CN110472145B - Content recommendation method and electronic equipment - Google Patents
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Abstract
The invention provides a content recommendation method and electronic equipment, and relates to the technical field of internet. Wherein, the method comprises the following steps: acquiring content to be recommended and at least two target user figures corresponding to target users; respectively determining a target weight coefficient of each target user portrait and a matching coefficient between each target user portrait and the content to be recommended; determining a recommendation index corresponding to the target user according to the matching coefficient and the target weight coefficient corresponding to each target user portrait; and when the recommendation index meets a preset recommendation condition, pushing the content to be recommended to the target user. According to the method and the device, the target user figures of the target user in different fields can be determined, and whether the content to be recommended which is cross-field but related to the fields of the target user figures is pushed to the target user or not is determined based on the target weight coefficients of the different target user figures and the matching degree of the target user figures and the content to be recommended, so that personalized content recommendation can be performed on the target user in a new field.
Description
Technical Field
The invention relates to the technical field of internet, in particular to a content recommendation method and electronic equipment.
Background
With the rapid development of the internet technology, the demand of users for obtaining content from the internet also tends to be more and more extensive in field, which also prompts a plurality of software products to take the original single-field product as the core and expand a large number of products in the peripheral fields so as to meet the demand of users for obtaining content in cross-field.
However, in practical applications, when a user acquires content, there is usually a demand for personalized content recommendation, and many software products cannot respectively perform personalized content recommendation on different users in a newly added field.
Disclosure of Invention
The invention provides a content recommendation method and electronic equipment, and aims to solve the problem that cross-field recommended content cannot meet the personalized requirements of users.
In order to solve the technical problem, the invention is realized as follows:
in a first aspect, an embodiment of the present invention provides a content recommendation method, applied to an electronic device, including:
acquiring content to be recommended and at least two target user figures corresponding to target users; wherein different ones of the target user representations have different domain attributes, respectively;
respectively determining target weight coefficients corresponding to the at least two target user portraits and matching coefficients between the at least two target user portraits and the content to be recommended;
determining a recommendation index corresponding to each target user according to the matching coefficient and the target weight coefficient corresponding to each target user portrait;
and when the recommendation index meets a preset recommendation condition, pushing the content to be recommended to the target user.
In a second aspect, an embodiment of the present invention further provides an electronic device, including:
the acquisition module is used for acquiring the content to be recommended and at least two target user figures corresponding to the target users; wherein different ones of the target user representations have different domain attributes, respectively;
the first determining module is used for respectively determining target weight coefficients corresponding to the at least two target user portraits and matching coefficients between the at least two target user portraits and the content to be recommended;
the second determining module is used for determining a recommendation index corresponding to each target user according to the matching coefficient and the target weight coefficient corresponding to each target user portrait;
and the pushing module is used for pushing the content to be recommended to the target user when the recommendation index meets a preset recommendation condition.
In a third aspect, an embodiment of the present invention further provides an electronic device, which includes a processor, a memory, and a computer program stored on the memory and executable on the processor, and when the computer program is executed by the processor, the steps of the content recommendation method according to the present invention are implemented.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the content recommendation method according to the present invention are implemented.
In the embodiment of the invention, the electronic equipment can firstly acquire the content to be recommended and at least two target user images corresponding to target users, wherein different target user images respectively have different domain attributes, and the domain attributes of the target user images are associated with the domain attributes of the content to be recommended. Then the electronic equipment can respectively determine a target weight coefficient corresponding to each target user portrait in the at least two target user portraits and a matching coefficient between each target user portrait in the at least two target user portraits and the content to be recommended, determine a recommendation index corresponding to the target user according to the matching coefficient and the target weight coefficient corresponding to each target user portrait, and push the content to be recommended to the target user when the recommendation index meets a preset recommendation condition. In the embodiment of the invention, the electronic equipment can determine target user figures corresponding to different fields of a target user, and determine whether to push the content to be recommended to the target user, which is related to the field to which each target user figure belongs but is across the fields, based on the target weight coefficients corresponding to the different target user figures and the matching degree between each target user figure and the content to be recommended, so that personalized content recommendation can be performed on the target user in a new field.
Drawings
Fig. 1 shows a flow chart of a content recommendation method in a first embodiment of the present invention;
FIG. 2 is a flowchart of a content recommendation method according to a second embodiment of the present invention;
fig. 3 shows a block diagram of an electronic device in a third embodiment of the present invention;
fig. 4 is a block diagram showing another electronic device according to a third embodiment of the present invention;
fig. 5 is a schematic diagram illustrating a hardware structure of an electronic device according to various embodiments of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.
Example one
Referring to fig. 1, a flowchart of a content recommendation method according to a first embodiment of the present invention is shown, which may specifically include the following steps:
In the embodiment of the present invention, the domain attribute of the target user representation is associated with the domain attribute of the content to be recommended, and the content to be recommended may be content configured in the electronic device by a software product party according to a self service requirement or a customer service requirement, where the electronic device may be a server, a server group, and the like corresponding to the software product, and this is not particularly limited in the embodiment of the present invention. The Content to be recommended may specifically include Content in the aspects of an advertisement, a function, a product, a User-generated Content (UGC), a professional-generated Content (PGC), and the like, which is not specifically limited in this embodiment of the present invention.
The target user is also one of the potential users who need to judge whether the content to be recommended needs to be pushed or not. The target user can be any user who registers an account in the software product or a related product thereof, wherein the related product of the software product and the software product can log in and use the software product through the same account, such as a mobile phone number, a micro signal and the like, so that the electronic equipment can identify user figures accumulated in different software by the same user according to the same account. Of course, the target user may also be one of the users selected by the electronic device based on a preset policy, for example, one of the member users, which is not specifically limited in this embodiment of the present invention.
In practical applications, the electronic device may also be a server device corresponding to a related product of the software product, or the electronic device may receive user data sent by server devices corresponding to other related products, and correspondingly, at least two target user representations corresponding to a target user may be selected by the electronic device from user data collected and stored by the electronic device itself, or may also be sent to the electronic device by other server devices, which is not specifically limited in the embodiment of the present invention.
The target user portrait corresponding to the target user, that is, data such as personal information, habits, and preferences of the target user in a certain field, may be, for example, data such as habits and preferences of the user in different fields, such as a work field, a leisure field, a trip field, a driving field, a home field, a health field, a sport field, a consultation field, a financing field, an education field, and a consumption field, and the embodiment of the present invention is not particularly limited thereto.
Different target user portraits corresponding to the target users respectively have different domain attributes, and the domain attribute of each user portraits is associated with the domain attribute of the content to be recommended. For example, the domain attribute of the first target user representation corresponding to the target user may be song listening, that is, the first target user representation is habit and preference data of the target user in the song listening domain, the domain attribute of the second target user representation corresponding to the target user may be entertainment consumption, that is, the second target user representation is habit and preference data of the target user in the entertainment consumption domain, and the domain attribute of the content to be recommended may be music/concert. Therefore, the electronic equipment can determine whether to push the content to be recommended to the target user, which is cross-domain and is associated with the domain to which each target user portrait belongs, based on the target user portraits corresponding to different domains of the target user.
It should be noted that, in the embodiment of the present invention, the order of acquiring the content to be recommended and at least two target user portraits corresponding to the target user is not specifically limited.
In the embodiment of the present invention, because the association degrees of the target user images in different fields and the content to be recommended are different, and the influence degree of the content to be recommended is different, a target weight coefficient corresponding to each target user image may be set in advance and stored in the electronic device, or a target weight coefficient corresponding to each target user image may be set based on a result fed back by a small number of users. After obtaining at least two target user images corresponding to a target user, the electronic device may determine a target weight coefficient set for each target user image.
In addition, the matching coefficient between the target user portrait and the content to be recommended may represent the degree of correlation between the target user portrait and the content to be recommended, for example, if the target user portrait includes the permanent location information of the target user and the content to be recommended relates to a location, when the permanent location information of the target user is the same as the location in the content to be recommended, the matching coefficient between the target user portrait and the content to be recommended is larger, and when the permanent location information of the target user is the same as the location in the content to be recommended, the matching coefficient between the target user portrait and the content to be recommended is inferior to the first case, and when the permanent location information of the target user is different from the location in the content to be recommended, the matching coefficient between the target user portrait and the content to be recommended is inferior to the second case.
It should be noted that, in the embodiment of the present invention, the determination order of the target weight coefficient and the matching coefficient is not particularly limited.
And 103, determining a recommendation index corresponding to the target user according to the matching coefficient and the target weight coefficient corresponding to each target user portrait.
In the embodiment of the invention, the electronic device can perform weighted summation on the matching coefficients corresponding to the target user figures according to the target weight coefficient corresponding to each target user figure of the target user, so that the recommendation index corresponding to the target user can be obtained. And when the recommendation index corresponding to the target user is larger, the target user is a powerful recommendation object capable of pushing the content to be recommended.
And 104, when the recommendation index meets a preset recommendation condition, pushing the content to be recommended to the target user.
In the embodiment of the invention, the preset recommendation condition can be set in the electronic equipment in advance, and when the recommendation index corresponding to the target user meets the preset recommendation condition, the content to be recommended can be pushed to the target user.
In the embodiment of the invention, the electronic equipment can firstly acquire the content to be recommended and at least two target user images corresponding to the target users, wherein different target user images respectively have different domain attributes, and the domain attributes of the target user images are associated with the domain attributes of the content to be recommended. Then, the electronic device can respectively determine a target weight coefficient corresponding to each target user portrait in the at least two target user portraits and a matching coefficient between each target user portrait in the at least two target user portraits and the content to be recommended, determine a recommendation index corresponding to the target user according to the matching coefficient corresponding to each target user portrait and the target weight coefficient, and push the content to be recommended to the target user when the recommendation index meets a preset recommendation condition. In the embodiment of the invention, the electronic equipment can determine the target user figures corresponding to different fields of the target user, and determine whether to push the content to be recommended, which is related to the fields of the cross-field and the target user figures, to the target user based on the target weight coefficients corresponding to the different target user figures and the matching degree between each target user figure and the content to be recommended, so that the target user can be subjected to personalized content recommendation in a new field.
Example two
Referring to fig. 2, a flowchart of a content recommendation method according to a second embodiment of the present invention is shown, which may specifically include the following steps:
This step is similar to the implementation of step 101 described above and will not be described in detail here.
For example, a traditional online music software originally only has related functions in the field of listening to songs, and a new function, namely a concert and ticket sale function of the concert, is introduced, and the original user image of the music software has certain understanding on the music preference of the user. At present, there is a cross-domain to-be-recommended content "X day-shanghai-singer certain-price concert ticket sale" to be recommended to a user, and the domain attribute of the to-be-recommended content is "concert/concert ticket". For a target user, the music software can collect the basic information user portrait and the music user portrait corresponding to the target user originally, and the music software can log in through an account number of another payment software, so that the music software can also collect the consumption capability portrait corresponding to the target user through the payment software. The electronic device corresponding to the application software, namely the server, can obtain the content to be recommended, namely 'X day-Shanghai-singer Zhang certain-concert admission ticket sale with the price of Y', and three target user images, namely a basic information user image, a music user image and a consumption capability image, corresponding to the target user. Referring to table 1 below, user information included in each target user profile, corresponding domain attributes, and an association with content to be recommended are shown.
TABLE 1
The embodiments of the present invention are described only by taking the data such as various target user images and user information shown in table 1 above as an example, and the data shown in table 1 above is not intended to limit the present invention.
In this embodiment of the present invention, before this step, the electronic device may further perform the following steps, which specifically include: determining at least two initial weight coefficients corresponding to each target user portrait; adjusting the at least two initial weight coefficients according to an A/B test strategy to obtain target weight coefficients; storing the corresponding relationship between each target user portrait and each target weight coefficient.
Specifically, for any target user portrait corresponding to a target user, the electronic device may first assign at least two initial weight coefficients to the target user portrait, and one initial weight coefficient may be used as a weight test policy, so as to obtain at least two weight test policies. Then, the electronic device can randomly select users with a preset proportion from all candidate users to be recommended, then the selected users can be grouped, each group executes the method according to different weight test strategies respectively so as to push the contents to be recommended to each selected user, and further, the optimal weight test strategy fed back by the user can be selected from at least two weight test strategies according to feedback results of clicking conditions of the user on a recommendation interface, browsing duration of the recommendation interface and the like.
Next, the electronic device may adjust the weight coefficient in the weight test strategy that is the best feedback from the user, and the adjustment principle may be: the weighting coefficient corresponding to the target user image which is beneficial to the recommendation can be increased, and the weighting coefficient corresponding to the target user image which has no obvious influence on the recommendation can be decreased. Through adjustment in different degrees, at least two new weight coefficients can be obtained again, and then the electronic device can randomly select users with preset proportions from the remaining candidate users, and then the process is repeated until the weight test strategy with the best user feedback is selected again from the at least two new weight test strategies. The process can be repeated for preset times, and for the weight test strategy with the best user feedback selected at the last time, the electronic device can determine each weight coefficient in the weight test strategy as a target weight coefficient corresponding to each target user portrait and can store the corresponding relation between each target user portrait and each target weight coefficient.
For example, the electronic device may determine 4 initial weighting coefficients for each target user portrait, so that four weighting test policies a, B, C, and D may be obtained, and then the electronic device may randomly select 10% of users from all candidate users to be recommended for pushing, where each weighting test policy may be for 2.5% of users. According to the user feedback result, the electronic equipment can select the weight test strategy A which is best fed back by the user, further the electronic equipment can adjust the weight coefficient of the target user portrait which is beneficial to recommendation to the user to be recommended to be high on the basis of the weight test strategy A, adjust the weight coefficient of the target user portrait which has no influence on the recommendation to be low, through adjustment of different degrees, 4 new weight test strategies E, F, G and H can be obtained again, the weight test strategies E, F, G and H are pushed to 10% of the rest candidate users continuously, after the user feedback result is obtained, the electronic equipment can select the optimal weight test strategy F, the basic information user portrait and the target weight coefficient 0.20 corresponding to the basic information user portrait in the weight test strategy F are stored correspondingly, the music user portrait and the target weight coefficient 0.55 corresponding to the music user portrait in the weight test strategy F are stored correspondingly, and the target weight coefficient 0.25 corresponding to the consumption user portrait in the weight test strategy F is stored correspondingly.
Of course, in practical applications, the target weight coefficient corresponding to each target user image may also be manually set, and the corresponding relationship between the target user image and the set target weight coefficient is stored in the electronic device.
Accordingly, the electronic device may determine the target weight coefficient corresponding to the current target user image from the pre-stored correspondence between the user image and the weight coefficient.
For example, the correspondence relationship between the user image and the weight coefficient pre-stored in the electronic device may be as shown in table 2 below, and the electronic device may determine, from the correspondence relationship shown in table 2, that the target weight coefficient corresponding to the basic information user image is 0.20, the target weight coefficient corresponding to the music user image is 0.55, and the target weight coefficient corresponding to the consumer user image is 0.25, respectively.
TABLE 2
| User representation | Weight coefficient |
| Basic information user representation | 0.20 |
| Music user portrait | 0.55 |
| Consumer capability user representation | 0.25 |
It should be noted that the embodiment of the present invention is described only by taking the correspondence between the user image and the weight coefficient as shown in table 2 above as an example, and the present invention is not limited to table 2 above.
In the embodiment of the present invention, each target user representation may include user information in at least one dimension, for example, the basic information user representation may include user information in dimensions of gender, age, permanent, and the like. At least two preset conditions can be set for each dimension respectively according to the content to be recommended and the user information under each dimension in advance. Correspondingly, for any dimension, the electronic device may determine, from the preset conditions corresponding to the dimension, a target preset condition that the user information in the dimension conforms to.
For example, referring to table 3 below, taking the user information of the permanent dimension corresponding to the basic information user image as an example, the permanent dimension is correspondingly set with 4 preset conditions, the user information of the permanent dimension may be shanghai, that is, the permanent of the target user is shanghai, when the concert place is located in shanghai, the electronic device may determine that the 1 st preset condition, "the target user permanent and the concert place are located in the same city," is the target preset condition met by the user information in the permanent dimension.
TABLE 3
It should be noted that, the embodiment of the present invention is only described by taking the preset conditions and the matching scores shown in table 3 above as examples, and table 3 above does not limit the present invention.
And 204, respectively determining a matching score corresponding to each target preset condition.
In the embodiment of the present invention, the electronic device may determine the matching score corresponding to each target preset condition from the corresponding relationship between the preset condition and the matching score.
For example, the electronic device may determine, from the correspondence between the preset conditions and the matching scores shown in table 3 above, that the matching score corresponding to the target preset condition "the target user permanent and the concert location are located in the same city" is 3.
In the embodiment of the invention, the electronic equipment can add the matching scores corresponding to each target preset condition in the same target user portrait, so that the matching coefficient between each target user portrait and the content to be recommended can be respectively obtained.
For example, the electronic device may add matching scores corresponding to each target preset condition in the basic information user representation, so that a matching coefficient between the basic information user representation and the content to be recommended may be 6. The electronic equipment can add the matching scores corresponding to each target preset condition in the music user portrait, so that the matching coefficient between the music user portrait and the content to be recommended can be 8. The electronic equipment can add the matching scores corresponding to each target preset condition in the user portrait of the consuming capacity, so that the matching coefficient between the user portrait of the consuming capacity and the content to be recommended is 2.
And step 206, determining a recommendation index corresponding to the target user according to the matching coefficient and the target weight coefficient corresponding to each target user portrait.
In the embodiment of the present invention, the step may be specifically implemented in a manner including: multiplying the matching coefficient corresponding to the same target user image by the target weight coefficient to obtain a recommended value corresponding to each target user image; and adding the recommendation values corresponding to the images of the target users to obtain the recommendation index corresponding to the target user.
The electronic equipment can perform weighted summation on the matching coefficients corresponding to the target user portraits according to the target weight coefficient corresponding to each target user portraits of the target users, and therefore the recommendation index corresponding to the target users can be obtained. And when the recommendation index corresponding to the target user is larger, the target user is a powerful recommendation object capable of pushing the content to be recommended. When the recommendation index corresponding to the target user is smaller, the target user is less likely to be a recommendation object of the content to be recommended.
In another implementation manner, the electronic device may further multiply the matching score corresponding to each target preset condition in each target user portrait by a target weight coefficient of the corresponding target user portrait respectively to obtain respective products, and then may add the respective products to obtain the recommendation index corresponding to the target user. The embodiment of the present invention does not specifically limit the specific implementation manner of determining the recommendation index corresponding to the target user.
For example, the electronic device may multiply the matching coefficient 6 corresponding to the basic information user image by the target weight coefficient 0.20, and obtain a recommended value corresponding to the basic information user image as 1.2; the electronic equipment can multiply the matching coefficient 8 of the corresponding music user image with a target weight coefficient of 0.55 to obtain a recommended value of 4.4 corresponding to the music user image; the electronic device may multiply the matching coefficient 2 corresponding to the consumable user image by the target weight coefficient 0.25 to obtain a recommended value of 0.5 corresponding to the consumable user image. Then, the electronic device may add the recommended value 1.2 corresponding to the basic information user image, the recommended value 4.4 corresponding to the music user image, and the recommended value 0.5 corresponding to the consumption capability user image to obtain a recommendation index of 6.1 corresponding to the target user.
And step 207, when the recommendation index meets a preset recommendation condition, pushing the content to be recommended to the target user.
In the embodiment of the invention, when the recommendation index corresponding to the target user meets the preset recommendation condition, the electronic device can send the recommendation information corresponding to the content to be recommended to the terminal logged in by the target user through the software account. In a specific application, the recommendation information may be information in the form of text, image, video, voice, and the like, which is not specifically limited in this embodiment of the present invention. And then the terminal corresponding to the target user can display the recommendation information, so that the target user can check the recommendation information.
Optionally, the step may be specifically implemented by the following steps, including: when the recommendation index is larger than or equal to a preset value, pushing the content to be recommended to the target user; and/or when the ranking of the recommendation indexes in the recommendation indexes corresponding to the preselected users is less than or equal to the preset ranking, pushing the content to be recommended to a target user; the recommendation indexes corresponding to the preselected users are arranged in the descending order.
That is, the preset recommendation condition may be that the recommendation index is greater than or equal to the preset value, and/or that the ranking of the recommendation index in the recommendation indexes corresponding to the preselected users is less than or equal to the preset ranking. Each pre-selected user is all potential users who need to judge whether the content to be recommended needs to be pushed, and correspondingly, the target user is any one of the pre-selected users.
When the recommendation index corresponding to the target user is greater than or equal to the preset value and/or the target user ranks at the top among all the preselected users with the recommendation indexes arranged from large to small, the content to be recommended is pushed to the target user, the personalized requirements of the target user can be met to a great extent, and better user feedback can be obtained easily.
For example, the recommendation index corresponding to the target user may be 6.1, which is greater than the preset value of 4.5, so that the electronic device may push the content to be recommended to the target user, "day X, shanghai, singer, and ticket sales at concert with price Y".
In the embodiment of the invention, the electronic equipment can firstly acquire the content to be recommended and at least two target user images corresponding to target users, wherein different target user images respectively have different domain attributes, and the domain attributes of the target user images are associated with the domain attributes of the content to be recommended. Then, the electronic device can respectively determine a target weight coefficient corresponding to each target user portrait in at least two target user portraits, respectively determine a target preset condition which is met by user information under each dimension from each preset condition corresponding to each dimension in the target user portrait, further respectively determine a matching score corresponding to each target preset condition, and add the matching scores corresponding to each target preset condition in the same target user portrait to obtain a matching coefficient between each target user portrait and the content to be recommended. And then, determining a recommendation index corresponding to the target user according to the matching coefficient and the target weight coefficient corresponding to each target user portrait, and pushing the content to be recommended to the target user when the recommendation index meets a preset recommendation condition. In the embodiment of the invention, the electronic equipment can determine target user figures corresponding to different fields of a target user, and based on target weight coefficients corresponding to different target user figures, weighting and summing are carried out on matching coefficients between each target user figure and content to be recommended, so that a recommendation index corresponding to the target user is obtained, and further when the recommendation index meets a preset recommendation condition, the content to be recommended which is related to the fields of cross-fields and each target user figure can be pushed to the target user, so that personalized content recommendation can be carried out on the target user in a new field.
EXAMPLE III
Referring to fig. 3, a block diagram of a structure of an electronic device 300 according to a third embodiment of the present invention is shown, which may specifically include:
an obtaining module 301, configured to obtain content to be recommended and at least two target user figures corresponding to a target user; wherein different ones of the target user representations have different domain attributes, respectively;
specifically, the domain attribute of the target user portrait is associated with the domain attribute of the content to be recommended.
A first determining module 302, configured to determine target weight coefficients corresponding to the at least two target user figures and matching coefficients between the at least two target user figures and the content to be recommended, respectively;
a second determining module 303, configured to determine, according to a matching coefficient and a target weight coefficient corresponding to each of the target user figures, a recommendation index corresponding to the target user;
a pushing module 304, configured to push the content to be recommended to the target user when the recommendation index meets a preset recommendation condition.
Optionally, referring to fig. 4, each of the target user representations includes user information in at least one dimension; the first determining module 302 comprises:
a first determining submodule 3021, configured to determine a target weight coefficient corresponding to each target user portrait based on a correspondence between pre-stored user portraits and weight coefficients, respectively;
a second determining submodule 3022, configured to determine, for each dimension, a target preset condition that is met by the user information in the dimension from at least one preset condition corresponding to the dimension; each preset condition is set based on user information under a corresponding dimension and the content to be recommended;
a third determining submodule 3023, configured to determine a matching score corresponding to each of the target preset conditions;
a first adding sub-module 3024, configured to add matching scores corresponding to each of the target preset conditions in the same target user portrait to obtain a matching coefficient between each of the target user portrait and the content to be recommended.
Optionally, referring to fig. 4, the second determining module 303 includes:
a multiplication submodule 3031, configured to multiply a matching coefficient and a target weight coefficient that correspond to the same target user image, so as to obtain a recommended value corresponding to each target user image;
and the second adding submodule 3032 is configured to add the recommendation values corresponding to each target user image to obtain a recommendation index corresponding to the target user.
Optionally, referring to fig. 4, the electronic device 300 further includes:
a third determining module 305 for determining at least two initial weighting coefficients corresponding to each of the target user representation;
an adjusting module 306, configured to adjust the at least two initial weight coefficients according to an a/B test policy, to obtain a target weight coefficient;
and a storage module 307, configured to store a corresponding relationship between each target user portrait and each target weight coefficient.
Optionally, referring to fig. 4, the pushing module 304 includes:
a first pushing submodule 3041, configured to push the content to be recommended to the target user when the recommendation index is greater than or equal to a preset value;
and/or the presence of a gas in the atmosphere,
a second pushing submodule 3042, configured to, when the ranking of the recommendation indexes in the recommendation indexes corresponding to the respective preselected users is less than or equal to the preset ranking, pushing the content to be recommended to the target user; and the recommendation indexes corresponding to the preselected users are arranged in a descending order.
The electronic device provided in the embodiment of the present invention can implement each process implemented by the electronic device in the method embodiments of fig. 1 and fig. 2, and is not described herein again to avoid repetition.
In the embodiment of the invention, the electronic device can firstly obtain the content to be recommended and at least two target user figures corresponding to the target users through the obtaining module, wherein different target user figures respectively have different domain attributes, and the domain attributes of the target user figures are associated with the domain attributes of the content to be recommended. Then, the electronic equipment can respectively determine a target weight coefficient corresponding to each target user portrait in the at least two target user portraits and a matching coefficient between each target user portrait in the at least two target user portraits and the content to be recommended through the first determination module, can determine a recommendation index corresponding to the target user according to the matching coefficient and the target weight coefficient corresponding to each target user portrait through the second determination module, and can push the content to be recommended to the target user through the push module when the recommendation index meets a preset recommendation condition. In the embodiment of the invention, the electronic equipment can determine the target user figures corresponding to different fields of the target user, and determine whether to push the content to be recommended, which is related to the fields of the cross-field and the target user figures, to the target user based on the target weight coefficients corresponding to the different target user figures and the matching degree between each target user figure and the content to be recommended, so that the target user can be subjected to personalized content recommendation in a new field.
Example four
Figure 5 is a schematic diagram of a hardware configuration of an electronic device implementing various embodiments of the invention,
the electronic device 500 includes, but is not limited to: a radio frequency unit 501, a network module 502, an audio output unit 503, an input unit 504, a sensor 505, a display unit 506, a user input unit 507, an interface unit 508, a memory 509, a processor 510, and a power supply 511. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 5 does not constitute a limitation of the electronic device, and that the electronic device may include more or fewer components than shown, or some components may be combined, or a different arrangement of components. In the embodiment of the present invention, the electronic device includes, but is not limited to, a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle-mounted terminal, a wearable device, a pedometer, and the like.
The processor 510 is configured to obtain content to be recommended and at least two target user figures corresponding to a target user; wherein different target user portraits respectively have different domain attributes; respectively determining target weight coefficients corresponding to the at least two target user portraits and matching coefficients between the at least two target user portraits and the content to be recommended; determining a recommendation index corresponding to each target user according to the matching coefficient and the target weight coefficient corresponding to each target user portrait; and when the recommendation index meets a preset recommendation condition, pushing the content to be recommended to the target user.
In the embodiment of the invention, the electronic equipment can firstly acquire the content to be recommended and at least two target user images corresponding to target users, wherein different target user images respectively have different domain attributes, and the domain attributes of the target user images are associated with the domain attributes of the content to be recommended. Then the electronic equipment can respectively determine a target weight coefficient corresponding to each target user portrait in the at least two target user portraits and a matching coefficient between each target user portrait in the at least two target user portraits and the content to be recommended, determine a recommendation index corresponding to the target user according to the matching coefficient and the target weight coefficient corresponding to each target user portrait, and push the content to be recommended to the target user when the recommendation index meets a preset recommendation condition. In the embodiment of the invention, the electronic equipment can determine the target user figures corresponding to different fields of the target user, and determine whether to push the content to be recommended, which is related to the fields of the cross-field and the target user figures, to the target user based on the target weight coefficients corresponding to the different target user figures and the matching degree between each target user figure and the content to be recommended, so that the target user can be subjected to personalized content recommendation in a new field.
It should be understood that, in the embodiment of the present invention, the radio frequency unit 501 may be used for receiving and sending signals during a process of sending and receiving information or a call, and specifically, receives downlink data from a base station and then processes the downlink data to the processor 510; in addition, the uplink data is transmitted to the base station. In general, radio frequency unit 501 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like. In addition, the radio frequency unit 501 can also communicate with a network and other devices through a wireless communication system.
The electronic device provides wireless broadband internet access to the user via the network module 502, such as assisting the user in sending and receiving e-mails, browsing web pages, and accessing streaming media.
The audio output unit 503 may convert audio data received by the radio frequency unit 501 or the network module 502 or stored in the memory 509 into an audio signal and output as sound. Also, the audio output unit 503 may also provide audio output related to a specific function performed by the electronic apparatus 500 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 503 includes a speaker, a buzzer, a receiver, and the like.
The input unit 504 is used to receive audio or video signals. The input Unit 504 may include a Graphics Processing Unit (GPU) 5041 and a microphone 5042, and the Graphics processor 5041 processes image data of still pictures or video obtained by an image capturing device (such as a camera) in a video capture mode or an image capture mode. The processed image frames may be displayed on the display unit 506. The image frames processed by the graphics processor 5041 may be stored in the memory 509 (or other storage media) or transmitted via the radio frequency unit 501 or the network module 502. The microphone 5042 may receive sounds and may be capable of processing such sounds into audio data. The processed audio data may be converted into a format output transmittable to a mobile communication base station via the radio frequency unit 501 in case of the phone call mode.
The electronic device 500 also includes at least one sensor 505, such as light sensors, motion sensors, and other sensors. Specifically, the light sensor includes an ambient light sensor that can adjust the brightness of the display panel 5061 according to the brightness of ambient light, and a proximity sensor that can turn off the display panel 5061 and/or a backlight when the electronic device 500 is moved to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), detect the magnitude and direction of gravity when stationary, and can be used to identify the posture of the electronic device (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration identification related functions (such as pedometer, tapping), and the like; the sensor 505 may also include a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, etc., which will not be described in detail herein.
The display unit 506 is used to display information input by the user or information provided to the user. The Display unit 506 may include a Display panel 5061, and the Display panel 5061 may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like.
The user input unit 507 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device. Specifically, the user input unit 507 includes a touch panel 5071 and other input devices 5072. Touch panel 5071, also referred to as a touch screen, can collect touch operations by a user on or near it (e.g., operations by a user on or near touch panel 5071 using a finger, a stylus, or any other suitable object or attachment). The touch panel 5071 may include two parts of a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 510, receives a command from the processor 510, and executes the command. In addition, the touch panel 5071 may be implemented in various types such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. In addition to touch panel 5071, user input unit 507 may include other input devices 5072. Specifically, the other input devices 5072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which are not described herein.
Further, a touch panel 5071 may be overlaid on the display panel 5061, and when the touch panel 5071 detects a touch operation thereon or nearby, the touch operation is transmitted to the processor 510 to determine the type of the touch event, and then the processor 510 provides a corresponding visual output on the display panel 5061 according to the type of the touch event. Although in fig. 5, the touch panel 5071 and the display panel 5061 are two independent components to implement the input and output functions of the electronic device, in some embodiments, the touch panel 5071 and the display panel 5061 may be integrated to implement the input and output functions of the electronic device, which is not limited herein.
The interface unit 508 is an interface for connecting an external device to the electronic apparatus 500. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input/output (I/O) port, a video I/O port, an earphone port, and the like. The interface unit 508 may be used to receive input (e.g., data information, power, etc.) from external devices and transmit the received input to one or more elements within the electronic apparatus 500 or may be used to transmit data between the electronic apparatus 500 and external devices.
The memory 509 may be used to store software programs as well as various data. The memory 509 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 509 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device.
The processor 510 is a control center of the electronic device, connects various parts of the whole electronic device by using various interfaces and lines, performs various functions of the electronic device and processes data by running or executing software programs and/or modules stored in the memory 509 and calling data stored in the memory 509, thereby performing overall monitoring of the electronic device. Processor 510 may include one or more processing units; preferably, the processor 510 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into processor 510.
The electronic device 500 may further include a power supply 511 (e.g., a battery) for supplying power to various components, and preferably, the power supply 511 may be logically connected to the processor 510 via a power management system, so as to implement functions of managing charging, discharging, and power consumption via the power management system.
In addition, the electronic device 500 includes some functional modules that are not shown, and are not described in detail here.
Preferably, an embodiment of the present invention further provides an electronic device, which includes a processor 510, a memory 509, and a computer program that is stored in the memory 509 and can be run on the processor 510, and when the computer program is executed by the processor 510, the processes of the content recommendation method embodiment are implemented, and the same technical effect can be achieved, and in order to avoid repetition, details are not described here again.
The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements the processes of the content recommendation method embodiment, and can achieve the same technical effect, and in order to avoid repetition, the computer program is not described herein again. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a component of' 8230; \8230;" does not exclude the presence of another like element in a process, method, article, or apparatus that comprises the element.
Through the description of the foregoing embodiments, it is clear to those skilled in the art that the method of the foregoing embodiments may be implemented by software plus a necessary general hardware platform, and certainly may also be implemented by hardware, but in many cases, the former is a better implementation. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (8)
1. A content recommendation method applied to an electronic device is characterized by comprising the following steps:
acquiring content to be recommended and at least two target user figures corresponding to target users; wherein different target user representations respectively have different domain attributes, the domain attributes being used to characterize a domain to which features of the target user representation belong, each target user representation comprising user information of at least one dimension;
respectively determining target weight coefficients corresponding to the at least two target user portraits and matching coefficients between the at least two target user portraits and the content to be recommended;
determining a recommendation index corresponding to the target user according to the matching coefficient and the target weight coefficient corresponding to each target user portrait;
when the recommendation index meets a preset recommendation condition, pushing the content to be recommended to the target user;
the step of respectively determining the target weight coefficients corresponding to the at least two target user figures and the matching coefficients between the at least two target user figures and the content to be recommended includes:
respectively determining a target weight coefficient corresponding to each target user portrait based on the corresponding relation between the pre-stored user portrait and the weight coefficients;
for each dimension, determining a target preset condition met by user information in the dimension from at least one preset condition corresponding to the dimension; each preset condition is set based on user information under a corresponding dimension and the content to be recommended;
respectively determining a matching score corresponding to each target preset condition;
adding matching scores corresponding to each target preset condition in the same target user portrait to obtain a matching coefficient between each target user portrait and the content to be recommended;
before the step of determining the target weight coefficients corresponding to the at least two target user figures and the matching coefficients between the at least two target user figures and the content to be recommended respectively, the method further includes:
determining at least two initial weighting coefficients corresponding to each of the target user representation;
adjusting the at least two initial weight coefficients according to an A/B test strategy to obtain target weight coefficients;
and storing the corresponding relation between each target user portrait and each target weight coefficient.
2. The method of claim 1, wherein the step of determining the recommendation index corresponding to the target user based on the matching coefficient and the target weighting coefficient corresponding to each of the target user images comprises:
multiplying a matching coefficient corresponding to the same target user image by a target weight coefficient to obtain a recommendation value corresponding to each target user image;
and adding the recommendation values corresponding to the target user images to obtain a recommendation index corresponding to the target user.
3. The method according to claim 1, wherein the step of pushing the content to be recommended to the target user when the recommendation index satisfies a preset recommendation condition comprises:
when the recommendation index is larger than or equal to a preset value, pushing the content to be recommended to the target user;
and/or the presence of a gas in the atmosphere,
when the ranking of the recommendation index in the recommendation indexes corresponding to the preselected users is less than or equal to a preset ranking, pushing the content to be recommended to the target user; and the recommendation indexes corresponding to the preselected users are arranged in the descending order.
4. An electronic device, comprising:
the acquisition module is used for acquiring the content to be recommended and at least two target user figures corresponding to the target users; wherein different target user representations respectively have different domain attributes, the domain attributes being used to characterize a domain to which features of the target user representation belong, each target user representation comprising user information of at least one dimension;
the first determining module is used for respectively determining target weight coefficients corresponding to the at least two target user figures and matching coefficients between the at least two target user figures and the content to be recommended;
the second determining module is used for determining a recommendation index corresponding to the target user according to the matching coefficient and the target weight coefficient corresponding to each target user portrait;
the pushing module is used for pushing the content to be recommended to the target user when the recommendation index meets a preset recommendation condition;
the first determining module comprises:
the first determining submodule is used for respectively determining a target weight coefficient corresponding to each target user portrait based on the corresponding relation between the pre-stored user portrait and the weight coefficient;
the second determining submodule is used for determining a target preset condition which is met by the user information under each dimension from at least one preset condition corresponding to the dimension; each preset condition is set based on user information under a corresponding dimension and the content to be recommended;
a third determining submodule, configured to determine a matching score corresponding to each of the target preset conditions, respectively;
the first adding sub-module is used for adding matching scores corresponding to each target preset condition in the same target user portrait to obtain a matching coefficient between each target user portrait and the content to be recommended;
the electronic device further includes:
a third determining module for determining at least two initial weighting coefficients corresponding to each of the target user representations;
the adjusting module is used for adjusting the at least two initial weight coefficients according to an A/B test strategy to obtain a target weight coefficient;
and the storage module is used for storing the corresponding relation between each target user portrait and each target weight coefficient.
5. The electronic device of claim 4, wherein the second determining module comprises:
the multiplication submodule is used for multiplying the matching coefficient corresponding to the same target user image and the target weight coefficient to obtain a recommended value corresponding to each target user image;
and the second addition sub-module is used for adding the recommendation values corresponding to the target user images to obtain the recommendation indexes corresponding to the target users.
6. The electronic device of claim 4, wherein the push module comprises:
the first pushing submodule is used for pushing the content to be recommended to the target user when the recommendation index is larger than or equal to a preset value;
and/or the presence of a gas in the atmosphere,
the second pushing submodule is used for pushing the content to be recommended to the target user when the ranking of the recommendation indexes in the recommendation indexes corresponding to the preselected users is less than or equal to the preset ranking; and the recommendation indexes corresponding to the preselected users are arranged in the descending order.
7. An electronic device, comprising a processor, a memory and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the content recommendation method according to any one of claims 1 to 3.
8. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of a content recommendation method according to any one of claims 1 to 3.
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