CN113961803A - Shooting recommendation method and device and computer-readable storage medium - Google Patents
Shooting recommendation method and device and computer-readable storage medium Download PDFInfo
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- CN113961803A CN113961803A CN202111177299.4A CN202111177299A CN113961803A CN 113961803 A CN113961803 A CN 113961803A CN 202111177299 A CN202111177299 A CN 202111177299A CN 113961803 A CN113961803 A CN 113961803A
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Abstract
The disclosure relates to a shot recommendation method and device and a computer-readable storage medium. The shot recommendation method comprises the following steps: acquiring portrait data of a photographed image, portrait data of a user and preset matching conditions; determining the corresponding relation between the photographed image and the user through a matching strategy according to the photographed image data, the user image data and the preset matching condition; and recommending the shot to the corresponding user. The scheme disclosed by the invention can be used for analyzing the accumulated user data and the current data to be shot based on a big data processing technology to form a corresponding user portrait and a shot portrait, and the shot portrait is pertinently recommended to the user according to the corresponding relation, so that the transaction rate of the shot is promoted.
Description
Technical Field
The present disclosure relates generally to the field of internet technology. More particularly, the present disclosure relates to a shot recommendation method and apparatus, and a computer-readable storage medium.
Background
With the rapid development of the internet technology and the proposal of the internet + concept, the development of the internet in the traditional industry is promoted. After the auction industry is networked, a large amount of data is accumulated, and the data serves various specific auction applications, particularly promotion and recommendation applications of auctions to customers in a manner of combining manual analysis and summary processing with human intervention.
However, in the current popularization and recommendation behaviors, a data analyst generally performs multidimensional analysis according to the grasped data to screen out the photos that the merchant may be interested in, and the photos are handed to the operator to communicate with the user, so that the user can know more photos information and participate in the auction to improve the trading rate. This process is labor intensive, has a significant delay, and the user may miss an intended auction because of forgetfulness.
Therefore, how to obtain an intelligent auction recommendation method is a problem to be solved in the prior art.
Disclosure of Invention
In order to at least partially solve the technical problems mentioned in the background, aspects of the present disclosure provide a method and apparatus for recommending a shot item, and a computer-readable storage medium.
According to a first aspect of the present disclosure, there is provided a method for recommending a shot, wherein the method comprises: acquiring portrait data of a photographed image, portrait data of a user and preset matching conditions; determining the corresponding relation between the photographed image and the user through a matching strategy according to the photographed image data, the user image data and the preset matching condition; and recommending the shot to the corresponding user.
Optionally, the acquiring of the portrait data of the photographed image includes: determining the attribute of the data to be matched; and extracting data of each shot from all shots to form shot image data of each shot according to the attributes of the data to be matched.
Optionally, the acquiring portrait data of the user includes: obtaining a preselected shot collection according to historical auction information of a user; adjusting the pre-selection shooting set according to user feedback information to obtain a user shooting set; extracting data of each photographed article in the user photographed article set according to the attributes of the data to be matched; and obtaining user portrait data according to all data with the same attribute of all the photographed images in the user photographed image set and the personal data of the user.
Optionally, the obtaining of the preset matching condition includes: and acquiring a preset matching condition corresponding to the attribute of the data to be matched.
Optionally, the user history auction information includes: the information of the photographed images which the user participates in the auction, the information of the photographed images which the user pays attention to and the information of the photographed images which the user browses.
Optionally, the user feedback information includes: the information of the photos that the user likes and/or the information of the photos that the user dislikes.
Optionally, the obtaining user portrait data according to all data of the same attribute of all photos in the user photo collection and the personal data of the user includes: determining the data range of the same attribute according to all data of the same attribute of all the photographed images in the user photographed image set; summarizing respective data ranges of all the data attributes to be matched as auction data of the user; and determining the user portrait data according to the auction data and the personal data of the user.
Optionally, the determining, according to the portrait data of the photographed image, the portrait data of the user, and the preset matching condition, a corresponding relationship between the photographed image and the user through a matching policy includes: determining whether the portrait data of the photographed image is matched with the auction data in the portrait data of the user or not according to the preset matching condition; and when the portrait data of the photographed image is matched with the auction data, determining the corresponding relation between the photographed image and the user according to personal information data in the portrait data of the user.
Optionally, the determining, according to the preset matching condition, whether the portrait data of the photographed image matches the auction data in the portrait data of the user includes: determining whether the portrait data of the photographed product and the auction data under each attribute of the data to be matched meet the corresponding preset matching condition, and determining the attribute of the data to be matched as a matching attribute when the data of the same attribute of the data to be matched in the auction data of the user and the portrait data of the photographed product meet the corresponding preset matching condition; counting the number of the matching attributes; and when the number of the matching attributes divided by the total number of the attributes of the data to be matched is greater than the preset matching degree, matching the portrait data of the photographed article with the auction data of the user.
Optionally, the recommending the shot to the corresponding user includes: and recommending the shot to the corresponding user through various channels.
According to a second aspect of the present disclosure, there is provided a device for recommending a shot, wherein the device comprises: the system comprises an acquisition module, a matching module and a display module, wherein the acquisition module is configured to acquire portrait data of a photographed article, portrait data of a user and preset matching conditions; the matching module is configured to determine the corresponding relation between the shot and the user through a matching strategy according to the image data of the shot, the image data of the user and the preset matching condition; a recommending module configured to recommend the beat items to the corresponding users.
Optionally, the obtaining module is configured to obtain the image data of the captured image by: determining the attribute of the data to be matched; and extracting data of each shot from all shots to form shot image data of each shot according to the attributes of the data to be matched.
Optionally, the obtaining module is configured to obtain portrait data of a user in the following manner: obtaining a preselected shot collection according to historical auction information of a user; adjusting the pre-selection shooting set according to user feedback information to obtain a user shooting set; extracting data of each photographed article in the user photographed article set according to the attributes of the data to be matched; and obtaining user portrait data according to all data with the same attribute of all the photographed images in the user photographed image set and the personal data of the user.
Optionally, the obtaining module is configured to obtain the preset matching condition in the following manner: and acquiring a preset matching condition corresponding to the attribute of the data to be matched.
Optionally, the user history auction information includes: the information of the photographed images which the user participates in the auction, the information of the photographed images which the user pays attention to and the information of the photographed images which the user browses.
Optionally, the user feedback information includes: the information of the photos that the user likes and/or the information of the photos that the user dislikes.
Optionally, the obtaining module is configured to obtain user portrait data according to all data of the same attribute of all photos in the user photo collection and the personal data of the user in the following manner: determining the data range of the same attribute according to all data of the same attribute of all the photographed images in the user photographed image set; summarizing respective data ranges of all the data attributes to be matched as auction data of the user; and determining the user portrait data according to the auction data and the personal data of the user.
Optionally, the matching module is configured to determine, according to the portrait data of the photographed image, the portrait data of the user, and the preset matching condition, a corresponding relationship between the photographed image and the user through a matching policy, in the following manner: determining whether the portrait data of the photographed image is matched with the auction data in the portrait data of the user or not according to the preset matching condition; and when the portrait data of the photographed image is matched with the auction data, determining the corresponding relation between the photographed image and the user according to personal information data in the portrait data of the user.
Optionally, the matching module is configured to determine whether the portrait data of the captured portrait is matched with the auction data in the portrait data of the user according to the preset matching condition in the following manner: determining whether the portrait data of the photographed product and the auction data under each attribute of the data to be matched meet the corresponding preset matching condition, and determining the attribute of the data to be matched as a matching attribute when the data of the same attribute of the data to be matched in the auction data of the user and the portrait data of the photographed product meet the corresponding preset matching condition; counting the number of the matching attributes; and when the number of the matching attributes divided by the total number of the attributes of the data to be matched is greater than the preset matching degree, matching the portrait data of the photographed article with the auction data of the user.
Optionally, the recommending module recommends the photographed images to the corresponding users in the following manner: and recommending the shot to the corresponding user through various channels.
According to a third aspect of the present disclosure, there is provided a device for recommending a photographed image, wherein the device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method of the first aspect of the present disclosure when executing the computer program.
According to a fourth aspect of the present disclosure, there is provided a computer readable storage medium, wherein the storage medium stores a computer program which, when executed, implements the method of the first aspect of the present disclosure described above.
By the shooting recommendation method and device, the accumulated user data and the current shooting data can be analyzed based on a big data processing technology to form corresponding user portrait and shooting portrait, and shooting is recommended to the user in a targeted manner according to the corresponding relation, so that the transaction rate of shooting is promoted.
Drawings
The above and other objects, features and advantages of exemplary embodiments of the present disclosure will become readily apparent from the following detailed description read in conjunction with the accompanying drawings. In the drawings, several embodiments of the disclosure are illustrated by way of example and not by way of limitation, and like or corresponding reference numerals indicate like or corresponding parts and in which:
FIG. 1 is a flow diagram illustrating a method for beat recommendation according to one embodiment of the present disclosure;
fig. 2 is a schematic block diagram illustrating a clap recommendation device according to one embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are some, but not all embodiments of the present disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
The present disclosure provides a method for recommending a photographed image. Referring to fig. 1, fig. 1 is a flowchart illustrating a method of tempo recommendation according to an embodiment of the present disclosure. As shown in fig. 1, the method comprises the following steps S101-S103. Step S101: and acquiring portrait data of a shot, portrait data of a user and preset matching conditions. Step S102: and determining the corresponding relation between the photographed image and the user through a matching strategy according to the photographed image data, the user image data and the preset matching condition. Step S103: and recommending the shot to the corresponding user.
By the shooting recommendation method, the accumulated user data and the current shooting data can be analyzed based on a big data processing technology to form the corresponding user portrait and the shooting portrait, and the shooting can be pertinently recommended to the user according to the corresponding relation, so that the transaction rate of the shooting is promoted.
In step S101, portrait data of a photographed image, portrait data of a user, and a preset matching condition may be acquired.
According to the embodiment of the present disclosure, in order to recommend a shooting to a user, portrait data of the shooting should be acquired. The image data of the photographed image is data constituting the photographed image, and the photographed image may include a plurality of attributes, and may have individual data for each attribute. For example, the photographic image may be a car (used car), and the image of the car includes attributes such as the brand of the car, the type of car, the rating of the car, the form mileage, the age of the car, each attribute having respective data, for example, the age of the car is 5 years. Of course, the time taken may be other types of tangible or intangible assets, and is not limited herein.
Further, the acquiring of the portrait data of the photographed image may include: determining the attribute of the data to be matched; and extracting data of each shot from all shots to form shot image data of each shot according to the attributes of the data to be matched.
Therefore, in order to acquire portrait data of a photographed image, it should be determined first what kind of attribute data needs to be extracted from various attribute data of the photographed image for later use, i.e., to determine data attributes to be matched, which may be prepared in advance and may be automatically called up, and may also be manually input by a human. The data attribute to be matched can be adjusted according to the requirement. Then, for each photographed image, data can be extracted according to the determined data attributes to be matched, and finally, the data of all the data attributes to be matched of a single photographed image are collected one by one to form the image data of the single photographed image. For example, in order to acquire image data of a car, attributes of data to be extracted from the car are first called or manually input, and corresponding data is extracted based on the attributes to construct image data of the car.
According to the embodiment of the disclosure, in order to recommend a shooting to a user, portrait data of the user should also be acquired. User representation data refers to data that constitutes a user representation, which may include user personal data and data related to a photographic image. The user personal data may include, for example, age, gender, various contact details (phone, micro-signal, mailbox, etc.), and city, etc.
Further, the acquiring portrait data of the user may include: obtaining a preselected shot collection according to historical auction information of a user; adjusting the pre-selection shooting set according to user feedback information to obtain a user shooting set; extracting data of each photographed article in the user photographed article set according to the attributes of the data to be matched; and obtaining user portrait data according to all data with the same attribute of all the photographed images in the user photographed image set and the personal data of the user.
In this embodiment, in order to acquire portrait data of a user, it is necessary to obtain user personal data and data related to a photographed image. User personal data may be obtained directly, while data related to the auction may be generated based on historical auction information for the auction in which the user has participated. The user history auction information may include: the information of the photographed images the user participates in the auction, the information of the photographed images the user has paid attention to and the information of the photographed images the user has browsed. Through the user historical auction information, a collection of beats related to the user may be formed. In addition, in order to further improve the accuracy of recommendation, a final shooting set may be formed by performing shooting deletion and addition operations on the shooting set formed above using user feedback information. The user feedback information may include: the information of the photos that the user likes and/or the information of the photos that the user dislikes. And the user feedback information may be information obtained by interacting with the user after each auction ends. For the final shooting set, the data of each shooting in the final shooting set is acquired for the same data attribute to be matched, as in the method for acquiring shooting image data described above. For example, if the attributes of the data to be matched determined in the above-described method of acquiring photographed image data are the brand, age, and evaluation level of the vehicle, these three attributes of the data to be matched are also used here. And finally, user portrait data can be obtained according to all data with the same attribute of all the photographed images in the user photographed image set and the personal data of the user.
Specifically, the obtaining user portrait data according to all data of the same attribute of all photos in the user photo collection and the personal data of the user may include: determining the data range of the same attribute according to all data of the same attribute of all the photographed images in the user photographed image set; summarizing respective data ranges of all the data attributes to be matched as auction data of the user; and determining the user portrait data according to the auction data and the personal data of the user.
In this embodiment, the data related to the auction is the auction data. After all data of the same attribute of all the shots in the shot collection of the user are obtained, all data under the same attribute may be summarized to obtain a range value, and the range value may be from a minimum value to a maximum value in all the data under the same attribute, or may be a section value occupying a maximum value in all the data. For example, when the photographed image is a car, the data range under the attribute is 1 to 10 years when the minimum value is 1 year and the maximum value is 10 years among all data under the age attribute of all cars. In addition, in order to reflect the data range more reasonably, the section value with a larger proportion in all the data can be selected according to the occurrence frequency of the specific car ages of the cars, for example, the car age with the current number arranged in the first two digits can be selected as the end value of the section, for example, the section value is selected from 2 to 6 years when the car age with the current number arranged in the first two digits appears for 1 time, 2 times, 4 times, 3 times, 5 times, 6 years and 1 time, 10 years, and other methods can be adopted to determine the section value. The data ranges corresponding to the different attributes may then be aggregated as auction data for the user. The auction data for each user and its personal data may constitute user representation data for that user.
According to the embodiment of the present disclosure, in order to recommend a photographed image to a user more accurately, a preset matching condition needs to be acquired so as to determine whether the user and the photographed image are matched, and the preset matching condition may be prepared in advance and may be manually input or automatically called. The obtaining of the preset matching condition may include: and acquiring a preset matching condition corresponding to the attribute of the data to be matched. In this embodiment, for the data attributes to be matched used in the photographed image and the user image, a separate preset matching condition is preset for each data attribute to be matched. The preset matching condition may be a correspondence of data and include: greater than, less than, inclusive, covered, and the like.
In step S102, a corresponding relationship between the photographed image and the user may be determined by a matching policy according to the photographed image data, the user image data, and the preset matching condition.
According to the embodiment of the disclosure, after the portrait data of the photographed image, the portrait data of the user and the preset matching condition are acquired, the corresponding relationship between the photographed image and the user can be determined through a matching strategy by using the portrait data of the photographed image, the portrait data of the user and the preset matching condition.
Further, the determining, according to the portrait data of the photographed image, the portrait data of the user, and the preset matching condition, the correspondence between the photographed image and the user through a matching policy may include: determining whether the portrait data of the photographed image is matched with the auction data in the portrait data of the user or not according to the preset matching condition; and when the portrait data of the photographed image is matched with the auction data, determining the corresponding relation between the photographed image and the user according to personal information data in the portrait data of the user.
Specifically, the determining whether the portrait data of the photographed image matches the auction data in the portrait data of the user according to the preset matching condition may include: determining whether the portrait data of the photographed product and the auction data under each attribute of the data to be matched meet the corresponding preset matching condition, and determining the attribute of the data to be matched as a matching attribute when the data of the same attribute of the data to be matched in the auction data of the user and the portrait data of the photographed product meet the corresponding preset matching condition; counting the number of the matching attributes; and when the number of the matching attributes divided by the total number of the attributes of the data to be matched is greater than the preset matching degree, matching the portrait data of the photographed article with the auction data of the user.
In this embodiment, for example, if the photographed image is an automobile, for example, the automobile age attribute in the user auction data is 3-5 years, the automobile age attribute in the photographed image data is 1 year, and the preset matching condition corresponding to the automobile age attribute is that the automobile age in the user auction data includes the automobile age in the photographed image data, the data of the automobile age attribute in the user auction data and the data of the automobile age attribute in the photographed image data do not satisfy the corresponding preset matching condition. For example, if the car age attribute in the user auction data is 3 to 5 years, the car age attribute in the photographed image data is 3 years (or 4 or 5 years), and the preset matching condition corresponding to the car age attribute is that the car age in the user auction data includes the car age in the photographed image data, the data of the car age attribute in the user auction data and the photographed image data satisfy the corresponding preset matching condition, and the car age attribute in the data attribute to be matched is determined as the matching attribute. After the above operations are performed according to respective preset matching conditions for each data attribute to be matched (e.g., brand of automobile, model of automobile, rating of automobile, mileage, age of automobile, etc.), the number of matching attributes in the data attributes to be matched can be obtained through statistics. And then, dividing the total number of the attributes of the data to be matched by the number of the matching attributes, comparing the division result with the preset matching degree, and matching the portrait data of the photographed image with the auction data in the portrait data of the user when the result is greater than the preset matching degree. The preset matching degree can be manually set according to needs.
Thus, when the portrait data of a photographed image matches the auction data in the portrait data of the user, the personal information data in the portrait data of the user can be called up to correspond the photographed image to the user.
In step S103, the shot may be recommended to the corresponding user.
According to the embodiment of the disclosure, after the corresponding relation between the shot and the user is determined, the shot can be recommended to the corresponding user. The recommending the shot to the corresponding user may include: and recommending the shot to the corresponding user through various channels. For example, the recommendation can be recommended to the corresponding user through channels such as WeChat, short message, APP, mail and the like.
Through the process, labor can be saved, and the shot can be recommended to the user through multiple channels in time. In addition, the recommendations can be re-sent or reminders sent periodically before the auction session to avoid users missing the auction session.
The present disclosure also provides a device for recommending the photographed product. The apparatus is configured to perform the steps in the embodiment of the method for recommending a photographic quality described above in connection with fig. 1.
Referring to fig. 2, fig. 2 is a schematic block diagram illustrating a shot recommendation apparatus 100 according to one embodiment of the present disclosure. The apparatus 100 includes an obtaining module 101, a matching module 102, and a recommending module 103. The acquisition module 101 is configured to acquire portrait data of a photographed image, portrait data of a user, and a preset matching condition. The matching module 102 is configured to determine a corresponding relationship between the photographed image and the user through a matching policy according to the photographed image data, the user image data, and the preset matching condition. The recommending module 103 is configured to recommend the shot to the corresponding user.
According to an embodiment of the present disclosure, the obtaining module 101 is configured to obtain the portrait data of the captured image as follows: determining the attribute of the data to be matched; and extracting data of each shot from all shots to form shot image data of each shot according to the attributes of the data to be matched.
According to an embodiment of the present disclosure, the obtaining module 101 is configured to obtain portrait data of a user in the following manner: obtaining a preselected shot collection according to historical auction information of a user; adjusting the pre-selection shooting set according to user feedback information to obtain a user shooting set; extracting data of each photographed article in the user photographed article set according to the attributes of the data to be matched; and obtaining user portrait data according to all data with the same attribute of all the photographed images in the user photographed image set and the personal data of the user.
According to an embodiment of the present disclosure, the obtaining module 101 is configured to obtain the preset matching condition in the following manner: and acquiring a preset matching condition corresponding to the attribute of the data to be matched.
According to an embodiment of the present disclosure, the user history auction information includes: the information of the photographed images which the user participates in the auction, the information of the photographed images which the user pays attention to and the information of the photographed images which the user browses.
According to an embodiment of the present disclosure, the user feedback information includes: the information of the photos that the user likes and/or the information of the photos that the user dislikes.
According to an embodiment of the present disclosure, the obtaining module 101 is configured to obtain user portrait data according to all data of the same attribute of all photos in the user photo collection and the personal data of the user in the following manner: determining the data range of the same attribute according to all data of the same attribute of all the photographed images in the user photographed image set; summarizing respective data ranges of all the data attributes to be matched as auction data of the user; and determining the user portrait data according to the auction data and the personal data of the user.
According to an embodiment of the present disclosure, the matching module 102 is configured to determine, according to the portrait data of the photographed image, the portrait data of the user, and the preset matching condition, a corresponding relationship between the photographed image and the user through a matching policy, in the following manner: determining whether the portrait data of the photographed image is matched with the auction data in the portrait data of the user or not according to the preset matching condition; and when the portrait data of the photographed image is matched with the auction data, determining the corresponding relation between the photographed image and the user according to personal information data in the portrait data of the user.
According to an embodiment of the present disclosure, the matching module 102 is configured to determine whether the portrait data of the captured portrait matches the auction data in the portrait data of the user according to the preset matching condition in the following manner: determining whether the portrait data of the photographed product and the auction data under each attribute of the data to be matched meet the corresponding preset matching condition, and determining the attribute of the data to be matched as a matching attribute when the data of the same attribute of the data to be matched in the auction data of the user and the portrait data of the photographed product meet the corresponding preset matching condition; counting the number of the matching attributes; and when the number of the matching attributes divided by the total number of the attributes of the data to be matched is greater than the preset matching degree, matching the portrait data of the photographed article with the auction data of the user.
According to an embodiment of the present disclosure, the recommending module 103 recommends the photographed images to the corresponding users as follows: and recommending the shot to the corresponding user through various channels.
It is to be understood that, regarding the device for recommending a feature of the embodiment described above with reference to fig. 2, the specific manner in which the respective modules perform operations has been described in detail in the embodiment of the method for recommending a feature of a feature described in conjunction with fig. 1, and will not be elaborated herein.
The embodiment of the present disclosure further provides a device for recommending a photographed image, where the device includes a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented: acquiring portrait data of a photographed image, portrait data of a user and preset matching conditions; determining the corresponding relation between the photographed image and the user through a matching strategy according to the photographed image data, the user image data and the preset matching condition; and recommending the shot to the corresponding user.
It is understood that the steps implemented when the computer program is executed by the processor are substantially the same as the implementation of the steps in the above method, and the specific manner is described in detail in the embodiment of the method for recommending the shooting quality, and will not be elaborated herein.
In another aspect, the present disclosure provides a computer-readable storage medium, wherein the storage medium stores a computer program that, when executed, implements the steps of: acquiring portrait data of a photographed image, portrait data of a user and preset matching conditions; determining the corresponding relation between the photographed image and the user through a matching strategy according to the photographed image data, the user image data and the preset matching condition; and recommending the shot to the corresponding user.
It is understood that the steps implemented when the computer program is executed by the processor are substantially the same as the implementation of the steps in the above method, and the specific manner is described in detail in the embodiment of the method for recommending the shooting quality, and will not be elaborated herein.
The embodiments of the present disclosure are described in detail above, and the principles and embodiments of the present disclosure are explained herein by applying specific embodiments, and the descriptions of the embodiments are only used to help understanding the method and the core ideas of the present disclosure; meanwhile, for a person skilled in the art, based on the idea of the present disclosure, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present disclosure should not be construed as a limitation to the present disclosure.
It should be understood that the terms "first" and "second," etc. in the claims, description, and drawings of the present disclosure are used for distinguishing between different objects and not for describing a particular order. The terms "comprises" and "comprising," when used in the specification and claims of this disclosure, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the disclosure herein is for the purpose of describing particular embodiments only, and is not intended to be limiting of the disclosure. As used in the specification and claims of this disclosure, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should be further understood that the term "and/or" as used in the specification and claims of this disclosure refers to any and all possible combinations of one or more of the associated listed items and includes such combinations.
The embodiments of the present disclosure have been described in detail, and the principles and embodiments of the present disclosure are explained herein using specific examples, which are provided only to help understand the method and the core idea of the present disclosure. Meanwhile, a person skilled in the art should, based on the idea of the present disclosure, change or modify the specific embodiments and application scope of the present disclosure. In view of the above, the description is not intended to limit the present disclosure.
Claims (22)
1. A method of shot recommendation, wherein the method comprises:
acquiring portrait data of a photographed image, portrait data of a user and preset matching conditions;
determining the corresponding relation between the photographed image and the user through a matching strategy according to the photographed image data, the user image data and the preset matching condition;
and recommending the shot to the corresponding user.
2. The method for recommending a shooting quality of claim 1, wherein said obtaining portrait data of a shooting quality comprises:
determining the attribute of the data to be matched;
and extracting data of each shot from all shots to form shot image data of each shot according to the attributes of the data to be matched.
3. The method of claim 2, wherein the obtaining of portrait data of a user comprises:
obtaining a preselected shot collection according to historical auction information of a user;
adjusting the pre-selection shooting set according to user feedback information to obtain a user shooting set;
extracting data of each photographed article in the user photographed article set according to the attributes of the data to be matched;
and obtaining user portrait data according to all data with the same attribute of all the photographed images in the user photographed image set and the personal data of the user.
4. The method for recommending racket products of claim 3, wherein the obtaining of the preset matching condition comprises:
and acquiring a preset matching condition corresponding to the attribute of the data to be matched.
5. The item recommendation method of claim 3, wherein the user history auction information comprises: the information of the photographed images which the user participates in the auction, the information of the photographed images which the user pays attention to and the information of the photographed images which the user browses.
6. The method of claim 3, wherein the user feedback information comprises: the information of the photos that the user likes and/or the information of the photos that the user dislikes.
7. The feature shooting recommendation method of claim 4, wherein the obtaining user portrait data from all data of the same attribute of all the features in the user feature shooting set and the personal data of the user comprises:
determining the data range of the same attribute according to all data of the same attribute of all the photographed images in the user photographed image set;
summarizing respective data ranges of all the data attributes to be matched as auction data of the user;
and determining the user portrait data according to the auction data and the personal data of the user.
8. The shooting recommendation method according to claim 7, wherein the determining, according to the portrait data of the shooting, the portrait data of the user and the preset matching condition, the correspondence between the shooting and the user through a matching policy comprises:
determining whether the portrait data of the photographed image is matched with the auction data in the portrait data of the user or not according to the preset matching condition;
and when the portrait data of the photographed image is matched with the auction data, determining the corresponding relation between the photographed image and the user according to personal information data in the portrait data of the user.
9. The shooting recommendation method of claim 8, wherein the determining whether the portrait data of the shooting is matched with the auction data in the portrait data of the user according to the preset matching condition comprises:
determining whether the portrait data of the photographed product and the auction data under each attribute of the data to be matched meet the corresponding preset matching condition, and determining the attribute of the data to be matched as a matching attribute when the data of the same attribute of the data to be matched in the auction data of the user and the portrait data of the photographed product meet the corresponding preset matching condition;
counting the number of the matching attributes;
and when the number of the matching attributes divided by the total number of the attributes of the data to be matched is greater than the preset matching degree, matching the portrait data of the photographed article with the auction data of the user.
10. The tempo recommendation method according to claim 1, wherein said recommending said tempo to said corresponding user comprises:
and recommending the shot to the corresponding user through various channels.
11. A device for recommending a shot, wherein the device comprises:
the system comprises an acquisition module, a matching module and a display module, wherein the acquisition module is configured to acquire portrait data of a photographed article, portrait data of a user and preset matching conditions;
the matching module is configured to determine the corresponding relation between the shot and the user through a matching strategy according to the image data of the shot, the image data of the user and the preset matching condition;
a recommending module configured to recommend the beat items to the corresponding users.
12. The device of claim 11, wherein the obtaining module is configured to obtain the portrait data of the captured feature by:
determining the attribute of the data to be matched;
and extracting data of each shot from all shots to form shot image data of each shot according to the attributes of the data to be matched.
13. The device of claim 12, wherein the obtaining module is configured to obtain the portrait data of the user by:
obtaining a preselected shot collection according to historical auction information of a user;
adjusting the pre-selection shooting set according to user feedback information to obtain a user shooting set;
extracting data of each photographed article in the user photographed article set according to the attributes of the data to be matched;
and obtaining user portrait data according to all data with the same attribute of all the photographed images in the user photographed image set and the personal data of the user.
14. The device for recommending the photographed image according to claim 13, wherein the obtaining module is configured to obtain the preset matching condition by:
and acquiring a preset matching condition corresponding to the attribute of the data to be matched.
15. The auction recommendation device of claim 13, wherein the user historical auction information comprises: the information of the photographed images which the user participates in the auction, the information of the photographed images which the user pays attention to and the information of the photographed images which the user browses.
16. The device of claim 13, wherein the user feedback information comprises: the information of the photos that the user likes and/or the information of the photos that the user dislikes.
17. The item of shooting recommendation device of claim 14, wherein the obtaining module is configured to obtain user portrait data from all data of the same attribute of all the items of shooting in the user item of shooting set and the personal data of the user as follows:
determining the data range of the same attribute according to all data of the same attribute of all the photographed images in the user photographed image set;
summarizing respective data ranges of all the data attributes to be matched as auction data of the user;
and determining the user portrait data according to the auction data and the personal data of the user.
18. The shooting recommendation device of claim 17, wherein the matching module is configured to determine the correspondence between the shooting and the user through a matching policy according to the portrait data of the shooting, the portrait data of the user, and the preset matching condition as follows:
determining whether the portrait data of the photographed image is matched with the auction data in the portrait data of the user or not according to the preset matching condition;
and when the portrait data of the photographed image is matched with the auction data, determining the corresponding relation between the photographed image and the user according to personal information data in the portrait data of the user.
19. The device of claim 18, wherein the matching module is configured to determine whether the portrait data of the captured image matches the auction data in the portrait data of the user according to the preset matching condition by:
determining whether the portrait data of the photographed product and the auction data under each attribute of the data to be matched meet the corresponding preset matching condition, and determining the attribute of the data to be matched as a matching attribute when the data of the same attribute of the data to be matched in the auction data of the user and the portrait data of the photographed product meet the corresponding preset matching condition;
counting the number of the matching attributes;
and when the number of the matching attributes divided by the total number of the attributes of the data to be matched is greater than the preset matching degree, matching the portrait data of the photographed article with the auction data of the user.
20. The device of claim 11, wherein the recommending module recommends the beat to the corresponding user as follows:
and recommending the shot to the corresponding user through various channels.
21. An apparatus for recommending beats, wherein the apparatus comprises a memory in which is stored a computer program and a processor which, when executing the computer program, implements the method according to any one of claims 1 to 10.
22. A computer-readable storage medium, wherein the storage medium stores a computer program which, when executed, implements the method of any one of claims 1-10.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202111177299.4A CN113961803A (en) | 2021-10-09 | 2021-10-09 | Shooting recommendation method and device and computer-readable storage medium |
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| CN202111177299.4A CN113961803A (en) | 2021-10-09 | 2021-10-09 | Shooting recommendation method and device and computer-readable storage medium |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114840567A (en) * | 2022-07-04 | 2022-08-02 | 太平洋国际拍卖有限公司 | Hill sorting-based shot sorting chart display method and system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114840567A (en) * | 2022-07-04 | 2022-08-02 | 太平洋国际拍卖有限公司 | Hill sorting-based shot sorting chart display method and system |
| CN114840567B (en) * | 2022-07-04 | 2022-10-11 | 太平洋国际拍卖有限公司 | Hill sorting-based shot sorting chart display method and system |
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