CN112784159B - Content recommendation method and device, terminal equipment and computer readable storage medium - Google Patents
Content recommendation method and device, terminal equipment and computer readable storage medium Download PDFInfo
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Abstract
The application is applicable to the technical field of big data, and provides a content recommendation method, a content recommendation device, terminal equipment and a computer-readable storage medium, wherein the content recommendation method comprises the following steps: acquiring position intervals corresponding to different content types, wherein each position interval comprises at least one display position on a target platform; sequencing the first candidate content under the content type corresponding to each position interval according to the content click rate to obtain a first content sequence corresponding to the position interval; and determining the display content at each display position in the position interval according to the first content sequence corresponding to the position interval. By the method, the interested content can be accurately recommended to the user, and the user experience is improved.
Description
Technical Field
The present application belongs to the field of big data technologies, and in particular, to a content recommendation method, apparatus, terminal device, and computer-readable storage medium.
Background
With the development of internet technology, the internet can provide more and more network services for users, such as: a user may browse videos, listen to music, read, shop, etc. over the internet. In order to facilitate the user to obtain information, the internet platform can actively recommend content to the user. At present, the content recommendation methods adopted when recommending content to users are mainly classified recommendation methods and recommendation methods based on click rate.
The classification recommendation method is to classify the content according to the content category, and set a classification navigation bar containing different content categories in a recommendation page according to a classification result, wherein the classification navigation bar can recommend the content of different categories to a user. However, for the classification recommendation method, the content categories included in the classification navigation bar are fixed, the recommended content included in each content category is also fixed and unchangeable within a certain time, the user sees the same content category each time, and after a certain content category is opened, the recommended content included in the content category is repeatedly recommended to the user, so that the user is difficult to quickly find the really interested recommended content.
The recommendation method based on the click rate is to sort the recommended contents according to the order of the click rate from high to low and recommend the contents in the front to the user. In practical applications, a certain content type may be concentrated to the front, for example, a video may have a high click rate, which may result in that the head recommendation bit in the content recommendation list is all video.
Therefore, the existing content recommendation method is low in intelligentization degree and poor in recommendation effect, and user experience is affected.
Disclosure of Invention
The embodiment of the application provides a content recommendation method and device, a terminal device and a computer readable storage medium, which can accurately recommend interesting content to a user and improve user experience.
In a first aspect, an embodiment of the present application provides a content recommendation method, including:
acquiring position intervals corresponding to different content types, wherein each position interval comprises at least one display position on a target platform;
sequencing the first candidate content under the content type corresponding to each position interval according to the content click rate to obtain a first content sequence corresponding to the position interval;
and determining the display content at each display position in the position interval according to the first content sequence corresponding to the position interval.
In the embodiment of the application, position intervals corresponding to different content types are obtained, which is equivalent to allocating a rough position range for each content type, so as to ensure that the contents of various content types can participate in sequencing; and then distributing content to each display position in each position interval according to the content click rate, so that the display positions are 'competed' among the first candidate contents according to the content click rate, and the displayed contents are ensured to accord with the reading preference of a user. By the method, the content under each content type can be displayed on the premise of meeting the reading preference of the user, the situation that the content of a certain type occupies all display positions is avoided, and the reading experience of the user is improved.
In a possible implementation manner of the first aspect, the obtaining the position intervals corresponding to the different content types includes:
assigning at least one of the content types to each of the presentation locations on the target platform;
and dividing the display positions of the distributed content types into a plurality of non-overlapping position intervals according to the content types and preset division rules respectively corresponding to each display position.
In a possible implementation manner of the first aspect, the preset partition rule includes:
for any two adjacent display positions, if the content types corresponding to the two adjacent display positions are the same, dividing the two adjacent display positions into the same position interval;
and if the content types corresponding to the two adjacent display positions are different, dividing the two adjacent display positions into different position intervals.
In a possible implementation manner of the first aspect, the content recommendation method includes:
for any one content type, obtaining a sorting parameter of the content type, wherein the sorting parameter comprises a maximum exposure number and a minimum exposure number;
when the number of the vacant display positions corresponding to the content type is equal to the minimum exposure number in the sorting parameter of the content type, allocating a second candidate content under the content type to the vacant display positions corresponding to the content type according to a content click rate, wherein the second candidate content under the content type is a content which is not displayed in the first candidate content under the content type.
In a possible implementation manner of the first aspect, the content recommendation method includes:
for any one content type, obtaining a sorting parameter of the content type, wherein the sorting parameter comprises a maximum exposure number and a minimum exposure number;
when the number of occupied display positions corresponding to the content type is equal to the maximum exposure number in the sorting parameter of the content type, stopping distributing display positions for second candidate content under the content type, wherein the second candidate content under the content type is content which is not displayed in the first candidate content under the content type.
In a possible implementation manner of the first aspect, the content recommendation method further includes:
acquiring historical data corresponding to a tth time period, wherein the historical data comprises content types to which contents of operations executed on the target platform by a user before the tth time period belong;
determining a data volume ratio between the different content types according to the historical data;
and adjusting the respective sorting parameters of the different content types in the t-th time period according to the data volume ratio and a preset floating number.
In a second aspect, an embodiment of the present application provides a content recommendation apparatus, including:
the device comprises an acquisition unit, a display unit and a display unit, wherein the acquisition unit is used for acquiring position intervals corresponding to different content types, and each position interval comprises at least one display position on a target platform;
the sorting unit is used for sorting the first candidate content under the content type corresponding to each position interval according to the content click rate to obtain a first content sequence corresponding to the position interval;
and the display unit is used for determining the display content at each display position in the position interval according to the first content sequence corresponding to the position interval.
In a third aspect, an embodiment of the present application provides a terminal device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the computer program to implement the content recommendation method according to any one of the above first aspects.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, and the embodiment of the present application provides a computer-readable storage medium, where a computer program is stored, where the computer program, when executed by a processor, implements the content recommendation method according to any one of the first aspect.
In a fifth aspect, an embodiment of the present application provides a computer program product, which, when run on a terminal device, causes the terminal device to execute the content recommendation method according to any one of the first aspect.
It is understood that the beneficial effects of the second aspect to the fifth aspect can be referred to the related description of the first aspect, and are not described herein again.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of a content recommendation method provided in an embodiment of the present application;
fig. 2 is a flowchart illustrating a content recommendation method according to another embodiment of the present application;
fig. 3 is a block diagram of a content recommendation apparatus according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, 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.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection".
Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather mean "one or more but not all embodiments" unless specifically stated otherwise.
First, the technical background of content recommendation is described. In the existing content recommendation method, candidate contents are generally sorted according to the content click rate to obtain a content queue; and then sequentially placing the candidate contents in the content queue at each showing position. For example: and obtaining 3 candidate contents A (the content click rate is 0.8), B (the content click rate is 0.9) and C (the content click rate is 0.3), and obtaining ase:Sub>A content sequence B-A-C according to the content click rate. Assuming 2 display positions, then B is placed in the first display position and a is placed in the second display position.
In practical applications, the content of a certain content type has a high "competitive" property because the click rate of the content is high. According to the existing content recommendation method, the content of the content type occupies most of the display positions in the sorting process, and the content of the content type with a low click rate may not be displayed. For example, a video will generally have a higher click through rate, which may result in the head recommendation bits being all video in the content queue obtained from the content click through rate.
In order to solve the above problem, an embodiment of the present application provides a content recommendation method. In the embodiment of the application, the display position is divided into position intervals, and the display intervals are distributed for different content types; then, each presentation interval is processed respectively, namely, each content type is subjected to competition according to the click rate in each presentation interval. By the method in the embodiment of the application, the situation that all content types compete for a certain display position at the same time is avoided, the competition is separated according to the position interval, the content of different content types can be displayed, and the situation that the content of a certain content type occupies all display positions is avoided.
The content recommendation method provided by the embodiment of the application can be executed by a processor of the target platform, and can also be executed by a processor of a content recommendation system for providing content recommendation service for the target platform. In an application scenario, a processor executing the content recommendation method provided by the embodiment of the application acquires respective corresponding position intervals of different content types on a target platform; then, ordering the first candidate content under the content type corresponding to each position interval according to the content click rate to obtain a first content sequence corresponding to the position interval; and then, according to the first content sequence corresponding to the position interval, determining the display content at each display position in the position interval, and displaying the display contents to the user through a foreground interface of the target platform.
The content recommendation method provided by the embodiment of the application is described below. Fig. 1 is a schematic flow chart of a content recommendation method provided in an embodiment of the present application. By way of example and not limitation, as shown in fig. 1, the content recommendation method may include the steps of:
s101, acquiring position intervals corresponding to different content types.
Wherein each position interval comprises at least one display position on the target platform. Each content type may correspond to one or more location intervals.
In addition, in order to determine the recommended content at each presentation position on the target platform, the sum of the ranges of the respective position intervals needs to cover all the presentation positions on the target platform. For example: the target platform has 20 display positions, and the position intervals are [1-5], [3-16] and [17-20] respectively. In this case, the sum of the ranges of the three location intervals may cover 20 presentation locations on the target platform.
The platform in the embodiment of the application refers to an information platform, such as a website and an application program, which can recommend content for a user and enable the user to search information by himself. The target platform refers to an information platform which needs to recommend content for a user. For example, a certain news website is an information platform, and when it is necessary to recommend content to a user on the news website by using the content recommendation method provided in the embodiment of the present application, the news website is a target platform in the embodiment of the present application.
In embodiments of the present application, the content type may include advertisements, albums, videos, cartoons, hotspots, and the like. May be the type of content that needs to be exposed on the target platform. Because the content provided by different target platforms is different, the content types can be divided according to actual needs, and are not specifically limited herein.
In one embodiment, the position interval may be obtained by the following steps:
assigning at least one content type to each presentation location on the target platform; and dividing the display positions of the distributed content types into a plurality of non-overlapping position intervals according to the content types and preset division rules respectively corresponding to each display position.
Optionally, the preset partition rule includes:
for any two adjacent display positions, if the content types corresponding to the two adjacent display positions are the same, dividing the two adjacent display positions into the same position interval.
And if the content types corresponding to the two adjacent display positions are different, dividing the two adjacent display positions into different position intervals.
For example, assume that the content types are albums, videos, and advertisements. Wherein, the content type distributed for the display positions 1-20 is an atlas, the content type distributed for the display positions 3-10 is a video, and the content type distributed for the display positions 7-12 is an advertisement. It can be seen that the display positions 1-2 can only display the atlas, 3-6 can display the atlas and the video (the content type corresponding to the display position 2 is different from the content type corresponding to the display position 3), 7-10 can display the atlas, the video and the advertisement (the content type corresponding to the display position 6 is different from the content type corresponding to the display position 7), 11-12 can display the advertisement and the atlas (the content type corresponding to the display position 10 is different from the content type corresponding to the display position 11), and 13-20 can display the atlas (the content type corresponding to the display position 12 is different from the content type corresponding to the display position 13). Then 1-20 display positions are divided into 5 non-overlapping position intervals of [1-2], [3-6], [7-10], [11-12], and [13-20] according to the content types respectively corresponding to the display positions and the preset division rule, and the sum of the ranges of the 5 position intervals can cover 20 display positions.
By the method, the disordered display positions can be ordered, so that each position interval and the content type form a clear mapping.
S102, sequencing the first candidate content under the content type corresponding to each position interval according to the content click rate, and obtaining a first content sequence corresponding to the position interval.
In the embodiment of the present application, the first candidate content in content type I refers to content that belongs to content type I and is not shown (i.e., is not assigned a showing position). When content recommendation is required according to the search keyword of the user, the first candidate content under the content type I refers to the content which is in line with the search keyword, belongs to the content type I and is not displayed. For example: the user inputs a search keyword "rabbit", the candidate content under the content type "atlas" is a picture containing or related to rabbits, and the candidate content under the content type "video" is a video containing or related to rabbits.
The processor executing the content recommendation method in the embodiment of the application acquires the first candidate content under the content type from the database corresponding to the target platform and sorts the first candidate content.
The database corresponding to the target platform can be a database of the target platform, can also be a third-party database such as a cloud storage space, and can also be a database of other information platforms performing data interaction with the target platform.
For the database of the target platform, when content is added to the database, each piece of added content needs to be subjected to security inspection, then a content tag is established for each piece of content, and finally the content and the content tag thereof are stored in the database. In this way, when executing step S102, the processor may determine the content in the database corresponding to the content tag matching the content type I as the first candidate content under the content type I.
The content click rate refers to the ratio of the number of times a piece of content on a web page is clicked to the number of times it is displayed. Reflecting the attention degree of a certain piece of content on the webpage.
Optionally, the first candidate content under the content type corresponding to each position interval may be sorted in the order from high to low in the content click rate.
As illustrated in the example of S101, one location interval may correspond to a plurality of content types. In this case, the first candidate contents of the plurality of content types corresponding to the position section are sorted together, and the first candidate contents corresponding to different content types "compete".
For example, assume that the content types corresponding to the location interval [3-6] are an atlas and a video, the first candidate contents under the atlas include a (content click rate is 0.3) and b (content click rate is 0.5), and the first candidate contents under the video include c (content click rate is 0.8), d (content click rate is 0.2), and e (content click rate is 0.6). Then the first content sequence corresponding to the position interval 3-6 is c-e-b-a-d.
S103, determining the display content at each display position in the position interval according to the first content sequence corresponding to the position interval.
When the first content sequence is obtained according to the content click-through rate from the large to the small, the content in the first content sequence may be sequentially assigned to the respective presentation positions in the order from the front to the back of the first content sequence.
In the embodiment of the present application, when the content x is assigned to the presentation position y, the content x is recorded as the presentation content at the presentation position y.
Continuing with the example in S102, the first content sequence corresponding to location interval [3-6] is c-e-b-a-d. Since there are 4 presentation positions in the position interval, which are 3, 4, 5, and 6, the first 4 pieces of content in the first content sequence are sequentially assigned to the 4 presentation positions. Specifically, c is assigned to 3, e is assigned to 4, b is assigned to 5, and a is assigned to 6. Wherein, the allocated 4 pieces of content c, e, b and a are the display content.
In the embodiment of the application, position intervals corresponding to different content types are obtained, which is equivalent to allocating a rough position range for each content type, so as to ensure that the contents of various content types can participate in sequencing; and then distributing content to each display position in each position interval according to the content click rate, so that the display positions are 'competed' among the first candidate contents according to the content click rate, and the displayed content is ensured to accord with the reading preference of a user. By the method, the content under each content type can be displayed on the premise of meeting the reading preference of the user, the situation that the content of a certain type occupies all display positions is avoided, and the reading experience of the user is improved.
In practical applications, since the click rate of a content of a certain content type is high, the "competitiveness" of the content type is strong, so that the content of the content type occupies most of the display positions in the sorting process, and the content of the content type with a low click rate may not be displayed.
In order to solve the above problem, in an embodiment, referring to fig. 2, a flowchart of a content recommendation method according to another embodiment of the present application is shown. By way of example and not limitation, as shown in fig. 2, the content recommendation method may further include the steps of:
s201, for any content type, obtaining the sequencing parameter of the content type.
The sorting parameters include a maximum exposure number and a minimum exposure number. The maximum exposure number is used to limit the maximum number of times that the content of each content type is allowed to be presented in one content recommendation process, i.e. at most several presentation positions can be occupied. The minimum exposure number is used to limit the minimum number of times that the content of each content type is allowed to be presented in one content recommendation process, i.e. the minimum number of presentation positions needs to be occupied.
S202, when the number of the vacant display positions corresponding to the content type is equal to the minimum exposure number in the sorting parameter of the content type, distributing the second candidate content under the content type to the vacant display positions corresponding to the content type according to the content click rate.
And S203, when the number of occupied display positions corresponding to the content type is equal to the maximum exposure number in the sequencing parameter of the content type, stopping distributing the display positions for the second candidate content under the content type.
The second candidate content under the content type I is the content which is not displayed in the first candidate content under the content type I when the number of the vacant display positions corresponding to the content type I is equal to the minimum exposure number corresponding to the content type I or when the number of the occupied display positions corresponding to the content type I is equal to the maximum exposure number corresponding to the content type I. For example: the first candidate content under content type I has a, b, c. When the number of the vacant display positions corresponding to the content type I is equal to the minimum exposure number corresponding to the content type I, or when the number of the occupied display positions corresponding to the content type I is equal to the maximum exposure number corresponding to the content type I, a is already allocated to the display position 1, namely a is already displayed, and b and c are not allocated, namely b and c are not displayed contents. So, the second candidate contents under content type I at this time are b and c.
The steps in S202 and S203 are explained below using an example.
Suppose that the display interval [1-2] can only display the atlas, the display interval [3-4] can display the video, and the display interval [5-6] can display the atlas and the video.
First, contents are assigned to the presentation positions in the presentation interval [1-2 ]. Assume that the first content sequence corresponding to the presentation interval [1-2] is a-b-c-d (i.e., a, b, c, and d are the first candidates under the atlas). Since there are only 2 display positions, i.e. a is assigned to display position 1 and b is assigned to display position 2. The remaining c and d are the second candidates in the atlas.
And then distributing the content to the display position in the display interval [3-4 ]. Assume that the first content sequence corresponding to the presentation interval [3-4] is e-f-g-h (i.e., a, b, c, and d are the first candidate content under the video). Since there are only 2 display positions, i.e. e to display position 3 and f to display position 4. And g and h are the second candidate content in the video.
And finally distributing the content to the display position in the display interval [5-6 ]. Suppose that the first content sequence corresponding to the presentation interval [5-6] is c-d-g-h, and the maximum exposure number 3 and the minimum exposure number of the atlas is 1, and the maximum exposure number of the video is 4 and the minimum exposure number is 1. The second candidate content c under the album is assigned to the presentation position 5 on the assumption described above. At this time, if there are 1, 2, 5, that is, 3 occupied display positions corresponding to the atlas, which is equal to the maximum exposure number of the atlas, the allocation of the display position for the second candidate content d under the atlas is stopped, so that the content d under the atlas is no longer allocated to the display position 6. At this time, the number of the vacant display positions (only 6) corresponding to the video is equal to 1, namely, the number of the vacant display positions is equal to the minimum exposure number of the video; therefore, the second candidate content g under the video is assigned to the presentation position 6 according to the content click-through rate.
In practical applications, in order to allocate the positions in order, the contents are usually allocated to the presentation positions in order from front to back.
By the method in the embodiment of the application, the contents of various content types can be effectively guaranteed to be displayed, and the distribution ordering of the display positions can be guaranteed.
In the solution described in the above embodiment, the location interval and the sorting parameter corresponding to each content type are fixed, and cannot be adjusted in real time according to the preference of the user.
In order to solve the above problem, in one embodiment, the content recommendation method may further include the steps of:
acquiring historical data corresponding to the t-th time period; determining a data volume ratio between different content types according to historical data; and adjusting respective sorting parameters of different content types in the t-th time period according to the data volume ratio and the preset floating number.
The history data includes content types to which the content of the operation performed by the user on the target platform before the t-th time period belongs. For example, the history data may include the content of the operation performed by the user in L time periods before the t-th time period and the content type thereof. The history data may also include H pieces of content that the user has operated most recently before the t-th time and the content type thereof. In other words, the history data may be acquired by time or by number.
The time period may be preset according to actual needs, for example, 1 time period may be 1 day, 1 hour, 1 week, 1 month, and the like. When a smaller time period is adopted, the adjustment frequency of the sequencing parameters is higher; otherwise, the adjustment frequency of the sequencing parameters is lower.
By changing the time period, the frequency of adjusting the sequencing parameters can be controlled, and the sequencing parameters can be flexibly adjusted according to actual needs, so that the content recommendation scheme in the application has stronger applicability.
The data volume ratio in the embodiment of the present application refers to a ratio of the number of times that a user performs an operation on content of different content types. Illustratively, the user clicks 3 pieces of content in L time periods before the t-th time period, wherein the content type of 2 pieces of content is video, and the content type of 1 piece of content is an atlas. Thus, the ratio of the amount of data for video to the atlas is 2:1.
Continuing with the above example, assuming that the preset floating number is 3, the maximum exposure number of the video is increased by 2 and the maximum exposure number of the atlas is increased by 1 according to the data amount ratio 2:1 of the video and the atlas.
For the content types not contained in the historical data, the sorting parameters can be kept unchanged, and the maximum exposure number can be correspondingly reduced according to the preset floating number.
By the method in the embodiment of the application, the sequencing parameters can be adjusted in real time, so that the sequencing result can follow the interest and preference of the user in real time.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Fig. 3 is a block diagram of a content recommendation apparatus according to an embodiment of the present application, which corresponds to the content recommendation method according to the foregoing embodiment, and only shows relevant portions according to the embodiment of the present application for convenience of description.
Referring to fig. 3, the apparatus includes:
an obtaining unit 31, configured to obtain location intervals corresponding to different content types, where each location interval includes at least one display location on the target platform.
And the sorting unit 32 is configured to sort, according to the content click rate, the first candidate content in the content type corresponding to each position interval, and obtain a first content sequence corresponding to the position interval.
The display unit 33 is configured to determine, according to the first content sequence corresponding to the position interval, display content at each display position in the position interval.
Optionally, the obtaining unit 31 is further configured to:
assigning at least one of said content types to each of said presentation locations on said target platform; and dividing the display positions of the distributed content types into a plurality of non-overlapping position intervals according to the content types and preset division rules respectively corresponding to each display position.
Optionally, the preset partition rule includes:
for any two adjacent display positions, if the content types corresponding to the two adjacent display positions are the same, dividing the two adjacent display positions into the same position interval; and if the content types corresponding to the two adjacent display positions are different, dividing the two adjacent display positions into different position intervals.
Optionally, the apparatus 3 further comprises:
a parameter obtaining unit, configured to obtain, for any one of the content types, a ranking parameter of the content type, where the ranking parameter includes a maximum exposure number and a minimum exposure number.
A first allocating unit, configured to allocate, according to a content click through rate, a second candidate content in the content type to the vacant display position corresponding to the content type when the number of the vacant display positions corresponding to the content type is equal to the minimum exposure number in the sorting parameter of the content type.
A second allocating unit, configured to stop allocating a presentation position to a second candidate content in the content type when the number of occupied presentation positions corresponding to the content type is equal to the maximum exposure number in the ranking parameter of the content type.
Wherein the second candidate content in the content type is content that is not shown in the first candidate content in the content type.
Optionally, the apparatus 3 further comprises:
the history data acquisition unit is used for acquiring history data corresponding to a t-th time period, wherein the history data comprises a content type to which the content operated by the user on the target platform before the t-th time period belongs.
And the ratio calculating unit is used for determining the data quantity ratio between the different content types according to the historical data.
And the parameter adjusting unit is used for adjusting the respective sorting parameters of the different content types in the t-th time period according to the data volume ratio and a preset floating number.
It should be noted that, for the information interaction, execution process, and other contents between the above-mentioned devices/units, the specific functions and technical effects thereof are based on the same concept as those of the embodiment of the method of the present application, and specific reference may be made to the part of the embodiment of the method, which is not described herein again.
The content recommendation apparatus shown in fig. 3 may be a software unit, a hardware unit, or a combination of software and hardware unit built in the existing terminal device, may be integrated into the terminal device as a separate pendant, or may exist as a separate terminal device.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. For the specific working processes of the units and modules in the system, reference may be made to the corresponding processes in the foregoing method embodiments, which are not described herein again.
Fig. 4 is a schematic structural diagram of a terminal device according to an embodiment of the present application. As shown in fig. 4, the terminal device 4 of this embodiment includes: at least one processor 40 (only one shown in fig. 4), a memory 41, and a computer program 42 stored in the memory 41 and executable on the at least one processor 40, the processor 40 implementing the steps in any of the various content recommendation method embodiments described above when executing the computer program 42.
The terminal device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The terminal device may include, but is not limited to, a processor, a memory. Those skilled in the art will appreciate that fig. 4 is merely an example of the terminal device 4, and does not constitute a limitation of the terminal device 4, and may include more or less components than those shown, or combine some components, or different components, such as an input-output device, a network access device, and the like.
The Processor 40 may be a Central Processing Unit (CPU), and the Processor 40 may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 41 may in some embodiments be an internal storage unit of the terminal device 4, such as a hard disk or a memory of the terminal device 4. The memory 41 may also be an external storage device of the terminal device 4 in other embodiments, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like provided on the terminal device 4. Further, the memory 41 may also include both an internal storage unit and an external storage device of the terminal device 4. The memory 41 is used for storing an operating system, an application program, a BootLoader (BootLoader), data, and other programs, such as program codes of the computer program. The memory 41 may also be used to temporarily store data that has been output or is to be output.
The embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the steps in the above-mentioned method embodiments.
The embodiments of the present application provide a computer program product, which when running on a terminal device, enables the terminal device to implement the steps in the above method embodiments when executed.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above may be implemented by instructing relevant hardware by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the embodiments of the methods described above may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to an apparatus/terminal device, recording medium, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier signals, telecommunications signals, and software distribution medium. Such as a usb-drive, a removable hard drive, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (8)
1. A content recommendation method, comprising:
acquiring position intervals corresponding to different content types, wherein each position interval comprises at least one display position on a target platform;
sequencing the first candidate content under the content type corresponding to each position interval according to the content click rate to obtain a first content sequence corresponding to the position interval;
determining the display content at each display position in the position interval according to the first content sequence corresponding to the position interval;
the content recommendation method comprises the following steps:
for any one content type, obtaining a sorting parameter of the content type, wherein the sorting parameter comprises a maximum exposure number and a minimum exposure number;
when the number of the vacant display positions corresponding to the content type is equal to the minimum exposure number in the sorting parameter of the content type, allocating a second candidate content under the content type to the vacant display positions corresponding to the content type according to a content click rate, wherein the second candidate content under the content type is a content which is not displayed in the first candidate content under the content type;
when the number of occupied display positions corresponding to the content type is equal to the maximum exposure number in the sorting parameter of the content type, stopping distributing display positions for second candidate contents under the content type, wherein the second candidate contents under the content type are contents which are not displayed in the first candidate contents under the content type;
the maximum exposure number is used for limiting the maximum number of times that the content of each content type is allowed to be displayed in one content recommendation process, and the minimum exposure number is used for limiting the minimum number of times that the content of each content type is allowed to be displayed in one content recommendation process.
2. The content recommendation method according to claim 1, wherein said obtaining the location intervals corresponding to the different content types comprises:
assigning at least one of said content types to each of said presentation locations on said target platform;
and dividing the display positions of the distributed content types into a plurality of non-overlapping position intervals according to the content types and preset division rules respectively corresponding to the display positions.
3. The content recommendation method according to claim 2, wherein the preset division rule comprises:
for any two adjacent display positions, if the content types corresponding to the two adjacent display positions are the same, dividing the two adjacent display positions into the same position interval;
and if the content types corresponding to the two adjacent display positions are different, dividing the two adjacent display positions into different position intervals.
4. The content recommendation method according to claim 1, wherein the content recommendation method further comprises:
acquiring historical data corresponding to a tth time period, wherein the historical data comprises content types to which contents of operations executed on the target platform by a user before the tth time period belong;
determining a data volume ratio between the different content types according to the historical data;
and adjusting the respective sorting parameters of the different content types in the t-th time period according to the data volume ratio and a preset floating number.
5. A content recommendation apparatus characterized by comprising:
the device comprises an acquisition unit, a display unit and a display unit, wherein the acquisition unit is used for acquiring position intervals corresponding to different content types, and each position interval comprises at least one display position on a target platform;
the sorting unit is used for sorting the first candidate content under the content type corresponding to each position interval according to the content click rate to obtain a first content sequence corresponding to the position interval;
the display unit is used for determining display content at each display position in the position interval according to the first content sequence corresponding to the position interval;
a parameter obtaining unit, configured to obtain, for any one of the content types, a ranking parameter of the content type, where the ranking parameter includes a maximum exposure number and a minimum exposure number;
a first allocation unit, configured to, when the number of the vacant display positions corresponding to the content type is equal to the minimum exposure number in the sorting parameter of the content type, allocate a second candidate content in the content type to the vacant display positions corresponding to the content type according to a content click rate;
a second allocating unit, configured to stop allocating a presentation position to a second candidate content in the content type when the number of occupied presentation positions corresponding to the content type is equal to the maximum exposure number in the ranking parameter of the content type;
the maximum exposure number is used for limiting the maximum number of times that the content of each content type is allowed to be shown in one content recommendation process, and the minimum exposure number is used for limiting the minimum number of times that the content of each content type is allowed to be shown in one content recommendation process.
6. The content recommendation device of claim 5, wherein the obtaining unit is further configured to:
assigning at least one of said content types to each of said presentation locations on said target platform;
and dividing the display positions of the distributed content types into a plurality of non-overlapping position intervals according to the content types and preset division rules respectively corresponding to each display position.
7. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 4 when executing the computer program.
8. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 4.
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| CN116911957B (en) * | 2023-09-12 | 2024-01-05 | 深圳须弥云图空间科技有限公司 | Heterogeneous content mixed recommendation method, device, system and storage medium |
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