CN111125572B - Method and device for processing information - Google Patents

Method and device for processing information Download PDF

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CN111125572B
CN111125572B CN201811287898.XA CN201811287898A CN111125572B CN 111125572 B CN111125572 B CN 111125572B CN 201811287898 A CN201811287898 A CN 201811287898A CN 111125572 B CN111125572 B CN 111125572B
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information
presented
value
sample presentation
sample
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CN111125572A (en
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龙睿
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Beijing ByteDance Network Technology Co Ltd
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Beijing ByteDance Network Technology Co Ltd
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Abstract

The embodiment of the application discloses a method and a device for processing information. One embodiment of the method comprises the following steps: acquiring an information set to be presented; for information to be presented in the information to be presented set, executing the following steps: determining a first value for characterizing the value of the information to be presented; generating a target value for representing the quality degree of the information to be presented based on the determined first value; and selecting information to be presented from the information set to be presented as information for presentation based on the generated target value. The embodiment improves the pertinence and the diversity of information processing; and, utilize the first numerical value used for representing the value of the information to be presented, confirm the goodness of the information to be presented, can improve the accuracy of information processing.

Description

Method and device for processing information
Technical Field
Embodiments of the present application relate to the field of computer technology, and in particular, to a method and apparatus for processing information.
Background
With the development of technology, people can browse news, advertisement and other presentation information by using electronic devices such as mobile phones and computers.
In general, a technician may predetermine a plurality of information to be presented to a user. Further, one piece of information to be presented can be selected from a plurality of pieces of information to be presented as information for presentation finally presented to the user.
Disclosure of Invention
The embodiment of the application provides a method and a device for processing information.
In a first aspect, embodiments of the present application provide a method for processing information, the method including: acquiring an information set to be presented; for information to be presented in the information to be presented set, executing the following steps: determining a first value for characterizing the value of the information to be presented; generating a target value for representing the quality degree of the information to be presented based on the determined first value; and selecting information to be presented from the information set to be presented as information for presentation based on the generated target value.
In some embodiments, before generating the target value for characterizing the goodness of the information to be presented based on the determined first value, the method further comprises: acquiring value data predetermined for the information to be presented; determining a second value representing a value of presenting the information to be presented based on the acquired value data; and generating a target value for characterizing the quality of the information to be presented based on the determined first value, comprising: based on the determined first and second values, a target value is generated that characterizes the extent of the information to be presented.
In some embodiments, the information to be presented corresponds to a page to be presented, and is used for clicking by a user to present the page to be presented corresponding to the clicked information to be presented to the user; and determining, based on the obtained value data, a second value for characterizing the value of presenting the information to be presented, comprising: inputting the information to be presented into a pre-trained click rate estimation model to obtain an estimation result; and determining a second value used for representing the value of the information to be presented based on the obtained estimated result and the value data corresponding to the information to be presented.
In some embodiments, generating a target value for characterizing the goodness of the information to be presented based on the determined first value and second value comprises: and carrying out weighted summation processing on the first numerical value and the second numerical value corresponding to the information to be presented based on the weight pre-allocated for the first numerical value and the second numerical value, and obtaining a processing result as a target numerical value for representing the quality degree of the information to be presented.
In some embodiments, determining a first value for characterizing the value of the information to be presented comprises: the information to be presented is input into a pre-trained value model, and a first value used for representing the value of the information to be presented is obtained.
In some embodiments, the value model includes a first value model, the first value model being trained by: acquiring a sample presentation information set which is composed of sample presentation information and is output to a user terminal connected with communication in a preset time period and used for presenting to a user using the user terminal; for sample presentation information in the sample presentation information set, performing the steps of: determining a time length for a user to browse the sample presentation information by using the user terminal, and determining a first numerical value corresponding to the sample presentation information based on the determined time length; forming a training sample by using the sample presentation information and a first numerical value corresponding to the sample presentation information; and using a machine learning method, taking sample presentation information included in training samples in the formed training samples as input, taking a first numerical value corresponding to the input sample presentation information as expected output, and training to obtain a first numerical value model.
In some embodiments, the value model comprises a second value model, the second value model being trained by: acquiring a sample presentation information set which is composed of sample presentation information output to a user terminal connected with communication and used for presenting to a user using the user terminal in a preset time period, wherein the sample presentation information is information in a sample window positioned on a sample page; for sample presentation information in the sample presentation information set, performing the steps of: determining the probability of a user executing a preset operation on the sample presentation information by using a user terminal, and determining a first numerical value corresponding to the sample presentation information based on the determined probability, wherein the preset operation is to close a sample window comprising the sample presentation information on a sample page corresponding to the sample presentation information; forming a training sample by using the sample presentation information and a first numerical value corresponding to the sample presentation information; and (3) using a machine learning method, taking sample presentation information included in training samples in the formed training samples as input, taking a first numerical value corresponding to the input sample presentation information as expected output, and training to obtain a second numerical value model.
In some embodiments, selecting information to be presented from the set of information to be presented as information for presentation based on the generated target value includes: ordering the information to be presented in the information set to be presented according to the size sequence of the generated target values to obtain an information sequence to be presented; and selecting the information to be presented from the information sequence to be presented as information for presentation.
In a second aspect, embodiments of the present application provide an apparatus for processing information, the apparatus comprising: an information acquisition unit configured to acquire a set of information to be presented; a numerical value generating unit configured to perform the following steps for information to be presented in the information to be presented set: determining a first value for characterizing the value of the information to be presented; generating a target value for representing the quality degree of the information to be presented based on the determined first value; and an information selecting unit configured to select information to be presented from the information set to be presented as information for presentation based on the generated target value.
In some embodiments, the value generation unit is further configured to: acquiring value data predetermined for the information to be presented; determining a second value representing a value of presenting the information to be presented based on the acquired value data; and generating a target value for representing the quality degree of the information to be presented based on the determined first value and the second value.
In some embodiments, the information to be presented corresponds to a page to be presented, and is used for clicking by a user to present the page to be presented corresponding to the clicked information to be presented to the user; and the value generation unit is further configured to: inputting the information to be presented into a pre-trained click rate estimation model to obtain an estimation result; and determining a second value used for representing the value of the information to be presented based on the obtained estimated result and the value data corresponding to the information to be presented.
In some embodiments, the value generation unit is further configured to: and carrying out weighted summation processing on the first numerical value and the second numerical value corresponding to the information to be presented based on the weight pre-allocated for the first numerical value and the second numerical value, and obtaining a processing result as a target numerical value for representing the quality degree of the information to be presented.
In some embodiments, the value generation unit is further configured to: the information to be presented is input into a pre-trained value model, and a first value used for representing the value of the information to be presented is obtained.
In some embodiments, the value model includes a first value model, the first value model being trained by: acquiring a sample presentation information set which is composed of sample presentation information and is output to a user terminal connected with communication in a preset time period and used for presenting to a user using the user terminal; for sample presentation information in the sample presentation information set, performing the steps of: determining a time length for a user to browse the sample presentation information by using the user terminal, and determining a first numerical value corresponding to the sample presentation information based on the determined time length; forming a training sample by using the sample presentation information and a first numerical value corresponding to the sample presentation information; and using a machine learning method, taking sample presentation information included in training samples in the formed training samples as input, taking a first numerical value corresponding to the input sample presentation information as expected output, and training to obtain a first numerical value model.
In some embodiments, the value model comprises a second value model, the second value model being trained by: acquiring a sample presentation information set which is composed of sample presentation information output to a user terminal connected with communication and used for presenting to a user using the user terminal in a preset time period, wherein the sample presentation information is information in a sample window positioned on a sample page; for sample presentation information in the sample presentation information set, performing the steps of: determining the probability of a user executing a preset operation on the sample presentation information by using a user terminal, and determining a first numerical value corresponding to the sample presentation information based on the determined probability, wherein the preset operation is to close a sample window comprising the sample presentation information on a sample page corresponding to the sample presentation information; forming a training sample by using the sample presentation information and a first numerical value corresponding to the sample presentation information; and (3) using a machine learning method, taking sample presentation information included in training samples in the formed training samples as input, taking a first numerical value corresponding to the input sample presentation information as expected output, and training to obtain a second numerical value model.
In some embodiments, the information selecting unit includes: the information ordering module is configured to order the information to be presented in the information set to be presented according to the size sequence of the generated target value, so as to obtain an information sequence to be presented; the information selection module is configured to select information to be presented from the information sequence to be presented as information for presentation.
In a third aspect, an embodiment of the present application provides a server, including: one or more processors; and a storage device having one or more programs stored thereon, which when executed by the one or more processors, cause the one or more processors to implement the method of any of the embodiments of the method for processing information described above.
In a fourth aspect, embodiments of the present application provide a computer readable medium having stored thereon a computer program which, when executed by a processor, implements a method of any of the embodiments of the methods for processing information described above.
The method and the device for processing information provided by the embodiment of the application are used for acquiring the information set to be presented, and then executing the following steps for the information to be presented in the information set to be presented: determining a first value for characterizing the value of the information to be presented; based on the determined first numerical value, generating a target numerical value for representing the quality degree of the information to be presented, and finally, based on the generated target numerical value, selecting the information to be presented from the information set to be presented as information for presentation, thereby effectively utilizing the first numerical value for representing the value of the information to be presented, determining the target numerical value for representing the quality degree of the information to be presented, further, based on the target numerical value, selecting better information to be presented from the information set to be presented as information for presentation to a user, and improving the pertinence and diversity of information processing; and, utilize the first numerical value used for representing the value of the information to be presented, confirm the goodness of the information to be presented, can improve the accuracy of information processing.
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Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments, made with reference to the following drawings, in which:
FIG. 1 is an exemplary system architecture diagram in which an embodiment of the present application may be applied;
FIG. 2 is a flow chart of one embodiment of a method for processing information according to the present application;
FIG. 3 is a schematic illustration of one application scenario of a method for processing information according to an embodiment of the present application;
FIG. 4 is a flow chart of yet another embodiment of a method for processing information according to the present application;
FIG. 5 is a schematic structural diagram of one embodiment of an apparatus for processing information according to the present application;
FIG. 6 is a schematic diagram of a computer system suitable for use in implementing embodiments of the present application.
Detailed Description
The present application is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 shows an exemplary system architecture 100 to which embodiments of the methods for processing information or the apparatuses for processing information of the present application may be applied.
As shown in fig. 1, a system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. Various communication client applications, such as a web browser application, a shopping class application, a search class application, an instant messaging tool, a mailbox client, social platform software, etc., may be installed on the terminal devices 101, 102, 103.
The terminal devices 101, 102, 103 may be hardware or software. When the terminal devices 101, 102, 103 are hardware, they may be various electronic devices having a display screen and supporting information transmission, including but not limited to smart phones, tablet computers, electronic book readers, MP3 players (Moving Picture Experts Group Audio Layer III, dynamic video expert compression standard audio plane 3), MP4 (Moving Picture Experts Group Audio Layer IV, dynamic video expert compression standard audio plane 4) players, laptop and desktop computers, and the like. When the terminal devices 101, 102, 103 are software, they can be installed in the above-listed electronic devices. Which may be implemented as multiple software or software modules (e.g., multiple software or software modules for providing distributed services) or as a single software or software module. The present invention is not particularly limited herein.
The server 105 may be a server providing various services, for example, a background server supporting presentation information displayed on the terminal devices 101, 102, 103. The background server can acquire the information set to be presented, analyze and the like data of the information set to be presented, and feed back a processing result (for example, information for presentation) to the terminal device.
It should be noted that, the method for processing information provided in the embodiment of the present application is generally performed by the server 105, and accordingly, the device for processing information is generally disposed in the server 105.
The server may be hardware or software. When the server is hardware, the server may be implemented as a distributed server cluster formed by a plurality of servers, or may be implemented as a single server. When the server is software, it may be implemented as a plurality of software or software modules (e.g., a plurality of software or software modules for providing distributed services), or as a single software or software module. The present invention is not particularly limited herein.
It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation. In the case where data used in the process of obtaining the presentation information does not need to be acquired from a remote place, the above-described system architecture may include no network and terminal devices, but only a server.
With continued reference to fig. 2, a flow 200 of one embodiment of a method for processing information according to the present application is shown. The method for processing information comprises the following steps:
step 201, a set of information to be presented is obtained.
In this embodiment, the execution subject of the method for processing information (e.g., the server shown in fig. 1) may acquire the set of information to be presented through a wired connection or a wireless connection. The information to be presented is information to be presented to the user, and may include, but is not limited to, at least one of the following: text, numbers, pictures, video, links. The set of information to be presented may comprise at least one information to be presented.
Specifically, the executing body may acquire at least one piece of information to be presented, which is stored locally in advance, to form an information set to be presented; at least one information to be presented sent by the electronic device (for example, the terminal device shown in fig. 1) in communication connection may also be acquired to form a set of information to be presented.
Step 202, for information to be presented in the information to be presented set, executing the following steps: determining a first value for characterizing the value of the information to be presented; based on the determined first value, a target value is generated that characterizes the extent of the merit of the information to be presented.
In this embodiment, for the information to be presented in the information to be presented set obtained in step 201, the executing body may execute the following steps:
step 2021, determining a first value for characterizing the value of the information to be presented.
The value of the information to be presented can be represented by an effect generated by browsing the content of the information to be presented by the user. The first value may be used to characterize the value of the information to be presented, and the larger the value, the higher the value that may be characterized. Here, the above-described executing entity may determine the first value for characterizing the value of the information to be presented in various ways.
As an example, the information to be presented includes text information, and the executing entity may determine the number of words included in the information to be presented, and determine the first value for characterizing the value of the information to be presented based on the determined number. For example, the executing entity may directly determine the determined number as a first value for characterizing the value of the information to be presented; alternatively, the determined number and the preset value may be integrated, and the obtained integrated result is determined as the first value for characterizing the value of the information to be presented. It can be understood that the more characters included in the information to be presented, the longer the user browses the information to be presented, and further, the longer the user can stay on the page where the information to be presented is located, so that the higher the value of the information to be presented is.
In some optional implementations of this embodiment, the executing entity may determine the first value for characterizing the value of the information to be presented by: the information to be presented is input into a pre-trained value model, and a first value used for representing the value of the information to be presented is obtained.
Wherein the value model may be used for characterizing a correspondence of information to be presented and a first value for characterizing a value of the information to be presented. Specifically, as an example, the value model may be a correspondence table that is preset by a technician based on statistics of a large amount of information to be presented and first values corresponding to the information to be presented, and stores a plurality of information to be presented and corresponding first values; the model obtained by training the initial model (for example, a neural network) by using a machine learning method can also be a model obtained by training the initial model based on a preset training sample.
In some alternative implementations of the present embodiment, the value model may include a first value model. The first value model may be used to characterize a correspondence of information to be presented and a first value used to characterize a value of the information to be presented. Specifically, the first valence model is obtained through training the following steps:
First, a sample presentation information set composed of sample presentation information to be presented to a user using a user terminal, which is output to a user terminal connected to a communication in a preset period of time, is acquired.
The sample presentation information set may include a plurality of pieces of sample presentation information. The information for sample presentation is information selected from a set of information to be presented by the sample. The preset time period may be a time period predetermined by a technician (e.g., one month). The user terminal of the communication connection may comprise at least one.
Then, for the sample presentation information in the sample presentation information set, the following steps are performed: determining a time length for a user to browse the sample presentation information by using the user terminal, and determining a first numerical value corresponding to the sample presentation information based on the determined time length; and forming a training sample by using the sample presentation information and the first numerical value corresponding to the sample presentation information.
Here, the time period for which the sample presentation information is displayed on the user terminal may be determined as the time period for which the user browses the sample presentation information using the user terminal.
In this implementation manner, various methods may be adopted to determine, based on the determined duration, a first value corresponding to the information for sample presentation, for example, the determined duration may be directly determined as the first value corresponding to the information for sample presentation; alternatively, the determined duration and the preset value may be subjected to product finding, and the product finding result may be determined as the first value corresponding to the information for sample presentation.
It will be appreciated that a plurality of training samples may be obtained using the sample presentation information set.
And finally, using a machine learning method, taking sample presentation information included in training samples in the formed training samples as input, taking a first numerical value corresponding to the input sample presentation information as expected output, and training to obtain a first numerical value model.
Specifically, the machine learning method may be used to train a predetermined initial model (for example, a neural network) by taking sample presentation information included in training samples among the composed training samples as input, taking a first numerical value corresponding to the input sample presentation information as an expected output, and finally obtaining a first numerical value model.
In some alternative implementations of the present embodiment, the value model may include a second value model. The second value model may be used to characterize a correspondence of information to be presented and a first value used to characterize a value of the information to be presented. Specifically, the second value model is obtained through training by the following steps:
first, a sample presentation information set composed of sample presentation information to be presented to a user using a user terminal, which is output to a user terminal connected to a communication in a preset period of time, is acquired.
Wherein the sample presentation information is information in a sample window located on a sample page. The sample page is a preset page. The sample window is a preset window for presenting information for sample presentation. When a user browses a sample page, a sample window on the sample page may be closed. It will be appreciated that closing the sample window by the user may characterize the user as not interested in the content of the sample presentation information in the sample window.
Then, for the sample presentation information in the sample presentation information set, the following steps are performed: determining the probability of a user executing a preset operation on the sample presentation information by using a user terminal, and determining a first numerical value corresponding to the sample presentation information based on the determined probability; and forming a training sample by using the sample presentation information and the first numerical value corresponding to the sample presentation information.
The preset operation is to close a sample window which comprises the sample presentation information and is on a sample page corresponding to the sample presentation information.
Specifically, whether a user executes a preset operation on the sample presentation information when browsing the sample page can be detected; if the preset operation is executed, determining that the probability of executing the preset operation by the user for the sample presentation information by using the user terminal is 100%; if the preset operation is not performed, the probability may be determined to be 0%.
It can be appreciated that the greater the probability that the user performs a preset operation on the sample presentation information, the less interesting the user is to the sample presentation information, and thus the lower the value of the sample presentation information can be characterized. Thus, in this implementation, the determined probability is inversely related to the first value, i.e. the larger the probability, the smaller the first value. Specifically, a first value corresponding to the sample presentation information may be determined based on the determined probability by various methods, for example, a negative number of the determined probability may be determined as the first value corresponding to the sample presentation information; alternatively, the inverse of the determined probability may be determined as the first value corresponding to the information for sample presentation.
And finally, using a machine learning method, taking sample presentation information included in training samples in the formed training samples as input, taking a first numerical value corresponding to the input sample presentation information as expected output, and training to obtain a second numerical model.
Specifically, the machine learning method may be used to train a predetermined initial model (for example, a neural network) by taking sample presentation information included in training samples among the composed training samples as input, taking a first numerical value corresponding to the input sample presentation information as an expected output, and finally obtaining a second numerical value model.
In addition, the value model may include both the first value model and the second value model.
In practice, the execution subjects of the steps for generating the models (the first value model and the second value model) may be the same as or different from the execution subjects of the method for processing information. If the same is true, the execution subject of the step for generating the model may store the trained model locally after training to obtain the model. If different, the executing entity of the step for generating the model may send the trained model to the executing entity of the method for processing information after training the model.
A step 2022, based on the determined first value, generates a target value for characterizing the extent of the merit of the information to be presented.
The target value is used for representing the quality degree of the information to be presented, and the larger the target value is, the better the information to be presented can be represented.
Specifically, the executing body may directly determine the determined first value as the target value for representing the quality degree of the information to be presented, or may process (for example, multiply by a preset value) the determined first value and determine the processing result as the target value for representing the quality degree of the information to be presented.
And 203, selecting information to be presented from the information set to be presented as information for presentation based on the generated target value.
In this embodiment, based on the target value generated in step 202, the executing body may select information to be presented from the information set to be presented as information for presentation. Wherein the presentation information is information that is ultimately intended for presentation to the user.
Specifically, the execution body may select, based on the generated target value, information to be presented from the information set to be presented as information for presentation by using various methods. For example, the information to be presented with the corresponding target value being greater than or equal to a preset threshold value can be selected from the information set to be presented as information for presentation; or selecting the information to be presented with the maximum corresponding target value from the information set to be presented as the information for presentation.
In some optional implementations of this embodiment, based on the generated target value, the executing entity may further select information to be presented from the set of information to be presented as information for presentation by: firstly, the execution main body can sort the information to be presented in the information to be presented set according to the size sequence of the generated target value, and obtain an information sequence to be presented. Then, the executing body may select information to be presented from the information sequence to be presented as information for presentation.
Specifically, as an example, the execution body may sort the information to be presented in the information set to be presented according to the order of the corresponding target values from large to small, so as to obtain the information sequence to be presented. Further, a preset number (for example, 1) of information to be presented, which is sequenced in front, can be selected from the information sequence to be presented as information for presentation; or the execution main body can sort the information to be presented in the information set to be presented according to the sequence from small to large of the corresponding target value, so as to obtain the information sequence to be presented. Furthermore, a preset number of information to be presented, which is sequenced later, can be selected from the information sequence to be presented as information for presentation.
With continued reference to fig. 3, fig. 3 is a schematic diagram of an application scenario of the method for processing information according to the present embodiment. In the application scenario of fig. 3, the server 301 may first obtain the set of information to be presented 302, where the set of information to be presented 302 may include information to be presented 3021 (e.g., "a-brand cell phone performance re-upgrade") and information to be presented 3022 ("B-brand cell phone price down"). Then, for the information to be presented 3021, the server 301 may perform the steps of: determining a first value 3031 (e.g., "8") for characterizing the value of the information 3021 to be presented; based on the first value 3031, a target value 3041 (for example, "80" (the target value "80" may be obtained by multiplying the first value "8" and the preset value "10)) for characterizing the degree of merit of the information 3021 to be presented is generated. Next, for the information to be presented 3022, the server 301 may similarly perform the steps of: determining a first value 3032 (e.g., "9") for characterizing the value of the information 3022 to be presented; based on the first value 3032, a target value 3042 (e.g., "90" (the target value "90" may be obtained by multiplying the first value "9" and the preset value "10)) for characterizing the degree of merit of the information 3022 to be presented is generated. Finally, the server 301 may select information to be presented from the information set to be presented 302 as information for presentation 305 based on the generated target values 3041, 3042. Specifically, referring to fig. 3, the server 301 may select, from the to-be-presented information set 303, to-be-presented information with a larger target value as the presentation information 305, that is, select to-be-presented information 3022 as the presentation information 305.
In addition, after obtaining the presentation information 305, the server 301 may also send the presentation information 305 to the communicatively connected terminal device 306, for presentation on the terminal device for browsing by a user using the terminal device 306.
The method provided by the embodiment of the application effectively utilizes the first value for representing the value of the information to be presented, determines the target value for representing the quality degree of the information to be presented, and further can select better information to be presented from the information set to be presented as information for presentation to a user based on the target value, thereby improving the pertinence and the diversity of information processing; and, utilize the first numerical value used for representing the value of the information to be presented, confirm the goodness of the information to be presented, can improve the accuracy of information processing.
With further reference to fig. 4, a flow 400 of yet another embodiment of a method for processing information is shown. The flow 400 of the method for processing information comprises the steps of:
step 401, a set of information to be presented is obtained.
In this embodiment, the execution subject of the method for processing information (e.g., the server shown in fig. 1) may acquire the set of information to be presented through a wired connection or a wireless connection. Wherein the information to be presented is information provided by an information provider to be presented to a user, and may include, but is not limited to, at least one of the following: text, numbers, pictures, video, links. The set of information to be presented may comprise at least one information to be presented.
Step 402, for information to be presented in the information to be presented set, performing the following steps: determining a first value for characterizing the value of the information to be presented; acquiring value data predetermined for the information to be presented; determining a second value representing a value of presenting the information to be presented based on the acquired value data; based on the determined first and second values, a target value is generated that characterizes the extent of the information to be presented.
In this embodiment, for the information to be presented in the information to be presented set obtained in step 401, the executing body may execute the following steps:
in step 4021, a first value characterizing the value of the information to be presented is determined.
The value of the information to be presented can be represented by an effect generated by browsing the content of the information to be presented by the user. The first value may be used to characterize the value of the information to be presented, and the larger the value, the higher the value that may be characterized. Here, the method described in step 2021 may be used to determine the first value for characterizing the value of the information to be presented, which is not described herein.
In step 4022, value data predetermined for the information to be presented is obtained.
In practice, when presenting information to be presented provided by an information provider, the information provider needs to pay a corresponding cost, such as an item cost, a monetary cost, an integral cost, and the like. It will be appreciated that the more cost an information provider pays, the higher the value that the information to be presented can be represented. Here, the value data may be used to determine how much the information provider of the information to be presented pays when presenting the information to be presented. For example, the information to be presented includes text information. The value data may be used to characterize the price paid by the information provider of the information to be presented for every thousand words presented.
Step 4023, determining a second value representing the value of presenting the information to be presented based on the obtained value data.
Wherein the second value may be used to characterize the value of the operation of presenting the information to be presented, the larger the value, the higher the value of the characterized information to be presented may be.
In particular, the executing entity may determine, based on the obtained value data, a second value for characterizing the value of presenting the information to be presented in various ways. For example, when the value data is used to represent 1000 words per presentation, the execution entity may determine the number of words included in the information to be presented, then quotient the determined number and the number 1000, multiply the quotient result by a cost value (e.g., price) represented by the value data, to obtain a total cost value corresponding to the information to be presented, and further determine a second value representing the value of presenting the information to be presented by using the total cost value corresponding to the information to be presented.
As an example, the total cost value corresponding to the information to be presented may be directly determined as a second value for characterizing the value of presenting the information to be presented; alternatively, the total cost value corresponding to the information to be presented may be processed (e.g., multiplied by a preset value), and the processing result may be determined as a second value for characterizing the value of presenting the information to be presented.
In some optional implementations of this embodiment, the information to be presented corresponds to a page to be presented, and is used for clicking by the user to present the page to be presented corresponding to the clicked information to be presented to the user. Furthermore, the value data may be used to characterize the cost paid by the information provider of the information to be presented every time the user clicks the information to be presented when the number of presentations of the information to be presented is a preset number. And, the executing entity may determine, based on the obtained value data, a second value for characterizing the value of presenting the information to be presented by:
firstly, the executing body can input the information to be presented into a pre-trained click rate estimation model to obtain an estimation result.
The predicted result may be used to characterize a predicted click rate corresponding to the information to be presented. The predicted click rate is a result obtained by predicting the click rate. The click rate is also called click through rate (CTR, click Through Rate) for indicating a ratio of the number of times information to be presented is clicked to the number of times information to be presented is presented. The click rate estimation model can be used for representing the corresponding relation between the information to be presented and the estimation result. The click rate estimation model may be a model that is trained on the initial model. The initial model may include, but is not limited to, at least one of the following: FM (Factorization Machine, factorer) model, FFM (Field-aware Factorization Machine, field-aware factorer), neural network model, and the like.
It should be noted that, the method for obtaining the click rate estimation model through training is a well-known technique widely studied and applied at present, and will not be described here.
Then, the executing body may determine a second value for representing the value of presenting the information to be presented based on the obtained estimated result and the value data corresponding to the information to be presented.
Specifically, the executing body may determine, by using various methods, a second value for representing the value of the information to be presented based on the obtained estimated result and the value data corresponding to the information to be presented. For example, when the number of times of presenting the information to be presented is 1000 times, the user clicks once, and the cost (for example, price) paid by the information provider of the information to be presented is paid, the executing body may product the obtained estimated result and the number of times 1000, determine the number of times of being clicked of the information to be presented in the process of presenting the information to be presented 1000 times, further product the number of times of being clicked and the cost value (for example, price) represented by the value data, obtain the total cost value corresponding to the information to be presented, and finally determine the second value for representing the value of presenting the information to be presented by using the total cost value corresponding to the information to be presented.
As an example, the total cost value corresponding to the information to be presented may be directly determined as a second value for characterizing the value of presenting the information to be presented; alternatively, the total cost value corresponding to the information to be presented may be processed (e.g., multiplied by a preset value), and the processing result may be determined as a second value for characterizing the value of presenting the information to be presented.
In step 4024, a target value for characterizing the quality of the information to be presented is generated based on the determined first value and second value.
The target value is used for representing the quality degree of the information to be presented, and the larger the target value is, the better the information to be presented can be represented.
Specifically, the executing body may generate the target value for representing the quality of the information to be presented by using various methods based on the determined first value and the second value. For example, the determined first and second values may be summed, and the result of the summation determined as a target value for characterizing the degree of merit of the information to be presented.
In some optional implementations of this embodiment, the executing entity may generate the target value for characterizing the quality of the information to be presented based on the determined first value and the second value by: the execution body may perform weighted summation processing on the first value and the second value corresponding to the information to be presented based on the weights pre-allocated to the first value and the second value, so as to obtain a processing result as a target value for representing the quality degree of the information to be presented.
And step 403, selecting information to be presented from the information set to be presented as information for presentation based on the generated target value.
In this embodiment, based on the target value generated in step 402, the executing entity may select information to be presented from the information set to be presented as information for presentation. Wherein the presentation information is information that is ultimately intended for presentation to the user.
As can be seen from fig. 4, compared with the embodiment corresponding to fig. 2, the flow 400 of the method for processing information in this embodiment highlights the step of determining the target value corresponding to the information to be presented by using the first value and the second value corresponding to the information to be presented. Therefore, the scheme described in the embodiment can introduce more data related to the quality degree of the information to be presented, so that the accuracy of the determined target value can be improved.
With further reference to fig. 5, as an implementation of the method shown in the foregoing figures, the present application provides an embodiment of an apparatus for processing information, where the embodiment of the apparatus corresponds to the embodiment of the method shown in fig. 2, and the apparatus may be specifically applied to various electronic devices.
As shown in fig. 5, the apparatus 500 for processing information of the present embodiment includes: an information acquisition unit 501, a value generation unit 502, and an information selection unit 503. Wherein the information acquisition unit 501 is configured to acquire a set of information to be presented; the value generation unit 502 is configured to perform the following steps for information to be presented in the set of information to be presented: determining a first value for characterizing the value of the information to be presented; generating a target value for representing the quality degree of the information to be presented based on the determined first value; the information selecting unit 503 is configured to select information to be presented from a set of information to be presented as information for presentation based on the generated target value.
In the present embodiment, the information acquisition unit 501 of the apparatus for processing information may acquire the set of information to be presented by a wired connection manner or a wireless connection manner. The information to be presented is information to be presented to the user, and may include, but is not limited to, at least one of the following: text, numbers, pictures, video, links. The set of information to be presented may comprise at least one information to be presented.
In this embodiment, for information to be presented in the information to be presented set obtained by the information obtaining unit 501, the value generating unit 502 may perform the following steps:
a first value characterizing the value of the information to be presented is determined 5021.
The value of the information to be presented can be represented by an effect generated by browsing the content of the information to be presented by the user. The first value may be used to characterize the value of the information to be presented, and the larger the value, the higher the value that may be characterized. Here, the above-described executing entity may determine the first value for characterizing the value of the information to be presented in various ways.
In step 5022, a target value for characterizing the quality of the information to be presented is generated based on the determined first value.
The target value is used for representing the quality degree of the information to be presented, and the larger the target value is, the better the information to be presented can be represented.
In the present embodiment, the information selecting unit 503 may select information to be presented from the information set to be presented as information for presentation based on the target value generated by the value generating unit 502. Wherein the presentation information is information that is ultimately intended for presentation to the user.
In some optional implementations of the present embodiment, the value generation unit 502 may be further configured to: acquiring value data predetermined for the information to be presented; determining a second value representing a value of presenting the information to be presented based on the acquired value data; and generating a target value for representing the quality degree of the information to be presented based on the determined first value and the second value.
In some optional implementations of this embodiment, the information to be presented corresponds to a page to be presented, and is used for clicking by a user to present the page to be presented corresponding to the clicked information to be presented to the user; and the value generation unit 502 may be further configured to: inputting the information to be presented into a pre-trained click rate estimation model to obtain an estimation result; and determining a second value used for representing the value of the information to be presented based on the obtained estimated result and the value data corresponding to the information to be presented.
In some optional implementations of the present embodiment, the value generation unit 502 may be further configured to: and carrying out weighted summation processing on the first numerical value and the second numerical value corresponding to the information to be presented based on the weight pre-allocated for the first numerical value and the second numerical value, and obtaining a processing result as a target numerical value for representing the quality degree of the information to be presented.
In some optional implementations of the present embodiment, the value generation unit 502 may be further configured to: the information to be presented is input into a pre-trained value model, and a first value used for representing the value of the information to be presented is obtained.
In some alternative implementations of the present embodiment, the value model includes a first value model that is trained by: acquiring a sample presentation information set which is composed of sample presentation information and is output to a user terminal connected with communication in a preset time period and used for presenting to a user using the user terminal; for sample presentation information in the sample presentation information set, performing the steps of: determining a time length for a user to browse the sample presentation information by using the user terminal, and determining a first numerical value corresponding to the sample presentation information based on the determined time length; forming a training sample by using the sample presentation information and a first numerical value corresponding to the sample presentation information; and using a machine learning method, taking sample presentation information included in training samples in the formed training samples as input, taking a first numerical value corresponding to the input sample presentation information as expected output, and training to obtain a first numerical value model.
In some alternative implementations of the present embodiment, the value model includes a second value model that is trained by: acquiring a sample presentation information set which is composed of sample presentation information output to a user terminal connected with communication and used for presenting to a user using the user terminal in a preset time period, wherein the sample presentation information is information in a sample window positioned on a sample page; for sample presentation information in the sample presentation information set, performing the steps of: determining the probability of a user executing a preset operation on the sample presentation information by using a user terminal, and determining a first numerical value corresponding to the sample presentation information based on the determined probability, wherein the preset operation is to close a sample window comprising the sample presentation information on a sample page corresponding to the sample presentation information; forming a training sample by using the sample presentation information and a first numerical value corresponding to the sample presentation information; and (3) using a machine learning method, taking sample presentation information included in training samples in the formed training samples as input, taking a first numerical value corresponding to the input sample presentation information as expected output, and training to obtain a second numerical value model.
In some optional implementations of the present embodiment, the information selecting unit 503 may include: an information ordering module (not shown in the figure) configured to order the information to be presented in the information set to be presented according to the size sequence of the generated target values, so as to obtain an information sequence to be presented; an information selection module (not shown in the figure) is configured to select information to be presented from the information sequence to be presented as information for presentation.
It will be appreciated that the elements described in the apparatus 500 correspond to the various steps in the method described with reference to fig. 2. Thus, the operations, features and resulting benefits described above with respect to the method are equally applicable to the apparatus 500 and the units contained therein, and are not described in detail herein.
The device 500 provided in the above embodiment of the present application effectively uses the first value for representing the value of the information to be presented, determines the target value for representing the quality degree of the information to be presented, and further, can select the better information to be presented from the information set to be presented as the information for presentation to the user based on the target value, thereby improving the pertinence and diversity of information processing; and, utilize the first numerical value used for representing the value of the information to be presented, confirm the goodness of the information to be presented, can improve the accuracy of information processing.
Referring now to FIG. 6, there is illustrated a schematic diagram of a computer system 600 suitable for use in implementing a server of an embodiment of the present application. The server illustrated in fig. 6 is merely an example, and should not be construed as limiting the functionality and scope of use of the embodiments herein.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU) 601, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the system 600 are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other through a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, mouse, etc.; an output portion 607 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The drive 610 is also connected to the I/O interface 605 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on drive 610 so that a computer program read therefrom is installed as needed into storage section 608.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 609, and/or installed from the removable medium 611. The above-described functions defined in the method of the present application are performed when the computer program is executed by a Central Processing Unit (CPU) 601. It should be noted that, the computer readable medium described in the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having 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 portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present application may be implemented by software, or may be implemented by hardware. The described units may also be provided in a processor, for example, described as: a processor includes an information acquisition unit, a value generation unit, and an information selection unit. The names of these units do not constitute a limitation on the unit itself in some cases, and for example, the information acquisition unit may also be described as "a unit that acquires information to be presented".
As another aspect, the present application also provides a computer-readable medium that may be contained in the server described in the above embodiment; or may exist alone without being assembled into the server. The computer readable medium carries one or more programs which, when executed by the server, cause the server to: acquiring an information set to be presented; for information to be presented in the information to be presented set, executing the following steps: determining a first value for characterizing the value of the information to be presented; generating a target value for representing the quality degree of the information to be presented based on the determined first value; and selecting information to be presented from the information set to be presented as information for presentation based on the generated target value.
The foregoing description is only of the preferred embodiments of the present application and is presented as a description of the principles of the technology being utilized. It will be appreciated by persons skilled in the art that the scope of the invention referred to in this application is not limited to the specific combinations of features described above, but it is intended to cover other embodiments in which any combination of features described above or equivalents thereof is possible without departing from the spirit of the invention. Such as the above-described features and technical features having similar functions (but not limited to) disclosed in the present application are replaced with each other.

Claims (16)

1. A method for processing information, comprising:
acquiring an information set to be presented;
for the information to be presented in the information to be presented set, executing the following steps: determining a first value used for representing the value of the information to be presented, wherein the value of the information to be presented is used for representing the effect generated by browsing the content of the information to be presented by a user;
acquiring value data predetermined for the information to be presented, wherein the value data is used for determining the cost of an information provider of the information to be presented when the information to be presented is presented;
determining a second value representing a value of presenting the information to be presented based on the acquired value data;
generating a target value for representing the quality degree of the information to be presented based on the determined first value and second value;
selecting information to be presented from the information set to be presented as information for presentation based on the generated target value;
the determining, based on the obtained value data, a second value for characterizing the value of presenting the information to be presented, comprising:
inputting the information to be presented into a pre-trained click rate estimation model to obtain an estimation result;
And determining a second value used for representing the value of the information to be presented based on the obtained estimated result and the value data corresponding to the information to be presented.
2. The method of claim 1, wherein the information to be presented corresponds to a page to be presented for clicking by a user to present the page to be presented corresponding to the clicked information to be presented to the user.
3. The method of claim 1, wherein the generating a target value for characterizing the goodness of the information to be presented based on the determined first value and second value comprises:
and carrying out weighted summation processing on the first numerical value and the second numerical value corresponding to the information to be presented based on the weight pre-allocated for the first numerical value and the second numerical value, and obtaining a processing result as a target numerical value for representing the quality degree of the information to be presented.
4. The method of claim 1, wherein the determining a first value for characterizing the value of the information to be presented comprises:
the information to be presented is input into a pre-trained value model, and a first value used for representing the value of the information to be presented is obtained.
5. The method of claim 4, wherein the value model comprises a first value model trained by:
Acquiring a sample presentation information set which is composed of sample presentation information and is output to a user terminal connected with communication in a preset time period and used for presenting to a user using the user terminal;
for the sample presentation information in the sample presentation information set, performing the steps of: determining a time length for a user to browse the sample presentation information by using the user terminal, and determining a first numerical value corresponding to the sample presentation information based on the determined time length; forming a training sample by using the sample presentation information and a first numerical value corresponding to the sample presentation information;
and using a machine learning method, taking sample presentation information included in training samples in the formed training samples as input, taking a first numerical value corresponding to the input sample presentation information as expected output, and training to obtain a first numerical value model.
6. The method of claim 4, wherein the value model comprises a second value model trained by:
acquiring a sample presentation information set which is composed of sample presentation information output to a user terminal connected with communication and used for presenting to a user using the user terminal in a preset time period, wherein the sample presentation information is information in a sample window positioned on a sample page;
For the sample presentation information in the sample presentation information set, performing the steps of: determining the probability of a user executing a preset operation on the sample presentation information by using a user terminal, and determining a first numerical value corresponding to the sample presentation information based on the determined probability, wherein the preset operation is to close a sample window comprising the sample presentation information on a sample page corresponding to the sample presentation information; forming a training sample by using the sample presentation information and a first numerical value corresponding to the sample presentation information;
and (3) using a machine learning method, taking sample presentation information included in training samples in the formed training samples as input, taking a first numerical value corresponding to the input sample presentation information as expected output, and training to obtain a second numerical value model.
7. The method according to one of claims 1-6, wherein the selecting information to be presented from the set of information to be presented as information for presentation based on the generated target value comprises:
ordering the information to be presented in the information set to be presented according to the size sequence of the generated target values to obtain an information sequence to be presented;
And selecting the information to be presented from the information sequence to be presented as information for presentation.
8. An apparatus for processing information, comprising:
an information acquisition unit configured to acquire a set of information to be presented;
a numerical value generating unit configured to perform the following steps for information to be presented in the information to be presented set: determining a first value for characterizing the value of the information to be presented; generating a target value for representing the quality degree of the information to be presented based on the determined first value, wherein the value of the information to be presented is used for representing the effect generated by browsing the content of the information to be presented by a user;
an information selecting unit configured to select information to be presented from the information set to be presented as information for presentation based on the generated target value;
the value generation unit is further configured to:
acquiring value data predetermined for the information to be presented, wherein the value data is used for determining the cost of an information provider of the information to be presented when the information to be presented is presented;
determining a second value representing a value of presenting the information to be presented based on the acquired value data;
Generating a target value for representing the quality degree of the information to be presented based on the determined first value and second value;
the value generation unit is further configured to:
inputting the information to be presented into a pre-trained click rate estimation model to obtain an estimation result;
and determining a second value used for representing the value of the information to be presented based on the obtained estimated result and the value data corresponding to the information to be presented.
9. The apparatus of claim 8, wherein the information to be presented corresponds to a page to be presented for clicking by a user to present the page to be presented to which the clicked information to be presented corresponds to the user.
10. The apparatus of claim 8, wherein the value generation unit is further configured to:
and carrying out weighted summation processing on the first numerical value and the second numerical value corresponding to the information to be presented based on the weight pre-allocated for the first numerical value and the second numerical value, and obtaining a processing result as a target numerical value for representing the quality degree of the information to be presented.
11. The apparatus of claim 8, wherein the value generation unit is further configured to:
the information to be presented is input into a pre-trained value model, and a first value used for representing the value of the information to be presented is obtained.
12. The apparatus of claim 11, wherein the value model comprises a first value model trained by:
acquiring a sample presentation information set which is composed of sample presentation information and is output to a user terminal connected with communication in a preset time period and used for presenting to a user using the user terminal;
for the sample presentation information in the sample presentation information set, performing the steps of: determining a time length for a user to browse the sample presentation information by using the user terminal, and determining a first numerical value corresponding to the sample presentation information based on the determined time length; forming a training sample by using the sample presentation information and a first numerical value corresponding to the sample presentation information;
and using a machine learning method, taking sample presentation information included in training samples in the formed training samples as input, taking a first numerical value corresponding to the input sample presentation information as expected output, and training to obtain a first numerical value model.
13. The apparatus of claim 11, wherein the value model comprises a second value model trained by:
Acquiring a sample presentation information set which is composed of sample presentation information output to a user terminal connected with communication and used for presenting to a user using the user terminal in a preset time period, wherein the sample presentation information is information in a sample window positioned on a sample page;
for the sample presentation information in the sample presentation information set, performing the steps of: determining the probability of a user executing a preset operation on the sample presentation information by using a user terminal, and determining a first numerical value corresponding to the sample presentation information based on the determined probability, wherein the preset operation is to close a sample window comprising the sample presentation information on a sample page corresponding to the sample presentation information; forming a training sample by using the sample presentation information and a first numerical value corresponding to the sample presentation information;
and (3) using a machine learning method, taking sample presentation information included in training samples in the formed training samples as input, taking a first numerical value corresponding to the input sample presentation information as expected output, and training to obtain a second numerical value model.
14. The apparatus according to one of claims 8-13, wherein the information selection unit comprises:
The information ordering module is configured to order the information to be presented in the information set to be presented according to the size sequence of the generated target value, so as to obtain an information sequence to be presented;
and the information selection module is configured to select information to be presented from the information sequence to be presented as information for presentation.
15. A server, comprising:
one or more processors;
a storage device having one or more programs stored thereon,
when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-7.
16. A computer readable medium having stored thereon a computer program, wherein the program when executed by a processor implements the method of any of claims 1-7.
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