CN113365148B - Score adjustment method, score adjustment device, electronic device, storage medium, and program product - Google Patents
Score adjustment method, score adjustment device, electronic device, storage medium, and program product Download PDFInfo
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- CN113365148B CN113365148B CN202110653787.1A CN202110653787A CN113365148B CN 113365148 B CN113365148 B CN 113365148B CN 202110653787 A CN202110653787 A CN 202110653787A CN 113365148 B CN113365148 B CN 113365148B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
- H04N21/44204—Monitoring of content usage, e.g. the number of times a movie has been viewed, copied or the amount which has been watched
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
- H04N21/4508—Management of client data or end-user data
- H04N21/4532—Management of client data or end-user data involving end-user characteristics, e.g. viewer profile, preferences
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
- H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
- H04N21/4668—Learning process for intelligent management, e.g. learning user preferences for recommending movies for recommending content, e.g. movies
Abstract
The disclosure provides a score adjustment method, a score adjustment device, electronic equipment, a storage medium and a program product, and relates to the field of media resource recommendation and the field of live broadcast, in particular to the field of video live broadcast recommendation. The method comprises the following steps: determining a set of consecutive unselected times associated with a set of categories that the candidate media asset has; and decreasing the score of the candidate media asset if at least one consecutive number of non-selections in the set of consecutive numbers of non-selections is greater than the associated at least one consecutive threshold number of non-selections. By the method, the scores of the media resources can be adjusted by utilizing the display history of the media resources and the selection playing history of the media resources by the user so as to reflect the interest of the user on the media resources, so that the display of the media resources to the user can be adjusted, and the user experience of the user when the user watches the media resources can be further improved.
Description
Technical Field
The present disclosure relates to computer technologies, and more particularly, to a score adjustment method, a score adjustment apparatus, an electronic device, a computer-readable storage medium, and a computer program product, which may be used in the fields of media resource recommendation, live broadcast, and the like, and particularly may be used in the fields of video live broadcast recommendation, and the like.
Background
With the development of the internet, the field of media resource recommendation has also been rapidly developed. Live services, such as video live services, are one type of media resource recommendation service. In a live service, a user enters a live channel, and a recommendation system recommends a live list of interest to the user. The real-time watching and clicking interest preferences of the users on different live broadcasts are different, so that the recommendation system needs to recommend different live broadcast resources to different users in real time so as to meet the real-time personal requirements of different users.
The traditional application recommendation algorithm can recommend live broadcast meeting the user interest to the user according to the historical behavior and real-time behavior of the user and the characteristics of showing live broadcast resources. However, the recommendation system is prone to generate pre-estimated deviations from the real-time interest preferences of the user, and is further prone to continuously derive live broadcasts that do not match the real interest preferences of the user. In this case, live broadcasts that do not meet the user interest preference in live broadcast resources need to be adjusted as soon as possible, and sometimes these live broadcasts need to be taken out of the field. However, the conventional product for determining the real-time interest of the user has great limitations, so that it is difficult to determine the real-time interest of the user in time, and thus, live broadcasts meeting the interest requirements of the user cannot be recommended to the user in real time, which may affect the user experience when the user watches media resources.
Disclosure of Invention
According to an embodiment of the present disclosure, a score adjusting method, a score adjusting apparatus, an electronic device, a computer-readable storage medium, and a computer program product are provided.
In a first aspect of the present disclosure, there is provided a score adjustment method including: determining a set of consecutive unselected times associated with the set of categories that the candidate media asset has, the consecutive unselected times in the set of consecutive unselected times indicating consecutive times that media assets of the category associated with the consecutive unselected times are presented without being selected for play; and decreasing the score of the candidate media asset if at least one consecutive number of non-selections in the set of consecutive numbers of times of non-selections is greater than the associated at least one threshold number of consecutive times of non-selections.
In a second aspect of the present disclosure, there is provided a score adjusting apparatus including: a consecutive unselected times set determination module configured to determine a consecutive unselected times set associated with a category set that the candidate media resource has, the consecutive unselected times in the consecutive unselected times set indicating consecutive times at which media resources of a category associated with the consecutive unselected times are presented without being selected for play; and a first score reduction module configured to reduce the score of the candidate media asset if at least one consecutive number of non-selections in the set of consecutive numbers of non-selections is greater than the associated at least one consecutive threshold number of non-selections.
In a third aspect of the present disclosure, an electronic device is provided, comprising at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to implement a method according to the first aspect of the disclosure.
In a fourth aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to implement a method according to the first aspect of the present disclosure.
In a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program which, when executed by a processor, performs the method according to the first aspect of the present disclosure.
By utilizing the technology according to the application, a score adjusting method is provided, and by utilizing the method, the scores of the media resources can be adjusted by utilizing the display history of the media resources and the selection playing history of the media resources by the user so as to reflect the interest of the user in the media resources, so that the display of the media resources to the user can be adjusted, and the user experience of the user when watching the media resources can be further improved.
It should be understood that the statements herein reciting aspects are not intended to limit the critical or essential features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The foregoing and other objects, features and advantages of the disclosure will be apparent from the following more particular descriptions of exemplary embodiments of the disclosure as illustrated in the accompanying drawings wherein like reference numbers generally represent like parts throughout the exemplary embodiments of the disclosure. It should be understood that the drawings are for a better understanding of the present solution and do not constitute a limitation of the present disclosure. Wherein:
FIG. 1 illustrates a schematic block diagram of a score adjustment environment 100 in which a score adjustment method in certain embodiments of the present disclosure may be implemented;
FIG. 2 illustrates a flow diagram of a score adjustment method 200 according to an embodiment of the present disclosure;
FIG. 3 shows a flow diagram of a score adjustment method 300 according to an embodiment of the present disclosure;
FIG. 4 illustrates a schematic diagram of a media asset presentation comparison 400, in accordance with an embodiment of the present disclosure;
fig. 5 shows a schematic block diagram of a score adjustment apparatus 500 according to an embodiment of the present disclosure; and
FIG. 6 illustrates a schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure.
Like or corresponding reference characters designate like or corresponding parts throughout the several views.
Detailed Description
Preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The term "including" and variations thereof as used herein is intended to be open-ended, i.e., "including but not limited to". Unless specifically stated otherwise, the term "or" means "and/or". The term "based on" means "based at least in part on". The terms "one example embodiment" and "one embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first," "second," and the like may refer to different or the same object. Other explicit and implicit definitions are also possible below.
As described in the background art, the conventional product for determining the real-time interest of the user has great limitations, so that it is difficult to determine the real-time interest of the user in time, and therefore, the live broadcast meeting the interest requirement of the user cannot be recommended to the user in real time, which may affect the user experience when the user watches media resources.
For example, the existing live recommendation system has the following disadvantages in the exploration of real-time interests of users: firstly, the existing live broadcast recommendation system relies on a model to learn the real-time interest of a user, and the model acquires a behavior characteristic increment training model of the user on a live broadcast channel page in a short time, but the feedback period of the model is usually longer, so that the interest change of the user cannot be learned in time; in addition, the existing live broadcast recommendation system lacks an effective right-reducing and backtracking mechanism for live broadcast resources, so that the live broadcast resources of the same category are excessively shown to users, and the diversity of personalized live broadcast resources is weak; moreover, the existing live recommendation system lacks of exploring diversity of user interests, so that the user experience is poor.
In order to at least partially solve one or more of the above problems and other potential problems, embodiments of the present disclosure provide a score adjustment method, by which scores of media resources can be adjusted by using a presentation history of the media resources and a selection play history of the media resources by a user to reflect interests of the user in the media resources, so that the presentation of the media resources to the user can be adjusted, and user experience of the user when the user watches the media resources can be improved.
Fig. 1 illustrates a schematic block diagram of a score adjustment environment 100 in which a score adjustment method in certain embodiments of the present disclosure may be implemented. According to one or more embodiments of the present disclosure, the score adjustment environment 100 may be a cloud environment. As shown in fig. 1, the score adjustment environment 100 includes a computing device 110 and input data 120. In the score adjustment environment 100, the input data 120 is provided to the computing device 110 as input to the computing device 110. The input data 120 may include, for example, attributes such as categories of media assets that have been presented or are to be presented, presentation histories of media assets and selection play histories of media assets by users, which may include the number of presentations of media assets over a certain time such as 7 days, and other data such as various thresholds associated with adjusting scores of media assets, among others, where the presentation histories of media assets may include instances of user selection play of media assets presented to a user over a certain time such as 7 days.
According to one or more embodiments of the present disclosure, the media assets may include, for example, pre-stored video, live video, pre-stored audio, live audio, and the like media assets.
After the computing device 110 receives the input data 120, the computing device 110 may determine a set of consecutive unselected times associated with the set of categories that the candidate media asset has based on the input data 120. According to one or more embodiments of the present disclosure, the consecutive numbers of times of non-selection in the set of consecutive numbers of times of non-selection indicate consecutive numbers of times the media asset of the category associated with the consecutive numbers of times of non-selection is presented without being selected for playing. The computing device 110 may then determine whether there is a condition in which at least one of the aforementioned set of consecutive numbers of deselections is greater than the associated at least one threshold of consecutive numbers of deselections, and, when so, decrease the score of the candidate media asset.
In accordance with one or more embodiments of the present disclosure, a category of a media asset may be considered a "label" added to the media asset to distinguish the media asset. The categories are of various kinds and may include, for example, a larger range of entertainment, health, sports, sannong, a smaller range of physical examination, health counseling, disease classification, football, basketball, and a smaller range of cancer, science, mei Xi, etc. Furthermore, categories may also be classified according to the range of videos that the category may cover, e.g. a larger range of entertainment, health, sports, sannong may be classified as a first class, a smaller range of physical examination, health counseling, disease classification, football, basketball, etc. may be classified as a second class, and a smaller range of cancer, science, mei Xi, etc. may be classified as a third class, wherein for example the smallest range of third class that has been directed to a person may also be referred to as a point of interest, which typically cannot be subdivided into smaller range classes anymore.
It should be appreciated that the score adjustment environment 100 is merely exemplary and not limiting, and is scalable in that more computing devices 110 may be included and more input data 120 may be provided to the computing devices 110, thereby enabling the need for more users to make score adjustments to more candidate media assets simultaneously or non-simultaneously, using more computing devices 110 and even more input data 120.
According to one or more embodiments of the disclosure, after a user enters a live channel page, a recommendation system finally displays media resources to the user through six stages of recall, rough ranking model scoring, rough ranking score adjustment, fine ranking model scoring, fine ranking score adjustment and resource issuing. Recall refers to the process of recommending candidate media assets to a user when the user first enters a live platform. The rough sort and the fine sort may be collectively referred to as a sort, and refer to a process of sorting resources presented by the target user. For live resources, the sorting needs to be faster so that the live resources can be provided to the user quickly after the live is started, which can be currently controlled within tens of milliseconds. The ranking models for coarse and fine may be different, with the coarse ranking being faster. During the coarse scoring adjustment and the fine scoring adjustment stages, computing device 110 may decrease the score of the candidate media asset.
In the score adjustment environment 100 shown in fig. 1, input of input data 120 to the computing device 110 may be made over a network.
Fig. 2 shows a flow diagram of a score adjustment method 200 according to an embodiment of the present disclosure. In particular, the score adjustment method 200 may be performed by the computing device 110 in the score adjustment environment 100 shown in fig. 1. It should be understood that the score adjustment method 200 may also include additional operations not shown and/or may omit the operations shown, as the scope of the disclosure is not limited in this respect.
At block 202, the computing device 110 determines a set of consecutive unselected times associated with the set of categories the candidate media resource has. According to one or more embodiments of the present disclosure, the number of consecutive deselections in the set of consecutive deselections indicates the number of consecutive times that the media asset of the category associated with the number of consecutive deselections is presented without being selected for play. In determining the set of consecutive unselected times associated with the set of categories that the candidate media resource has, the computing device 110 may determine the set of consecutive unselected times associated with the set of categories that the candidate media resource has over a time frame, e.g., 7 days, such that execution of the score adjustment method 200 may be made more real-time.
In accordance with one or more embodiments of the present disclosure, upon determining a set of consecutive unselected times associated with a set of categories that the candidate media resource has, the computing device 110 may build a < category, score reduction ratio > dictionary for each category. If, during the determination at block 202, the user has selected a media asset having a certain category for playback, entries for that category may be deleted from the dictionary.
According to one or more embodiments of the present disclosure, one media asset may have a plurality of categories. For example, a media asset for football player "Mei Xi" may have "sports" as the largest primary category of scope, "football" as the smaller secondary category of scope, and "Mei Xi" as the smallest tertiary category or point of interest. As another example, a media asset for a community may have three categories of "sports", "entertainment", and "food" at the same time as it relates to entertaining sports and dining.
According to one or more embodiments of the present disclosure, if a user is presented 10 times with a media asset in the category "sports," but none of the users has selected to play them, the number of consecutive non-selections of this category "sports" is 10. According to some embodiments of the present disclosure, if a plurality of media assets having the same category are presented to a user at one time, but the user does not choose to play any of the media assets, each of the media assets will be counted despite being presented simultaneously. According to further embodiments of the present disclosure, if a plurality of media assets having the same category are presented to the user at one time, the number of consecutive non-selections for the category is only considered to be 1 for the media assets.
At block 204, the computing device 110 determines whether there is a condition where at least one consecutive number of deselections in the set of consecutive numbers of deselections is greater than the associated at least one consecutive number of deselections threshold. If there is a condition where at least one consecutive number of deselections in the set of consecutive numbers of deselections is greater than the associated at least one consecutive number of deselections threshold, then the method 200 proceeds to block 206; otherwise, the computing device 110 does not need to perform subsequent operations and the method 200 ends.
According to some embodiments of the present disclosure, the at least one consecutive number of non-selections corresponds one-to-one to the associated at least one consecutive number of non-selections threshold, and the specific value of the consecutive number of non-selections threshold may be predetermined, for example, based on whether the category is popular. For example, since the category "sports" is popular, the threshold of the number of consecutive non-selections associated with the category "sports" may be set to 3 times. For another example, since the category "deep learning" is low in popularity, the threshold of the number of consecutive unselections associated with the category "deep learning" may be set to 6.
According to other embodiments of the present disclosure, when the at least one consecutive non-selection number is a plurality of consecutive non-selection numbers, the at least one consecutive non-selection number threshold may also include only one consecutive non-selection number threshold. At this time, the computing device 110 will first determine the maximum number of consecutive non-selections in the set of consecutive non-selections, and further determine whether the aforementioned maximum number of consecutive non-selections is greater than the aforementioned single threshold of consecutive non-selections, e.g., the first threshold of consecutive non-selections. If the maximum number of consecutive unselected times is greater than the first threshold number of consecutive unselected times, the method 200 proceeds to block 206; otherwise, the computing device 110 does not need to perform subsequent operations and the method 200 ends.
At block 206, the computing device 110 reduces the score of the candidate media asset. According to some embodiments of the present disclosure, the computing device 110 may decrease the current score of the candidate media resource by a preset proportion, e.g., 10%, when there is a case where at least one consecutive number of times of non-selection in the set of consecutive times of non-selection is greater than the associated at least one consecutive threshold number of times of non-selection, or may decrease the current score of the candidate media resource by a preset score value, e.g., 10 points, in a case where the full score of the candidate media resource is 100 points.
According to further embodiments of the present disclosure, when the computing device 100 advances the method 200 to block 206 by determining that the maximum number of consecutive non-selections is greater than the first number of consecutive non-selections threshold as described above, the computing device 110 may decrease the current score of the candidate media asset by a proportion associated with the maximum number of consecutive non-selections value or by a score value associated with the maximum number of consecutive non-selections value based on the maximum number of consecutive non-selections value. For example, the score of the candidate media asset may be reduced using a score reduction ratio. The fraction reduction ratio may be calculated using the following formula (1):
fractional reduction ratio = fractional reduction weight/(e) (maximum consecutive unselected number-first consecutive unselected number threshold) + fractional reduction of weight (maximum consecutive unselected number-first consecutive unselected number threshold) ) (1)
In formula (1), the score reduction weight may be a predetermined value such as 2. Further, as can be seen from equation (1), when the maximum consecutive unselected number is equal to the first consecutive unselected number threshold, the score reduction ratio has a value of 1.
After determining the score reduction ratio, if during the rough score adjustment and the fine score adjustment stages, certain categories that the candidate media resource has hit < category, score reduction ratio > entries in the dictionary, the rough score and the fine score may be multiplied by the largest score reduction ratio of the score reduction ratios associated with those categories, respectively.
According to further embodiments of the present disclosure, when the at least one consecutive number of non-selections comprises a plurality of consecutive numbers of non-selections, and thus the associated at least one consecutive number of non-selections threshold comprises an associated plurality of consecutive number of non-selections thresholds, the computing device 110 may decrease the current score of the candidate media resource by a proportion associated with the plurality of values of the plurality of consecutive numbers of non-selections, or by a score value associated with the plurality of values of the plurality of consecutive numbers of non-selections, based on the plurality of values of the plurality of consecutive numbers of non-selections. For example, the category coefficients of a plurality of categories associated with a plurality of consecutive times of non-selection may be determined first, and the aforementioned score reduction weight proportion may be determined later by the category coefficients and a plurality of score reduction coefficients associated with a plurality of consecutive times of non-selection. The category coefficient for each category of the candidate media assets may be calculated using equation (2) as follows:
class coefficient = 1.0/number of consecutive deselections (number of shown times-threshold number of shown times) (2)
In equation (2), the threshold of the number of presentations for the primary class, the secondary class, and the tertiary class, as exemplified by the three-level class, may be preset to 3, 4, and 5, respectively, or any suitable preset value.
Then, the fraction reduction ratio can be calculated using the following equation (3):
fraction reduction ratio = 1.0/(1.0 +e) -1.0 (primary class coefficient primary class score reduction coefficient + secondary class coefficient secondary class score reduction coefficient + tertiary class coefficient tertiary class score reduction coefficient) ) (3)
After the score reduction ratio is determined, if, during the rough and fine score adjustment stages, certain categories that the candidate media resource has hit < category, score reduction ratio > entries in the dictionary, the rough and fine scores may be multiplied by the score reduction ratios associated with those categories, respectively.
Fig. 3 shows a flow diagram of a score adjustment method 300 according to an embodiment of the disclosure. In particular, the score adjustment method 300 may also be performed by the computing device 110 in the score adjustment environment 100 shown in fig. 1. It should be understood that the score adjustment method 300 may also include additional operations not shown and/or may omit the operations shown, as the scope of the present disclosure is not limited in this respect. The score adjustment method 300 may be an extension of the score adjustment method 200.
At block 302, the computing device 110 determines a set of consecutive unselected times associated with the set of categories the candidate media resource has. According to one or more embodiments of the present disclosure, the consecutive numbers of times of non-selection in the set of consecutive numbers of times of non-selection indicate consecutive numbers of times the media asset of the category associated with the consecutive numbers of times of non-selection is presented without being selected for playing. The specific content of the step referred to in the block 302 is the same as that of the step referred to in the block 202, and is not described herein again.
At block 304, the computing device 110 determines whether there is a condition where at least one consecutive number of deselections in the set of consecutive numbers of deselections is greater than the associated at least one consecutive number of deselections threshold. If there is a condition that at least one consecutive number of deselections in the set of consecutive numbers of deselections is greater than the associated at least one consecutive number of deselections threshold, then the method 300 proceeds to block 306; otherwise, the computing device 110 does not need to perform subsequent operations and the method 300 ends. The specific content of the step referred to in the block 304 is the same as that of the step referred to in the block 204, and is not described herein again.
At block 306, the computing device 110 reduces the score of the candidate media asset. The specific content of the step referred to in the block 306 is the same as that of the step referred to in the block 206, and is not described herein again.
At block 308, the computing device 110 adjusts the presentation of the candidate media asset based on the reduced score of the candidate media asset. According to one or more embodiments of the present disclosure, when a user enters a media resource presentation interface, the recommendation system may present the recommended media resources to the user according to, for example, historical presentation conditions of different categories of media resources or historical play conditions of different categories of media resources selected by the user, and the user may browse the different media resources presented by the recommendation system through a sliding interface.
The order in which the media assets are presented in the asset presentation interface is related to the scores of the media assets, which may represent the user's interest level in the media assets.
FIG. 4 shows a schematic diagram of a media asset presentation comparison 400 according to an embodiment of the disclosure. Media asset presentation interface 410 as shown in FIG. 4 is an initial media asset presentation interface in which a first media asset 411, a second media asset 412, a third media asset 413, and a fourth media asset 414 are presented. Where the score of first media asset 411 is the highest and is therefore placed at the uppermost position in media asset presentation interface 410, the scores of second media asset 412, third media asset 413, and fourth media asset 414 decrease in order compared to the score of first media asset 411. The user may display a fifth media asset, not currently displayed, located below the fourth media asset 414, for example, by performing a swipe up gesture on media asset presentation interface 410.
According to some embodiments of the present disclosure, the computing device 110 adjusting the presentation of the candidate media assets includes adjusting presentation priorities of the candidate media assets. For example, the likelihood that a candidate media asset is presented may be associated with a presentation priority of the candidate media asset, the greater the presentation priority, the greater the likelihood that the candidate media asset is presented, and vice versa. Thus, the computing device 110 may decrease the presentation priority of the candidate media asset based on the decreased score of the candidate media asset, thereby making the candidate media asset less likely to be presented.
According to further embodiments of the present disclosure, adjusting the presentation of the candidate media assets by the computing device 110 includes adjusting an order of presentation of the candidate media assets relative to other media assets being presented. For example, when multiple media assets are presented in the same media asset presentation interface, the computing device 110 may determine that the presentation of the media assets is smooth according to the scores of the different media assets, and the media asset with the highest score may be placed at the top of the media asset presentation interface. Thus, the computing device 110 may adjust the position of the media asset in the media asset presentation interface downward based on the decreased score of the candidate media asset.
According to still further embodiments of the present disclosure, the computing device 110 adjusting the presentation of the candidate media asset includes determining whether a reduced score of the candidate media asset is below a score threshold, and stopping the presentation of the candidate media asset when the reduced score of the candidate media asset is below the score threshold.
With reference to FIG. 4, the media asset presentation interface 420 as shown in FIG. 4 is a media asset presentation interface after adjusting presentation of the candidate media asset based on the reduced score of the candidate media asset. In particular, the score of the second media asset 412 in the media asset presentation interface 410 is lowered below the score of the third media asset 413, and the score of the fourth media asset 414 is lower than the score threshold. Thus, in the media asset presentation interface 420, the presentation order of the media assets is adjusted such that the second media asset 412 is presented below the third media asset 413 and the fourth media asset 414 is no longer presented, but instead a presentation of the fifth media asset 415 is added in the media asset presentation interface 420.
At block 310, the computing device 110 determines at least one other candidate media resource associated with the candidate media resource. According to some embodiments of the present disclosure, the computing device 110 may determine at least one other candidate media resource having the same category as the category associated with at least one of the set of consecutive numbers of deselections. For example, if at least one consecutive number of non-selections of the set of consecutive numbers of non-selections of the candidate media resource that is greater than the associated at least one consecutive threshold number of non-selections is associated with the category "sports," the computing device 110 may determine at least one other candidate media resource having the category "sports.
According to further embodiments of the present disclosure, wherein the candidate media asset is a live media asset, and the computing device 110 may determine at least one other candidate media asset having the same anchor as the anchor of the candidate media asset. It is noted that the name or identification of the anchor may also be considered a category or point of interest of the candidate media asset, when the computing device 110 is equivalent to at least one other candidate media asset that is also determined to have the same category as the category associated with at least one of the set of consecutive numbers of non-selections.
At block 312, the computing device 110 may decrease the score of the at least one other candidate media resource determined at block 310. The way of decreasing the score of at least one other candidate media resource is the same as the way of decreasing the score of the candidate media resource, and is not repeated herein.
Related matters related to a score adjustment environment 100 in which a score adjustment method in certain embodiments of the present disclosure may be implemented, a score adjustment method 200 according to an embodiment of the present disclosure, a score adjustment method 300 according to an embodiment of the present disclosure, and a media asset presentation comparison 400 according to an embodiment of the present disclosure are described above with reference to fig. 1-4. It should be understood that the above description is intended to better illustrate what is recited in the present disclosure, and is not intended to be limiting in any way.
It should be understood that the number of various elements and the size of physical quantities employed in the various drawings of the present disclosure are by way of example only and are not limiting upon the scope of the present disclosure. The above numbers and sizes may be arbitrarily set as needed without affecting the normal implementation of the embodiments of the present disclosure.
Details of the score adjustment method 200 and the score adjustment method 300 according to embodiments of the present disclosure have been described above with reference to fig. 1 to 4. Hereinafter, each module in the fraction adjustment apparatus will be described with reference to fig. 5.
Fig. 5 is a schematic block diagram of a score adjustment apparatus 500 according to an embodiment of the present disclosure. As shown in fig. 5, the score adjusting means 500 includes: a consecutive unselected times set determining module 510 configured to determine a consecutive unselected times set associated with the category set that the candidate media resource has, a consecutive unselected times in the consecutive unselected times set indicating consecutive times at which the media resource of the category associated with the consecutive unselected times is presented without being selected for playing; and a first score reduction module 520 configured to reduce the score of the candidate media asset if at least one consecutive number of deselections in the set of consecutive numbers of deselections is greater than the associated at least one consecutive number of deselections threshold.
In one or more embodiments, the first score reduction module 520 comprises: a second score reduction module (not shown) configured to reduce the score by one of: presetting a proportion; and a preset score value.
In one or more embodiments, wherein the at least one consecutive number of non-selections threshold is a first consecutive number of non-selections threshold, and the first score reduction module 520 comprises: a maximum consecutive number-of-non-selections determination module (not shown) configured to determine a maximum consecutive number of non-selections in a set of consecutive numbers of non-selections; and a third score reduction module (not shown) configured to reduce the score of the candidate media asset if the maximum number of consecutive non-selections is greater than the first threshold number of consecutive non-selections.
In one or more embodiments, the third score reduction module includes: a fourth score reduction module (not shown) configured to reduce the score by one of: a ratio associated with the number of times value; and a score value associated with the degree value.
In one or more embodiments, wherein the at least one consecutive number of deselections comprises a plurality of consecutive numbers of deselections, and the first score reduction module 520 comprises: a fifth score reduction module (not shown) configured to reduce the score by one of: a ratio associated with a plurality of order values; and a score value associated with the plurality of degree values.
In one or more embodiments, the score adjusting apparatus 500 further includes: a first further candidate media resource determination module (not shown) configured to determine at least one further candidate media resource associated with the candidate media resource; and a sixth score reduction module (not shown) configured to reduce the score of at least one other candidate media asset.
In one or more embodiments, the first other candidate media resource determination module comprises: a second further candidate media asset determination module (not shown) configured to determine at least one further candidate media asset having the same category as the category associated with the consecutive number of non-selections in the set of consecutive numbers of non-selections.
In one or more embodiments, wherein the candidate media asset is a live media asset, and the first other candidate media asset determination module comprises: a third other candidate media resource determination module (not shown) configured to determine at least one other candidate media resource having the same anchor as the anchor of the candidate media resource.
In one or more embodiments, the score adjusting apparatus 500 further includes: a presentation adjustment module (not shown) configured to adjust presentation of the candidate media asset based on the reduced score of the candidate media asset.
In one or more embodiments, wherein the presentation adjustment module comprises one of: a presentation priority adjustment module (not shown) configured to adjust a presentation priority of the candidate media asset; and a presentation order adjustment module (not shown) configured to adjust a presentation order of the candidate media assets relative to other media assets being presented.
In one or more embodiments, wherein the presentation adjustment module comprises: a presentation stopping module (not shown) configured to stop presentation of the candidate media asset if the reduced score is below the score threshold.
Through the above description with reference to fig. 1 to 5, the technical solution according to the embodiments of the present disclosure has many advantages over the conventional solution. For example, with the technical solution according to the embodiments of the present disclosure, compared to a live broadcast recommendation system that lacks a media resource right drop and backtracking mechanism or has a media resource right drop and backtracking mechanism that is rough in the conventional technology at present, the score of a media resource can be adjusted by using the presentation history of the media resource and the selection play history of the media resource by a user to reflect the interest of the user in the media resource, so that the presentation of the media resource to the user can be adjusted, the media resource that is not interested by the user is dropped or backtracked, the diversity of media resource presentation can be improved, and the user experience when the user watches the media resource can be improved.
The present disclosure also provides an electronic device, a computer-readable storage medium, and a computer program product according to embodiments of the present disclosure.
FIG. 6 illustrates a schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure. For example, the computing device 110 as shown in fig. 1 and the score adjustment apparatus 500 as shown in fig. 5 may be implemented by the electronic device 600. The electronic device 600 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 6, the apparatus 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 602 or a computer program loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 can also be stored. The calculation unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
A number of components in the device 600 are connected to the I/O interface 605, including: an input unit 606 such as a keyboard, a mouse, or the like; an output unit 607 such as various types of displays, speakers, and the like; a storage unit 608, such as a magnetic disk, optical disk, or the like; and a communication unit 609 such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The computing unit 601 performs the various methods and processes described above, such as the method 200 and the method 300. For example, in some embodiments, the methods 200 and 300 may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 600 via the ROM 602 and/or the communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the methods 200 and 300 described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the method 200 and the method 300 by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program code, when executed by the processor or controller, causes the functions/acts specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user may provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (24)
1. A score adjustment method, comprising:
determining a set of consecutive unselect times associated with a set of categories that a candidate media asset has, the consecutive unselect times in the set of consecutive unselect times indicating consecutive times that media assets of the category associated with the consecutive unselect times are presented without being selected for playback; and
decreasing the score of the candidate media asset if at least one consecutive number of deselections in the set of consecutive numbers of deselections is greater than at least one consecutive number of deselections threshold associated with the at least one consecutive number of deselections.
2. The method of claim 1, wherein decreasing the score of the candidate media resource comprises decreasing the score by one of:
reducing the score by one of:
presetting a proportion; and
a preset point value.
3. The method of claim 1, wherein the at least one threshold of consecutive number of non-selections is a first threshold of consecutive number of non-selections, and decreasing the score of the candidate media resource comprises:
determining the maximum continuous unselection times in the continuous unselection times set; and
decreasing the score of the candidate media resource if the maximum number of consecutive non-selections is greater than the first threshold number of consecutive non-selections.
4. The method of claim 3, wherein reducing the score of the candidate media resource comprises:
based on the number of times value of the maximum number of consecutive non-selections, decreasing the score by one of:
a ratio associated with the number of times value; and
a score value associated with the degree value.
5. The method of claim 1, wherein the at least one consecutive number of non-selections comprises a plurality of consecutive numbers of non-selections, and reducing the score of the candidate media asset comprises:
based on a plurality of degree values of the plurality of consecutive unselect degrees, decreasing the score by one of:
a ratio associated with the plurality of degree values; and
a score value associated with the plurality of degree values.
6. The method of claim 1, further comprising:
determining at least one other candidate media resource associated with the candidate media resource; and
decreasing the score of the at least one other candidate media resource.
7. The method of claim 6, wherein determining the at least one other candidate media resource associated with the candidate media resource comprises:
determining the at least one other candidate media resource having the same category as the category associated with the at least one consecutive number of deselections in the set of consecutive numbers of deselections.
8. The method of claim 6, wherein the candidate media asset is a live media asset, and determining the at least one other candidate media asset associated with the candidate media asset comprises:
determining the at least one other candidate media resource having the same anchor as the anchor of the candidate media resource.
9. The method of claim 1, further comprising:
adjusting presentation of the candidate media resource based on the reduced score of the candidate media resource.
10. The method of claim 9, wherein adjusting the presentation of the candidate media assets comprises one of:
adjusting the presentation priority of the candidate media resources; and
adjusting a presentation order of the candidate media assets relative to other media assets being presented.
11. The method of claim 9, wherein adjusting the presentation of the candidate media assets comprises:
stopping the presentation of the candidate media assets if the reduced score is below a score threshold.
12. A score adjustment apparatus comprising:
a consecutive unselected times set determination module configured to determine a consecutive unselected times set associated with a category set that the candidate media resource has, the consecutive unselected times in the consecutive unselected times set indicating consecutive times at which media resources of a category associated with the consecutive unselected times are presented without being selected for play; and
a first score reduction module configured to reduce the score of the candidate media resource if at least one consecutive number of deselections in the set of consecutive numbers of deselections is greater than at least one consecutive number of deselections threshold associated with the at least one consecutive number of deselections.
13. The apparatus of claim 12, wherein the first score reduction module comprises:
a second score reduction module configured to reduce the score by one of:
presetting a proportion; and
a preset point value.
14. The apparatus of claim 12, wherein the at least one consecutive number of non-selections threshold is a first consecutive number of non-selections threshold, and the first score reduction module comprises:
a maximum consecutive unselected number determination module configured to determine a maximum consecutive unselected number in the set of consecutive unselected numbers; and
a third score reduction module configured to reduce the score of the candidate media resource if the maximum number of consecutive unselected times is greater than the first threshold number of consecutive unselected times.
15. The apparatus of claim 14, wherein the third fractional reduction module comprises:
a fourth score reduction module configured to reduce the score by one of:
a ratio associated with the number of times value; and
a score value associated with the degree value.
16. The apparatus of claim 12, wherein the at least one consecutive number of deselections comprises a plurality of consecutive numbers of deselections, and the first score reduction module comprises:
a fifth score reduction module configured to reduce the score by one of:
a ratio associated with the plurality of degree values; and
a score value associated with the plurality of degree values.
17. The apparatus of claim 12, further comprising:
a first other candidate media resource determination module configured to determine at least one other candidate media resource associated with the candidate media resource; and
a sixth score reduction module configured to reduce the score of the at least one other candidate media resource.
18. The apparatus of claim 17, wherein the first other candidate media resource determination module comprises:
a second other candidate media asset determination module configured to determine the at least one other candidate media asset having the same category as the category associated with the at least one consecutive number of deselections in the set of consecutive numbers of deselections.
19. The apparatus of claim 17, wherein the candidate media assets are live media assets and the first other candidate media asset determination module comprises:
a third other candidate media resource determination module configured to determine the at least one other candidate media resource that has the same anchor as the anchor of the candidate media resource.
20. The apparatus of claim 12, further comprising:
a presentation adjustment module configured to adjust presentation of the candidate media asset based on the reduced score of the candidate media asset.
21. The apparatus of claim 20, wherein the presentation adjustment module comprises one of:
a presentation priority adjustment module configured to adjust a presentation priority of the candidate media resource; and
a presentation order adjustment module configured to adjust a presentation order of the candidate media assets relative to other media assets being presented.
22. The device of claim 20, wherein the presentation adjustment module comprises:
a presentation stopping module configured to stop the presentation of the candidate media assets if the reduced score is below a score threshold.
23. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-11.
24. A non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of any one of claims 1-11.
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