CN114676272A - Information processing method, device and equipment of multimedia resource and storage medium - Google Patents

Information processing method, device and equipment of multimedia resource and storage medium Download PDF

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CN114676272A
CN114676272A CN202210267772.6A CN202210267772A CN114676272A CN 114676272 A CN114676272 A CN 114676272A CN 202210267772 A CN202210267772 A CN 202210267772A CN 114676272 A CN114676272 A CN 114676272A
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account
sample
characteristic information
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涂畅
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Beijing Dajia Internet Information Technology Co Ltd
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Beijing Dajia Internet Information Technology Co Ltd
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    • G06F16/40—Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
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    • G06F16/489—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using time information
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    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F18/00—Pattern recognition
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Abstract

The disclosure relates to an information processing method, an information processing device, information processing equipment and a storage medium of multimedia resources, relates to the technical field of computers, and can accurately determine interaction parameters of the multimedia resources. The information processing method of the multimedia resource comprises the following steps: acquiring characteristic information of a target account; the target account includes: the account which performs interactive operation on the multimedia resource to be processed in the first time period; inputting the characteristic information of the target account into a pre-trained target model to obtain an interaction parameter of the multimedia resource to be processed at a first moment; the target model is obtained by training according to the characteristic information of the sample account; the sample account includes: the account which performs interactive operation on the sample multimedia resources in the second time period; the characteristic information of the sample account includes: identification characteristic information and behavior characteristic information of the sample account; the first time is after the first time period.

Description

Information processing method, device and equipment of multimedia resource and storage medium
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to an information processing method, an information processing apparatus, a device, and a storage medium for multimedia resources.
Background
Short videos gradually become one of the main means for people to record life and also one of the main forms for people to consume and entertain everyday. The interactive parameters (e.g. playing times, praised times, etc.) of the short video are important parameters of the short video. Therefore, how to accurately determine the interaction parameters of the short video at a certain time is a technical problem that needs to be solved at present.
Disclosure of Invention
The present disclosure provides an information processing method, apparatus, device and storage medium for multimedia resources, which can accurately determine interaction parameters of multimedia resources.
The technical scheme of the embodiment of the disclosure is as follows:
according to a first aspect of the embodiments of the present disclosure, an information processing method of a multimedia resource is provided, which may be applied to an electronic device. The method can comprise the following steps:
acquiring characteristic information of a target account; the target account includes: the account which performs interactive operation on the multimedia resource to be processed in a first time period; the characteristic information of the target account comprises: identification characteristic information and behavior characteristic information of the target account; the behavior characteristic information of the target account is used for representing the interactive behavior executed by the target account on the multimedia resource to be processed in a first time period;
Inputting the characteristic information of the target account into a pre-trained target model to obtain an interaction parameter of the multimedia resource to be processed at a first moment; the target model is obtained by training according to the characteristic information of the sample account; the sample accounts include: the account which performs interactive operation on the sample multimedia resources in the second time period; the characteristic information of the sample account includes: identification characteristic information and behavior characteristic information of the sample account; the behavior characteristic information of the sample account is used for representing the interactive behavior executed on the sample multimedia resource by the sample account in the second time period; the first time is after the first time period.
Optionally, the information processing method of the multimedia resource further includes:
acquiring identification characteristic information of a sample account and behavior characteristic information of the sample account;
and training to obtain a target model according to the identification characteristic information of the sample account, the behavior characteristic information of the sample account and a preset model.
Optionally, the sample accounts include a positive sample account and a negative sample account;
acquiring identification characteristic information of the sample account and behavior characteristic information of the sample account, wherein the identification characteristic information comprises the following steps:
acquiring the number of times of the interactive operation executed on the sample multimedia resource at the second moment; the second time is after the second time period;
Determining a positive sample account and a negative sample account according to the number of times of the interactive operation executed on the sample multimedia resources at the second moment;
and determining the combination of the identification characteristic information of the positive sample account and the identification characteristic information of the negative sample account as the identification characteristic information of the sample account, and determining the combination of the behavior characteristic information of the positive sample account and the behavior characteristic information of the negative sample account as the behavior characteristic information of the sample account.
Optionally, determining the positive sample account and the negative sample account according to the number of times of the sample multimedia resources being performed with the interactive operation at the second time includes:
determining the sample multimedia resources of which the times of the interactive operation executed at the second moment is more than the preset times as positive sample multimedia resources;
determining the account which performs the interactive operation on the positive sample multimedia resource in the second time period as a positive sample account;
determining sample multimedia resources of which the times of the interactive operation executed at the second moment are less than or equal to the preset times as negative sample multimedia resources;
and determining the account which performs the interactive operation on the negative sample multimedia resource in the second time period as a negative sample account.
Optionally, the preset model includes: a logistic regression model; training to obtain a target model according to the identification characteristic information of the sample account, the behavior characteristic information of the sample account and a preset model, wherein the training comprises the following steps:
training the identification characteristic information of the sample account and the behavior characteristic information of the sample account according to the logistic regression model to obtain a model to be adjusted;
and performing L1 regularization processing and orthogonal regularization processing on the model to be adjusted to obtain a target model.
Optionally, after the feature information of the target account is input into the pre-trained target model to obtain the interaction parameter of the multimedia resource to be processed at the first time, the method further includes:
recommending the multimedia resource to be processed to the audience account when the interactive parameter of the multimedia resource to be processed at the first moment meets the preset condition
According to a second aspect of the embodiments of the present disclosure, an information processing apparatus of a multimedia resource is provided, which can be applied to an electronic device. The apparatus may include: an acquisition unit and a processing unit;
the acquisition unit is used for acquiring the characteristic information of the target account; the target account includes: the account which performs interactive operation on the multimedia resource to be processed in a first time period; the characteristic information of the target account comprises: identification characteristic information and behavior characteristic information of the target account; the behavior characteristic information of the target account is used for representing the interactive behavior executed by the target account on the multimedia resource to be processed in a first time period;
The processing unit is used for inputting the characteristic information of the target account into a pre-trained target model so as to obtain the interaction parameters of the multimedia resource to be processed at a first moment; the target model is obtained by training according to the characteristic information of the sample account; the sample account includes: the account which performs interactive operation on the sample multimedia resources in the second time period; the characteristic information of the sample account includes: identification characteristic information and behavior characteristic information of the sample account; the behavior characteristic information of the sample account is used for representing the interactive behavior executed on the sample multimedia resource by the sample account in the second time period; the first time is after the first time period.
Optionally, the obtaining unit is further configured to obtain identification feature information of the sample account and behavior feature information of the sample account;
and the processing unit is also used for training to obtain a target model according to the identification characteristic information of the sample account, the behavior characteristic information of the sample account and the preset model.
Optionally, the sample accounts include a positive sample account and a negative sample account;
an acquisition unit, specifically configured to:
acquiring the number of times of the interactive operation executed on the sample multimedia resource at the second moment; the second time is after the second time period;
Determining a positive sample account and a negative sample account according to the number of times of the interactive operation executed on the sample multimedia resources at the second moment;
and determining the combination of the identification characteristic information of the positive sample account and the identification characteristic information of the negative sample account as the identification characteristic information of the sample account, and determining the combination of the behavior characteristic information of the positive sample account and the behavior characteristic information of the negative sample account as the behavior characteristic information of the sample account.
Optionally, the obtaining unit is specifically configured to:
determining the sample multimedia resources of which the times of the interactive operation executed at the second moment are more than the preset times as the positive sample multimedia resources;
determining the account which performs the interactive operation on the positive sample multimedia resource in the second time period as a positive sample account;
determining sample multimedia resources of which the times of the interactive operation executed at the second moment are less than or equal to the preset times as negative sample multimedia resources;
and determining the account which performs the interactive operation on the negative sample multimedia resources in the second time period as a negative sample account.
Optionally, the preset model includes: a logistic regression model; a processing unit, specifically configured to:
Training the identification characteristic information of the sample account and the behavior characteristic information of the sample account according to the logistic regression model to obtain a model to be adjusted;
and performing L1 regularization processing and orthogonal regularization processing on the model to be adjusted to obtain a target model.
Optionally, the processing unit is further configured to recommend the multimedia resource to be processed to the audience account when the interaction parameter of the multimedia resource to be processed at the first time meets a preset condition.
According to a third aspect of embodiments of the present disclosure, there is provided an electronic device, which may include: a processor and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the information processing method of any one of the above-mentioned first aspect, optionally the multimedia resource.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium having instructions stored thereon, where the instructions of the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the information processing method of any one of the above-mentioned first aspects, optionally, the multimedia resource.
According to a fifth aspect of embodiments of the present disclosure, there is provided a computer program product, which includes computer instructions, when the computer instructions are run on an electronic device, the electronic device is caused to execute the information processing method of a multimedia resource according to any one of the optional implementation manners in the first aspect.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects:
based on any one of the above aspects, in the present disclosure, the feature information of the target account, on which the interactive operation is performed on the multimedia resource to be processed in the first time period, may be obtained, and the interactive parameter of the multimedia resource to be processed at the first time may be determined according to the pre-trained target model. Firstly, the interaction parameters of the multimedia resources to be processed can be determined in advance, so that whether the multimedia resources to be processed are recommended to the audience account can be determined in advance according to the obtained interaction parameters. Secondly, the target model is obtained by training according to the characteristic information of the sample account, so that the interactive parameters of the multimedia resources to be processed can be accurately determined.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure and are not to be construed as limiting the disclosure.
Fig. 1 is a schematic flowchart illustrating an information processing method for a multimedia resource according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart illustrating an information processing method for a multimedia resource according to another embodiment of the present disclosure;
fig. 3 is a schematic flowchart illustrating an information processing method for a multimedia resource according to another embodiment of the present disclosure;
fig. 4 is a schematic flowchart illustrating an information processing method for a multimedia resource according to another embodiment of the present disclosure;
fig. 5 is a flowchart illustrating an information processing method for a multimedia resource according to another embodiment of the present disclosure;
fig. 6 is a flowchart illustrating an information processing method for a multimedia resource according to another embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of an information processing apparatus for a multimedia resource according to another embodiment of the present disclosure;
fig. 8 shows a schematic structural diagram of a terminal provided in an embodiment of the present disclosure;
fig. 9 shows a schematic structural diagram of a server provided in an embodiment of the present disclosure.
Detailed Description
In order to make the technical solutions of the present disclosure better understood by those of ordinary skill in the art, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the foregoing drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in other sequences than those illustrated or described herein. The implementations described in the exemplary embodiments below do not represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the disclosure, as detailed in the appended claims.
It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, 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, and/or components.
The data to which the present disclosure relates may be data that is authorized by a user or sufficiently authorized by parties.
As described in the background, interactive parameters (e.g., number of plays, number of prawns, etc.) of the short video are important parameters of the short video. Therefore, how to accurately determine the interaction parameters of the short video at a certain time is a technical problem that needs to be solved at present.
Based on this, the embodiment of the present disclosure provides an information processing method for multimedia resources, which may obtain feature information of a target account on which an interactive operation is performed on a multimedia resource to be processed in a first time period, and determine an interactive parameter of the multimedia resource to be processed at a first time according to a pre-trained target model. Firstly, the interaction parameters of the multimedia resources to be processed can be determined in advance, so that the method can determine whether to recommend the multimedia resources to be processed to the audience account in advance according to the obtained interaction parameters. Secondly, the target model is obtained by training according to the characteristic information of the sample account, so that the interactive parameters of the multimedia resources to be processed can be accurately determined.
The following is an exemplary description of the information processing method for multimedia resources provided by the embodiments of the present disclosure:
the information processing method of the multimedia resource can be applied to the electronic equipment.
In some embodiments, the electronic device may be a server, a terminal, or another electronic device for performing information processing on multimedia resources, which is not limited in this disclosure.
The server may be a single server, or may be a server cluster formed by a plurality of servers. In some embodiments, the server cluster may also be a distributed cluster. The present disclosure is also not limited to a specific implementation of the server.
The terminal may be a mobile phone, a tablet computer, a desktop computer, a laptop computer, a handheld computer, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, a cellular phone, a Personal Digital Assistant (PDA), an Augmented Reality (AR), a Virtual Reality (VR) device, and other devices that can install and use a content community application (e.g., a fast hand), and the specific form of the electronic device is not particularly limited by the present disclosure. The system can be used for man-machine interaction with a user through one or more modes of a keyboard, a touch pad, a touch screen, a remote controller, voice interaction or handwriting equipment and the like.
The following describes the information processing method for multimedia resources according to the embodiment of the present disclosure in detail with reference to the accompanying drawings.
As shown in fig. 1, when the information processing method of a multimedia asset is applied to an electronic device, the information processing method of the multimedia asset may include:
S101, the electronic equipment obtains characteristic information of the target account.
Wherein the target account includes: and the account which performs interactive operation on the multimedia resource to be processed in the first time period. The characteristic information of the target account comprises: identification characteristic information and behavior characteristic information of the target account; the behavior characteristic information of the target account is used for representing the interactive behavior executed by the target account on the multimedia resource to be processed in the first time period.
Optionally, when the electronic device obtains the feature information of the target account, the electronic device may first obtain the log data of the to-be-processed multimedia resource from the server that issues the to-be-processed multimedia resource. Then, the electronic device can extract the account identifier of the account which has performed the interactive operation on the multimedia resource to be processed from the log data. Subsequently, the electronic device may obtain the feature information of the target account from a database in which the corresponding relationship between the account identifier and the feature information is stored.
Illustratively, the identification characteristic information may include a user representation of the target account, categories of multimedia assets that the target account likes to view, time periods of the viewed multimedia assets, locations of the viewed multimedia assets, and the like.
The behavior feature information may include whether the target account likes to perform an interactive operation on the multimedia resource of interest, whether the multimedia resource on which the target account performs the interactive operation is a hotspot multimedia resource, and the like.
Optionally, the interactive operation includes: a praise operation, a comment operation, a share operation, etc.
S102, the electronic equipment inputs the characteristic information of the target account into a pre-trained target model to obtain the interaction parameters of the multimedia resource to be processed at the first moment.
The target model is obtained by training according to the characteristic information of the sample account; the sample accounts include: the account which performs the interactive operation on the sample multimedia resources in the second time period; the characteristic information of the sample account includes: identification characteristic information and behavior characteristic information of the sample account; the behavior characteristic information of the sample account is used for representing the interactive behavior executed on the sample multimedia resource by the sample account in the second time period; the first time is after the first time period.
Specifically, since the target model is trained in advance, after the feature information of the target account is obtained, the obtained feature information of the target account can be directly input into the target model, so as to obtain the interaction parameters of the multimedia resource to be processed at the first moment.
The interactive parameter is used for representing the times of interactive operations executed by other audience accounts on the multimedia resource to be processed at a certain moment.
Optionally, the interactive operation may be a comment operation, a share operation, and the like.
Alternatively, the interaction parameter may be a specific value. The electronic device may preset an interaction parameter threshold. And when the interactive parameter is greater than the interactive parameter threshold value, determining that the interactive parameter of the multimedia resource to be processed at the first moment is higher. Correspondingly, when the interactive parameter is less than or equal to the interactive parameter threshold, the interactive parameter of the multimedia resource to be processed at the first moment is determined to be lower.
For example, the electronic device may acquire the pending multimedia resource with a praise number of 6000 at 10/30/2021 for information processing of the multimedia resource. In this case, the electronic device may obtain the feature information of the 6000 accounts praised for the multimedia resource to be processed. Then, the electronic device inputs the acquired feature information of the 6000 accounts into a pre-trained target model to obtain interaction parameters of the multimedia resources to be processed in 2021, 11 months and 5 days.
It should be understood that when the interaction parameter of the multimedia asset to be processed is already high, it is not meaningful to determine the interaction parameter of the multimedia asset to be processed. Therefore, the interaction parameter of the multimedia resource to be processed related to the present disclosure can be in a lower interval.
For example, when the praise of the to-be-processed multimedia resource is used for representing the interaction parameter of the to-be-processed multimedia resource, the praise of the to-be-processed multimedia resource may be a praise greater than 5000 and less than 10000.
Optionally, the interaction parameter of the multimedia resource to be processed may also be represented by other parameters, such as the number of comments, the number of shares, and the like.
The technical scheme provided by the embodiment at least has the following beneficial effects: from S101 to S103, feature information of a target account on which an interactive operation is performed on the to-be-processed multimedia resource in the first time period may be obtained, and an interactive parameter of the to-be-processed multimedia resource at the first time may be determined according to a pre-trained target model. Firstly, the interaction parameters of the multimedia resources to be processed can be determined in advance, so that whether the multimedia resources to be processed are recommended to the audience account can be determined in advance according to the obtained interaction parameters. Secondly, the target model is obtained by training according to the characteristic information of the sample account, so that the interactive parameters of the multimedia resources to be processed can be accurately determined.
In an embodiment, as shown in fig. 2, the information processing method for multimedia resources further includes:
S201, the electronic equipment obtains the identification characteristic information of the sample account and the behavior characteristic information of the sample account.
Specifically, when a target model is obtained through training, a large amount of sample data is needed as training data. In this case, the electronic device may obtain, as the sample account, an account in which the interactive operation was performed on the sample multimedia asset for the second time period.
Optionally, when the electronic device obtains the identification feature information of the sample account and the behavior feature information of the sample account, the electronic device may first obtain sample multimedia resource log data from a server that issues sample multimedia resources. The electronic device can then extract from the log data an account identification of the account on which the interaction was performed with the sample multimedia asset. Subsequently, the electronic device may obtain the identification characteristic information of the sample account and the behavior characteristic information of the sample account from a database in which the account identification and the characteristic information are stored.
Optionally, the second time period may be the same time period as the first time period, or the second time period may be before the first time period, or the second time period may include the first time period. But the second time period cannot be located after the first time period, otherwise, the target model cannot be obtained by training in advance when the interaction parameters of the multimedia resources to be processed are determined.
In practical applications, the second time period generally precedes the first time period in order to more accurately determine the interaction parameters of the multimedia resource to be processed.
S202, the electronic equipment trains to obtain a target model according to the characteristic information of the sample account and the preset model.
Optionally, the preset model may be a logistic regression model, or may be other models, such as a machine regression model, a deep learning model, and the like. The model training process may refer to a process of training a model in the prior art, which is not described herein again.
The technical scheme provided by the embodiment at least has the following beneficial effects: from S201 to S202, the electronic device may train to obtain the target model based on the obtained feature information of the sample account and the preset model, so that the electronic device can accurately obtain the interaction parameters of the multimedia resource to be processed by obtaining the target model, and the accuracy of obtaining the interaction parameters of the multimedia resource is improved.
In one embodiment, the sample accounts include positive sample accounts and negative sample accounts. With reference to fig. 2 and as shown in fig. 3, in the above S201, the method for acquiring, by the electronic device, the identification characteristic information of the sample account and the behavior characteristic information of the sample account specifically includes:
S301, the electronic equipment obtains the number of times of the interactive operation executed on the sample multimedia resource at the second moment.
Specifically, to improve the accuracy of the trained target model, the electronic device may divide the sample accounts into positive sample accounts and negative sample accounts. When determining the positive sample account and the negative sample account, the electronic device may distinguish the positive sample account from the negative sample account according to the number of times the sample multimedia resource is executed with the interactive operation at the second time. Namely, the interaction parameters of the sample multimedia resources at the second moment are determined to distinguish the positive sample account from the negative sample account
Wherein the second time is after the second time period.
S302, the electronic equipment determines a positive sample account and a negative sample account according to the number of times of the interactive operation executed on the sample multimedia resources at the second moment.
Specifically, since the second time is located after the second time period, it can be determined whether the interaction parameter of the sample multimedia asset at the second time is already high according to the number of times the sample multimedia asset is performed the interaction operation at the second time.
Optionally, the number of the sample multimedia resources may be multiple, and if the interaction parameter of a part of the sample multimedia resources at the second time is higher, the sample account performing the interaction operation on the part of the sample multimedia resources may be used as the positive sample account.
Correspondingly, if the interaction parameter of another part of sample multimedia resources at the second time is lower, the sample account for performing the interaction operation on the part of sample multimedia resources may be taken as a negative sample account.
Therefore, by distinguishing the positive sample accounts from the negative sample accounts, the trained target model can select the accounts with higher contribution degree to the interactive parameters of the multimedia resources from the massive accounts, and further the interactive parameters of the multimedia resources to be processed can be reasonably obtained.
S303, the electronic equipment determines the combination of the identification characteristic information of the positive sample account and the identification characteristic information of the negative sample account as the identification characteristic information of the sample account, and determines the combination of the behavior characteristic information of the positive sample account and the behavior characteristic information of the negative sample account as the behavior characteristic information of the sample account.
The technical scheme provided by the embodiment at least has the following beneficial effects: from S301 to S303, the electronic device may divide the sample account into a positive sample account and a negative sample account, so that the trained target model may select an account with a higher contribution degree to the interaction parameter of the multimedia resource from a large number of accounts, thereby improving the accuracy of the information processing model training of the multimedia resource, and further obtaining the interaction parameter of the multimedia resource to be processed reasonably.
In an embodiment, referring to fig. 3 and as shown in fig. 4, in the above S302, the method for the electronic device to determine the positive sample account and the negative sample account according to the number of times the sample multimedia resource is performed with the interactive operation at the second time specifically includes:
s401, the electronic equipment determines the sample multimedia resources of which the times of the interactive operation executed at the second moment are more than the preset times as the positive sample multimedia resources.
S402, the electronic equipment determines the account which is subjected to the interactive operation on the positive sample multimedia resource in the second time period as a positive sample account.
And S403, the electronic equipment determines the sample multimedia resources of which the number of times of the interactive operation executed at the second moment is less than or equal to the preset number of times as negative sample multimedia resources.
S404, the electronic device determines the account which performs the interactive operation on the negative sample multimedia resource in the second time period as a negative sample account.
Illustratively, the preset interactive operation is a praise operation. The number of the sample multimedia resources is preset to be 200, and the praise number of the 200 sample multimedia resources is higher than 5000 and less than 10000. The electronic device may obtain accounts from the log data that complied with 200 sample multimedia resources at 14 days 10 months 2021.
Then, the electronic device obtains praise for 200 sample multimedia assets at 10/20/2021.
When the praise number of 150 sample multimedia assets among 200 sample multimedia assets in 10 months and 20 days in 2021 is greater than 10 ten thousand, the 150 sample multimedia assets are determined as positive sample multimedia assets.
Then, the electronic device determines the accounts approved by the 150 positive sample multimedia resources as the positive sample accounts on 14 days 10 months 2021.
Correspondingly, when the praise number of 50 sample multimedia assets in 200 sample multimedia assets at 10/20/2021 is less than or equal to 10 ten thousand, the 50 sample multimedia assets are determined as negative sample multimedia assets.
Then, the electronic device determines the accounts approved by the 50 negative sample multimedia resources as the negative sample accounts at 14/10/2021.
It should be noted that the sequence of executing S401-S402 and S403-S404 by the electronic device is not limited. That is, the electronic device may determine the positive sample account first and then determine the negative sample account; or determining the negative sample account and then determining the positive sample account; positive and negative sample accounts may also be determined simultaneously.
The technical scheme provided by the embodiment at least has the following beneficial effects: from S401 to S404, a specific implementation manner is given for the electronic device to divide the sample account into the positive sample account and the negative sample account, so that the trained target model can select an account with a higher contribution degree to the interaction parameters of the multimedia resources from a large number of accounts, the accuracy of the information processing model training of the multimedia resources is improved, and the interaction parameters of the multimedia resources to be processed can be reasonably obtained.
In one embodiment, the pre-set model comprises: and (4) performing logistic regression model. With reference to fig. 2 and as shown in fig. 5, in the above S202, the method for training, by the electronic device, the target model according to the identification feature information of the sample account, the behavior feature information of the sample account, and the preset model specifically includes:
s501, the electronic equipment trains the identification characteristic information of the sample account and the behavior characteristic information of the sample account according to the logistic regression model to obtain a model to be adjusted.
Logistic regression is a generalized linear model and thus has many similarities to multiple linear regression analysis. They are essentially identical in model form, all with w x + b, where w and b are the parameters to be solved, differing in their dependent variables. When the electronic device obtains the target model through training, the identification feature information of the sample account and the behavior feature information of the sample account can be trained according to the model of the logistic regression model, so that the model to be adjusted is obtained.
Optionally, the electronic device may also train to obtain the target model through other models, which is not limited in this disclosure.
S502, the electronic equipment executes L1 regularization processing and orthogonal regularization processing on the model to be adjusted to obtain a target model.
Specifically, in the model training process, parameters of the model to be adjusted can be adjusted through the loss function.
The loss function (loss function) is a function that maps a random event or a value of a random variable related to the random event to a non-negative real number to represent a "risk" or a "loss" of the random event. In application, the loss function is usually associated with the optimization problem as a learning criterion, i.e. the model is solved and evaluated by minimizing the loss function.
In the present disclosure, an L1 regularization term and an orthogonal regularization term may be added to the loss function, that is, an L1 regularization process and an orthogonal regularization process are performed on the model to be adjusted to obtain the target model.
The L1 regularization is used for screening an account group which is critical to whether interaction parameters for acquiring multimedia resources are higher than a preset threshold value from hundreds of millions of sample accounts. And the orthogonal regularization is to remove sample accounts with extremely similar characteristic information from the sample accounts, so that the characteristic information of the sample accounts is prevented from generating redundancy, and the training speed of model training is improved.
The technical scheme provided by the embodiment at least has the following beneficial effects: from S501-S502, when the electronic device trains the target model, the electronic device may perform L1 regularization and orthogonal regularization on the model to be adjusted to obtain the target model, which not only improves the accuracy of the sample account, but also reduces the redundancy of the sample account, thereby improving the accuracy and speed of the information processing model training of the multimedia resource.
In an embodiment, with reference to fig. 1 and as shown in fig. 6, after S102, the method for processing information of a multimedia resource further includes:
s601, when the interaction parameter of the multimedia resource to be processed at the first moment meets a preset condition, recommending the multimedia resource to be processed to the audience account by the electronic equipment.
Optionally, the preset condition may be that the interaction parameter of the multimedia resource to be processed at the first time is greater than a preset threshold, or may be another condition used for indicating that the interaction parameter of the multimedia resource to be processed at the first time is higher, which is not limited herein.
Specifically, when the acquired interaction parameter of the to-be-processed multimedia resource at the first moment is higher, the distribution quantity of the to-be-processed multimedia resource can be increased, that is, the to-be-processed multimedia resource can be recommended to a large number of audience accounts.
Correspondingly, when the acquired interactive parameters of the to-be-processed multimedia resources at the first moment are low, the distribution quantity of the to-be-processed multimedia resources can be reduced, namely, the to-be-processed multimedia resources are not recommended to certain audience accounts, so that the pressure of a distribution network is reduced.
The technical scheme provided by the embodiment at least has the following beneficial effects: s601 shows that the electronic device may reasonably determine whether to recommend the pending multimedia resource to the viewer account according to the interaction parameter of the pending multimedia resource at the first time.
It is understood that, in practical implementation, the terminal/server according to the embodiment of the present disclosure may include one or more hardware structures and/or software modules for implementing the information processing method for the corresponding multimedia resource, and these hardware structures and/or software modules may constitute an electronic device. Those of skill in the art will readily appreciate that the present disclosure can be implemented in hardware or a combination of hardware and computer software for performing the exemplary algorithm steps described in connection with the embodiments disclosed herein. Whether a function is performed in hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. 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 disclosure.
Based on such understanding, the embodiment of the present disclosure also provides an information processing apparatus of a multimedia resource, which can be applied to an electronic device. Fig. 7 shows a schematic structural diagram of an information processing apparatus for multimedia resources provided by an embodiment of the present disclosure. As shown in fig. 7, the information processing apparatus of the multimedia asset may include: an acquisition unit 701 and a processing unit 702;
an obtaining unit 701, configured to obtain feature information of a target account; the target account includes: the account which performs interactive operation on the multimedia resource to be processed in a first time period; the characteristic information of the target account comprises: identification characteristic information and behavior characteristic information of the target account; the behavior characteristic information of the target account is used for representing the interactive behavior executed by the target account on the multimedia resource to be processed in a first time period;
the processing unit 702 is configured to input feature information of a target account into a pre-trained target model to obtain an interaction parameter of a multimedia resource to be processed at a first time; the target model is obtained by training according to the characteristic information of the sample account; the sample account includes: the account which performs interactive operation on the sample multimedia resources in the second time period; the characteristic information of the sample account includes: identification characteristic information and behavior characteristic information of the sample account; the behavior characteristic information of the sample account is used for representing the interactive behavior executed on the sample multimedia resource by the sample account in the second time period; the first time is after the first time period.
Optionally, the obtaining unit 701 is further configured to obtain identification feature information of the sample account and behavior feature information of the sample account;
the processing unit 702 is further configured to train to obtain a target model according to the identification feature information of the sample account, the behavior feature information of the sample account, and the preset model.
Optionally, the sample accounts include a positive sample account and a negative sample account;
the obtaining unit 701 is specifically configured to:
acquiring the times of the interactive operation executed on the sample multimedia resource at the second moment; the second time is after the second time period;
determining a positive sample account and a negative sample account according to the number of times of the interactive operation executed on the sample multimedia resources at the second moment;
and determining the combination of the identification characteristic information of the positive sample account and the identification characteristic information of the negative sample account as the identification characteristic information of the sample account, and determining the combination of the behavior characteristic information of the positive sample account and the behavior characteristic information of the negative sample account as the behavior characteristic information of the sample account.
Optionally, the obtaining unit 701 is specifically configured to:
determining the sample multimedia resources of which the times of the interactive operation executed at the second moment are more than the preset times as the positive sample multimedia resources;
Determining the account which performs the interactive operation on the positive sample multimedia resource in the second time period as a positive sample account;
determining sample multimedia resources of which the times of the interactive operation executed at the second moment are less than or equal to the preset times as negative sample multimedia resources;
and determining the account which performs the interactive operation on the negative sample multimedia resource in the second time period as a negative sample account.
Optionally, the preset model includes: a logistic regression model; the processing unit 702 is specifically configured to:
training the identification characteristic information of the sample account and the behavior characteristic information of the sample account according to the logistic regression model to obtain a model to be adjusted;
and performing L1 regularization processing and orthogonal regularization processing on the model to be adjusted to obtain a target model.
Optionally, the processing unit 702 is further configured to recommend the multimedia resource to be processed to the audience account when the interaction parameter of the multimedia resource to be processed at the first time meets a preset condition.
As described above, the embodiment of the present disclosure may perform division of functional modules on an electronic device according to the above method example. The integrated module can be realized in a hardware form, and can also be realized in a software functional module form. In addition, it should be further noted that the division of the modules in the embodiments of the present disclosure is schematic, and is only a logic function division, and there may be another division manner in actual implementation. For example, the functional blocks may be divided for the respective functions, or two or more functions may be integrated into one processing block.
The specific manner in which each module performs the operation and the beneficial effects of the information processing apparatus for multimedia resources in the foregoing embodiments have been described in detail in the foregoing method embodiments, and are not described again here.
The embodiment of the disclosure also provides a terminal, which can be a user terminal such as a mobile phone, a computer and the like. Fig. 8 shows a schematic structural diagram of a terminal provided in an embodiment of the present disclosure. The terminal, which may be an information processing device of a multimedia resource, may include at least one processor 61, a communication bus 62, a memory 63, and at least one communication interface 64.
The processor 61 may be a Central Processing Unit (CPU), a micro-processing unit, an ASIC, or one or more integrated circuits for controlling the execution of programs according to the present disclosure. As an example, in connection with fig. 7, the processing unit 702 in the electronic device implements the same functions as the processor 61 in fig. 8.
The communication bus 62 may include a path that carries information between the aforementioned components.
The communication interface 64 may be any device, such as a transceiver, for communicating with other devices or communication networks, such as a server, an ethernet, a Radio Access Network (RAN), a Wireless Local Area Network (WLAN), etc. As an example of this, it is possible to provide,
The memory 63 may be, but is not limited to, a read-only memory (ROM) or other type of static storage device that may store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that may store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, optical disk storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory may be self-contained and connected to the processing unit by a bus. The memory may also be integrated with the processing unit.
The memory 63 is used for storing application program codes for executing the disclosed solution, and is controlled by the processor 61. The processor 61 is configured to execute application program code stored in the memory 63 to implement the functions in the disclosed method.
In particular implementations, processor 61 may include one or more CPUs such as CPU0 and CPU1 in fig. 8 as one embodiment.
In a particular implementation, the terminal may include multiple processors, such as processor 61 and processor 65 in fig. 8, as an example. Each of these processors may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. A processor herein may refer to one or more devices, circuits, and/or processing cores that process data (e.g., computer program instructions).
In one implementation, the terminal may further include an input device 66 and an output device 67, as one example. The input device 66 is in communication with the output device 67 and may accept user input in a variety of ways. For example, the input device 66 may be a mouse, keyboard, touch screen device, or sensing device, among others. The output device 67 is in communication with the processor 61 and may display information in a variety of ways. For example, the output device 67 may be a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display device, or the like.
Those skilled in the art will appreciate that the configuration shown in fig. 8 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components may be used.
The embodiment of the disclosure also provides a server. Fig. 9 shows a schematic structural diagram of a server provided in an embodiment of the present disclosure. The server may be an information processing apparatus of a multimedia resource. The server, which may vary considerably due to configuration or performance, may include one or more processors 71 and one or more memories 72. At least one instruction is stored in the memory 72, and the at least one instruction is loaded and executed by the processor 71 to implement the information processing method for multimedia resources provided by the above method embodiments. Certainly, the server may further have a wired or wireless network interface, a keyboard, an input/output interface, and other components to facilitate input and output, and the server may further include other components for implementing functions of the device, which are not described herein again.
The present disclosure also provides a computer-readable storage medium including instructions stored thereon, which, when executed by a processor of a computer device, enable a computer to perform the information processing method of a multimedia asset provided by the above-described illustrated embodiment. For example, the computer readable storage medium may be a memory 63 comprising instructions executable by the processor 61 of the terminal to perform the above-described method. Also for example, the computer readable storage medium may be a memory 72 comprising instructions executable by the processor 71 of the server to perform the above-described method. Alternatively, the computer readable storage medium may be a non-transitory computer readable storage medium, for example, which may be a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
The present disclosure also provides a computer program product, which includes computer instructions, when the computer instructions are run on an electronic device, the electronic device is caused to execute the information processing method for a multimedia resource shown in any one of the above-mentioned fig. 1 to 6.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice in the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims (10)

1. An information processing method for multimedia resources is characterized by comprising the following steps:
Acquiring characteristic information of a target account; the target account includes: the account which performs interactive operation on the multimedia resource to be processed in the first time period; the characteristic information of the target account comprises: identification characteristic information and behavior characteristic information of the target account; the behavior characteristic information of the target account is used for representing the interactive behavior executed by the target account on the multimedia resource to be processed in the first time period;
inputting the characteristic information of the target account into a pre-trained target model to obtain an interaction parameter of the multimedia resource to be processed at a first moment; the target model is obtained by training according to the characteristic information of the sample account; the sample account includes: an account on which the interactive operation has been performed on the sample multimedia resources within a second time period; the characteristic information of the sample account comprises: identification feature information and behavior feature information of the sample account; the behavior characteristic information of the sample account is used for representing the interactive behavior executed by the sample account on the sample multimedia resource in the second time period; the first time is after the first time period.
2. The method for processing the information of the multimedia resource according to claim 1, further comprising:
acquiring identification characteristic information of the sample account and behavior characteristic information of the sample account;
and training to obtain the target model according to the identification characteristic information of the sample account, the behavior characteristic information of the sample account and a preset model.
3. The information processing method of a multimedia resource according to claim 2, wherein the sample accounts include a positive sample account and a negative sample account;
the obtaining the identification characteristic information of the sample account and the behavior characteristic information of the sample account includes:
acquiring the number of times that the sample multimedia resource is subjected to the interactive operation at a second moment; the second time is after the second time period;
determining the positive sample account and the negative sample account according to the number of times the sample multimedia resource is subjected to the interactive operation at the second moment;
and determining the combination of the identification characteristic information of the positive sample account and the identification characteristic information of the negative sample account as the identification characteristic information of the sample account, and determining the combination of the behavior characteristic information of the positive sample account and the behavior characteristic information of the negative sample account as the behavior characteristic information of the sample account.
4. The method for processing the information of the multimedia resource according to claim 3, wherein the determining the positive sample account and the negative sample account according to the number of times the sample multimedia resource is executed with the interactive operation at the second time comprises:
determining sample multimedia resources, of the sample multimedia resources, of which the times of the interactive operation executed at the second moment is greater than a preset time, as positive sample multimedia resources;
determining the account performing the interaction operation on the positive sample multimedia resource in the second time period as the positive sample account;
determining sample multimedia resources of which the times of the interactive operation executed at the second moment are less than or equal to the preset times as negative sample multimedia resources;
and determining the account which performs the interaction operation on the negative sample multimedia resource in the second time period as the negative sample account.
5. The method as claimed in claim 2, wherein the predetermined model comprises: a logistic regression model; the training according to the identification feature information of the sample account, the behavior feature information of the sample account and a preset model to obtain the target model comprises:
Training the identification characteristic information of the sample account and the behavior characteristic information of the sample account according to the logistic regression model to obtain a model to be adjusted;
and performing L1 regularization processing and orthogonal regularization processing on the model to be adjusted to obtain the target model.
6. The method for processing the information of the multimedia resource according to any one of claims 1 to 5, wherein after the inputting the feature information of the target account into a pre-trained target model to obtain the interaction parameters of the multimedia resource to be processed at the first time, the method further comprises:
and recommending the multimedia resource to be processed to an audience account when the interactive parameter of the multimedia resource to be processed at the first moment meets a preset condition.
7. An information processing apparatus of a multimedia resource, characterized by comprising: an acquisition unit and a processing unit;
the acquisition unit is used for acquiring the characteristic information of the target account; the target account includes: the account which performs interactive operation on the multimedia resource to be processed in the first time period; the characteristic information of the target account comprises: identification characteristic information and behavior characteristic information of the target account; the behavior characteristic information of the target account is used for representing the interactive behavior executed by the target account on the multimedia resource to be processed in the first time period;
The processing unit is used for inputting the characteristic information of the target account into a pre-trained target model to obtain the interaction parameters of the multimedia resource to be processed at a first moment; the target model is obtained by training according to the characteristic information of the sample account; the sample account includes: an account for which the interaction was performed on sample multimedia assets over a second time period; the characteristic information of the sample account comprises: identification characteristic information and behavior characteristic information of the sample account; the behavior characteristic information of the sample account is used for representing the interactive behavior executed on the sample multimedia resource by the sample account in the second time period; the first time is after the first time period.
8. An electronic device, characterized in that the electronic device comprises:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the information processing method of the multimedia resource according to any one of claims 1 to 6.
9. A computer-readable storage medium having instructions stored thereon, wherein the instructions in the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the information processing method of a multimedia asset as claimed in any one of claims 1-6.
10. A computer program product comprising instructions for causing an electronic device to perform the method of information processing of a multimedia asset according to any of claims 1-6, when said instructions are run on said electronic device.
CN202210267772.6A 2022-03-17 2022-03-17 Information processing method, device and equipment of multimedia resource and storage medium Pending CN114676272A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115129988A (en) * 2022-06-29 2022-09-30 北京达佳互联信息技术有限公司 Information acquisition method and device, electronic equipment and storage medium

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115129988A (en) * 2022-06-29 2022-09-30 北京达佳互联信息技术有限公司 Information acquisition method and device, electronic equipment and storage medium

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