiment of the present application. As shown in fig. 8, the product display position recommendation system 20 is configured to implement the operation corresponding to the server in any one of the method embodiments, and the product display position recommendation system 20 of this embodiment may include: server 21, vision sensor 22, bluetooth beacon device 23, and bluetooth positioning tag 24.
The server 21 is configured to implement the commodity display position recommendation method in the foregoing embodiment. Reference may be made in particular to the description relating to the method embodiments described above.
The bluetooth positioning tag 24 is adhered to the surface of the commodity, and the customer feeds back the position information of the commodity to the bluetooth beacon device.
The bluetooth beacon device 23 is installed at a first preset position on the roof in the store, and is used for acquiring the position information of the commodity sent by the bluetooth positioning tag.
The vision sensor 22 is installed at a second preset position on the roof of the store, and is used for acquiring the position information of the customer.
The server provided in this embodiment may be used to execute the method for recommending a merchandise display position, and the implementation manner and the technical effect are similar, which are not described herein again.
The present application also provides a computer-readable storage medium, in which a computer program is stored, and the computer program is used for implementing the methods provided by the above-mentioned various embodiments when being executed by a processor.
The computer-readable storage medium may be a computer storage medium or a communication medium. Communication media includes any medium that facilitates transfer of a computer program from one place to another. Computer storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, a computer readable storage medium is coupled to a server such that the server can read information from, and write information to, the computer readable storage medium. Of course, the computer readable storage medium may also be an integral part of the server. The server and the computer-readable storage medium may reside in an Application Specific Integrated Circuits (ASIC).
The computer-readable storage medium may be implemented by any type of volatile or nonvolatile Memory device or combination thereof, such as Static Random-Access Memory (SRAM), Electrically-Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk or optical disk. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
The present application also provides a program product comprising execution instructions stored in a computer-readable storage medium. The server may read the execution instructions from the computer-readable storage medium, and the server executes the execution instructions to cause the device to implement the methods provided by the various embodiments described above.
The chip is applied to a server and includes a memory and a processor, where the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that a device in which the chip is installed executes the method in the above various possible embodiments.
It should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the modules is only one logical division, and the actual implementation may have another division, for example, a plurality of modules may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.
Modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present application may be integrated into one processing unit, or each module may exist alone physically, or two or more modules are integrated into one unit. The unit formed by the modules can be realized in a hardware form, and can also be realized in a form of hardware and a software functional unit.
The integrated module implemented in the form of a software functional module may be stored in a computer-readable storage medium. The software functional module is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor to execute some steps of the methods according to the embodiments of the present application.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. Which when executed performs steps comprising the method embodiments described above. And the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same. Although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: it is also possible to modify the solutions described in the previous embodiments or to substitute some or all of them with equivalents. And the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.
Claims (10)
1. A commodity display position recommendation method is characterized by comprising the following steps:
the method comprises the steps of obtaining commodity attention data, wherein the commodity attention data comprise an attention value of at least one commodity, and the attention value is used for indicating the attention degree of the corresponding commodity in a preset time period;
determining the ranking information of the attention value of each commodity according to the commodity attention data;
and determining display position recommendation information according to the attention value ranking information and the display position information, wherein the display position information comprises characteristic information of each display position, and the display recommendation information comprises commodity information recommended to be displayed on each display position.
2. The method of claim 1, wherein the obtaining commodity attention data comprises:
acquiring a first attention index of a commodity, wherein the first attention index is determined according to the total duration that the distance between a target object and the commodity is less than a preset value in the preset time period;
acquiring a second attention index of the commodity, wherein the second attention index is determined according to the duration of the commodity held by the target object in the preset time period;
and determining the attention value of the commodity according to the first attention index and the second attention index.
3. The method of claim 2, wherein the obtaining a first indicator of interest of the commodity comprises:
acquiring a moving track of the target object within the preset time period, wherein the moving track is obtained by positioning according to video information acquired by a visual sensor;
determining a time length when the distance between the commodity and the target object is smaller than the preset value according to the moving track and the preset position of the commodity;
and counting the total time length of the distance between all the target objects and the commodity, which is less than a preset value, in the preset time period, and determining the first attention index according to the total time length.
4. The method according to claim 3, wherein the obtaining of the movement trajectory of the target object within the preset time period comprises:
acquiring a video information set, wherein the video information set comprises video information of the target object within the preset time period, which is obtained by shooting by each visual sensor;
respectively extracting the outlines of the target objects in the video information, and determining the coordinate sequences of the target objects in the video information according to the outlines;
and selecting the coordinate sequences of the target object in the two videos, and determining the moving track of the target object according to the coordinate sequences of the target object in the two videos.
5. The method of claim 2, wherein the obtaining a second indicator of interest for the commodity comprises:
acquiring positioning information of the commodity in the preset time period, wherein the positioning information is obtained by positioning a Bluetooth beacon device according to a Bluetooth fixed label pasted on the commodity;
comparing the positioning information with a preset position of the commodity to determine whether the commodity is held;
and counting the total duration of the commodity held by the target object, and determining the second attention index of the commodity according to the total duration.
6. The method according to claim 5, wherein the obtaining of the positioning information of the commodity in the preset time period comprises:
acquiring a Bluetooth information set, wherein the Bluetooth information set comprises Bluetooth information obtained by positioning each Bluetooth beacon device according to a Bluetooth fixed label pasted on the commodity;
selecting a first group of Bluetooth information, and determining a first coordinate of the commodity according to the first group of Bluetooth information, wherein the first group of Bluetooth information is any three pieces of Bluetooth information in the Bluetooth information set;
selecting a second group of Bluetooth information, and determining a second coordinate of the commodity according to the second group of Bluetooth information, wherein at least one piece of Bluetooth information in the second group of Bluetooth information is different from the Bluetooth information in the first group of Bluetooth information;
and determining the commodity positioning information according to the first coordinate and the second coordinate.
7. The method of claim 6, wherein a Received Signal Strength Indication (RSSI) signal is included in the Bluetooth message.
8. A merchandise display location recommendation device, the device comprising:
the system comprises an attention unit, a display unit and a display unit, wherein the attention unit is used for acquiring commodity attention data, the commodity attention data comprises an attention value of at least one commodity, and the attention value is used for indicating the attention degree of the corresponding commodity in a preset time period;
the ordering unit is used for determining the ordering information of the attention value of each commodity according to the commodity attention data;
and the recommending unit is used for determining display recommending information according to the attention value ranking information and the display position information, the display position information comprises characteristic information of each display position, and the display recommending information comprises commodity information recommended to be displayed on each display position.
9. A merchandise display location recommendation system, the system comprising: the system comprises a server, a visual sensor, a Bluetooth beacon device and a Bluetooth positioning tag;
the Bluetooth positioning label is pasted on the surface of the commodity, and the client feeds back the position information of the commodity to the Bluetooth beacon device;
the Bluetooth beacon device is arranged at a first preset position on a roof in a store and used for acquiring the position information of the commodity sent by the Bluetooth positioning tag;
the visual sensor is arranged at a second preset position of the roof in the store and used for acquiring the position information of the target object;
the server is used for implementing the commodity display position recommendation method according to any one of claims 1 to 7.
10. A computer-readable storage medium, wherein computer-executable instructions are stored in the computer-readable storage medium, and when executed by a processor, the computer-executable instructions are used for implementing the merchandise display position recommendation method according to any one of claims 1 to 7.
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