CN113139129B - Virtual reading trajectory graph generation method and device, electronic equipment and storage medium - Google Patents
Virtual reading trajectory graph generation method and device, electronic equipment and storage medium Download PDFInfo
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
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Abstract
The invention relates to a data analysis technology, and discloses a virtual reading trajectory graph generation method, which comprises the following steps: converting the existing information data into an information image; converting the historical reading track into a track vector to mark the information image, so as to obtain a first track image; performing reading track analysis on the first track image by using the countermeasure generation network to obtain a second track image; and when the coincidence degree of the first track image and the second track image is not greater than a preset threshold, adjusting parameters of the countermeasure generation network, and when the coincidence degree is greater than the preset threshold, performing reading track analysis on the information data to be analyzed by using the countermeasure generation network to obtain a virtual reading track diagram of the user. In addition, the invention also relates to a blockchain technology, and existing resource data can be stored in nodes of the blockchain. The invention also provides a virtual reading trajectory graph generating device, equipment and a medium. The invention can solve the problem of lower accuracy when analyzing the preference information of the user.
Description
Technical Field
The present invention relates to the field of data analysis technologies, and in particular, to a virtual reading trajectory graph generating method, a virtual reading trajectory graph generating device, an electronic device, and a computer readable storage medium.
Background
With the advent of the big data age, companies or enterprises have been pushing massive amounts of information, such as various news, books, advertisements, etc., to people. Because the demands of people are different, the information required by each person is different, so that the information pusher is difficult to quickly find the information preferred by the user.
The existing user preference analysis is often based on preference analysis of user portraits, for example, matching calculation is carried out on user images and various information to analyze and acquire the information of user preferences, but in the method, because the generation period of the user portraits is long, but the preference change of the user is faster, the accuracy of the obtained analysis result is lower after the user preference information is analyzed based on the user portraits.
Disclosure of Invention
The invention provides a virtual reading trajectory graph generation method, a virtual reading trajectory graph generation device and a computer readable storage medium, which mainly aim to solve the problem of low accuracy of analyzing user preference information.
In order to achieve the above object, the present invention provides a virtual reading trajectory graph generating method, including:
acquiring existing information data of a user and a historical reading track of the existing information, and constructing an information image according to the existing information data;
constructing a track vector according to the historical reading track, and marking the information image by utilizing the track vector to obtain a first track image;
performing reading track analysis on the first track image by utilizing a pre-constructed countermeasure generation network to obtain a second track image;
calculating the coincidence ratio of the first track image and the second track image;
if the contact ratio is smaller than or equal to a preset threshold value, adjusting parameters of the countermeasure generation network, and returning to the step of analyzing the reading track of the first track image;
outputting the countermeasure generation network if the contact ratio is greater than the preset threshold value, so as to obtain a reading track generation network;
and obtaining information data to be analyzed, and carrying out reading track analysis on the information data to be analyzed by utilizing the reading track generation network to obtain a virtual reading track diagram of the user.
Optionally, the constructing an information image according to the existing information data includes:
dividing the existing information data according to a first unit time to obtain an information subset;
determining the information reading quantity and the information total quantity of each information subset;
and constructing an information image according to the information reading quantity and the information total quantity of each information subset.
Optionally, the constructing an information image according to the information reading quantity and the information total quantity of each information subset includes:
factorization is carried out on the total information quantity of the existing information data to obtain an information matrix;
performing a first operation on the information reading quantity of each information subset and a preset unit gray value to obtain matrix gray;
performing a second operation using the matrix gray level and the information matrix to obtain an information image.
Optionally, the constructing a track vector according to the historical reading track includes:
extracting browsing duration of the user on each information data in the historical reading track in a second unit time;
and carrying out vector conversion on each information data in the historical reading track according to the browsing time length to obtain a track vector.
Optionally, the performing vector conversion on each information data in the historical reading track according to the browsing duration to obtain a track vector includes:
vector conversion is carried out on each piece of existing information data in the historical reading track by using the following vector conversion algorithm:
wherein, the liquid crystal display device comprises a liquid crystal display device,is +.>Browsing duration of individual existing information data, +.>Is->Track vector of existing information data +.>For the minimum browsing duration in the historical reading track, < > in->And the maximum browsing duration in the historical reading track is set.
Optionally, the performing reading track analysis on the first track image by using a pre-constructed countermeasure generation network to obtain a second track image includes:
mapping the track vector in the first track map to a pre-constructed vector space by using a generator in the countermeasure generation network to obtain vector characterization;
constructing an objective function by using a preset adjusting function and the vector representation;
and calculating the first track image by using the objective function to obtain a second track image.
Optionally, the calculating the coincidence ratio of the first track image and the second track image includes:
calculating a loss value between each track vector in the first track image and the second track image by using a loss function of a discriminator in the countermeasure generation network;
and taking the average value of the loss values as the coincidence ratio of the first track image and the second track image.
In order to solve the above problems, the present invention further provides a virtual reading trajectory graph generating device, which includes:
the first conversion module is used for acquiring the existing information data of the user and the historical reading track in the existing information, and constructing an information image according to the existing information data;
the second conversion module is used for constructing a track vector according to the historical reading track, and marking the information image by utilizing the track vector to obtain a first track image;
the first analysis module is used for carrying out reading track analysis on the first track image by utilizing a pre-constructed countermeasure generation network to obtain a second track image;
the contact ratio calculating module is used for calculating the contact ratio of the first track image and the second track image;
the parameter adjustment module is used for adjusting the parameters of the countermeasure generation network and returning to the step of carrying out reading track analysis on the first track image if the contact ratio is smaller than or equal to a preset threshold value;
the network output module is used for outputting the countermeasure generation network if the contact ratio is larger than the preset threshold value, so as to obtain a reading track generation network;
and the second analysis module is used for acquiring information data to be analyzed, and carrying out reading track analysis on the information data to be analyzed by utilizing the reading track generation network to obtain a virtual reading track diagram of the user.
In order to solve the above-mentioned problems, the present invention also provides an electronic apparatus including:
a memory storing at least one instruction; a kind of electronic device with high-pressure air-conditioning system
And the processor executes the instructions stored in the memory to realize the virtual reading trajectory graph generation method.
In order to solve the above-mentioned problems, the present invention also provides a computer-readable storage medium having at least one instruction stored therein, the at least one instruction being executed by a processor in an electronic device to implement the virtual reading trajectory graph generating method described above.
According to the embodiment of the invention, the track vector is generated through the historical reading track, the track vector is utilized to mark the information image generated by the existing information data, so that the track image containing the user reading track is obtained, the efficiency of analyzing the information data is improved, the track image is utilized to train the pre-constructed countermeasure generation network, the trained network is utilized to analyze the reading track of the information data to be analyzed, the preference of the user on each data in the information data to be analyzed is obtained, and the accuracy of the network is utilized to realize the accurate analysis of the information. Therefore, the virtual reading trajectory graph generation method, the virtual reading trajectory graph generation device, the electronic equipment and the computer readable storage medium can solve the problem of low accuracy of analyzing the user preference information.
Drawings
FIG. 1 is a flowchart of a method for generating a virtual reading trajectory graph according to an embodiment of the present invention;
FIG. 2 is a flow chart of converting an information image according to an embodiment of the invention;
FIG. 3 is a flowchart illustrating an initial resource tag generation process according to an embodiment of the present invention;
FIG. 4 is a functional block diagram of a virtual reading trajectory graph generating device according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device for implementing the virtual reading trajectory graph generating method according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the application provides a virtual reading trajectory graph generation method. The execution subject of the virtual reading trajectory graph generating method includes, but is not limited to, at least one of a server, a terminal, and the like, which can be configured to execute the method provided by the embodiment of the application. In other words, the virtual reading trajectory graph generating method may be performed by software or hardware installed in a terminal device or a server device, and the software may be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Referring to fig. 1, a flow chart of a virtual reading trajectory graph generating method according to an embodiment of the invention is shown. In this embodiment, the method for generating a virtual reading trajectory graph includes:
s1, acquiring existing information data of a user and a historical reading track of the existing information, and constructing an information image according to the existing information data.
In the embodiment of the invention, the existing information data is information (such as news, books, advertisements and the like transmitted to the client) which can be acquired by the user, and the total number of the information, the read number and the like.
For example, the information transmitted to the client page includes: a news, a book and an advertisement, and the total number of information is 3, and 2 information is read therein.
In detail, the historical reading track is information such as names, browsing time and the like of information browsed by a user in the existing information data.
For example, the existing information data includes information a, information B and information C, wherein the information B and the information C are browsed by the user, and the browsing duration of the information B is 0.5 hour, and the browsing duration of the information C is 0.1 hour, and the browsing durations of the information B, the information C and the information B and the information C respectively correspond to the historical reading tracks of the user in the existing information data.
In the embodiment of the invention, the information calling instruction can be generated, and the existing information data and the historical reading track which are pre-stored in the database, the block chain or the network cache can be called by utilizing the information calling instruction.
In the embodiment of the present invention, the acquiring the existing information data of the user and the historical reading track in the existing information includes:
acquiring an information calling instruction, and extracting a target access address in the information calling instruction;
searching a storage database of the existing information data and the historical reading track according to the target access address;
extracting the existing information data and the historical reading track from the storage database.
In detail, the information call instruction may be generated through a pre-built graphical click button program or through an instructional operation platform.
Specifically, the invention can utilize a preset parser to parse the information call instruction to extract the target access address in the information call instruction, wherein the parser comprises, but is not limited to, a json parser and a python parser; and then searching a storage database for storing the existing information data and the historical reading track according to the target access address, and acquiring the existing information data and the historical reading track from the storage database.
Further, since the existing information data are mostly text data and have huge data volume, if the existing information data are directly processed, a large amount of computation resources are occupied, and the processing efficiency is reduced.
In one embodiment of the present invention, referring to fig. 2, the constructing an information image according to the existing information data includes:
s21, dividing the existing information data according to a first unit time to obtain an information subset;
s22, determining the information reading quantity and the information total quantity of each information subset;
s23, constructing an information image according to the information reading quantity and the information total quantity of each information subset.
In one embodiment of the present invention, the first unit time may be a natural day (24 hours). The embodiment of the invention constructs the information image according to the information reading quantity and the information total quantity of the existing information data generated by each natural day.
For example, the existing information data includes information available to the user from 3 months 1 day to 3 months 3 days, and the existing information data may be divided into 3 months 1 day information subset, 3 months 2 day information subset, and 3 months 3 day information subset.
Further, the information reading number and the information total number in each first unit time can be determined according to the information subset, for example, the existing information data comprises news, books, advertisements and the like at 3 months and 1 day, and the total number of the information in the information is 3, and if 2 information is read and the like, the information total number in the information subset of 3 months and 1 day can be determined to be 3, and the information reading number is 2. In another embodiment of the present invention, the constructing an information image according to the information reading number and the information total number of each of the information subsets includes:
factorization is carried out on the total information quantity of the existing information data to obtain an information matrix;
performing a first operation on the information reading quantity of the information subset and a preset unit gray value to obtain matrix gray;
performing a second operation using the matrix gray level and the information matrix to obtain an information image.
In detail, assuming that the total information amount is Z, the total information amount may be factorized into z=x.y, wherein X, Y is a factor obtained by factorizing Z, and further it may be determined that the size of the information matrix corresponding to Z is x.y, wherein X is the number of rows and columns of the daily information matrix and Y is the number of columns of the daily information matrix.
For example, the total number of information is 3, the total number of information can be factorized into 3=1.3, and the size of the information matrix corresponding to 3 can be determined to be 1.3, wherein 1 is the number of rows and columns of the daily information matrix, and 3 is the number of columns and columns of the daily information matrix.
In an embodiment of the present invention, the first operation includes, but is not limited to, a multiplication operation, a division operation, an addition operation, and a subtraction operation.
For example, the number of information reads is q, the unit gray value is e, and when the first operation is multiplication, the matrix gray q×e can be obtained.
In detail, the second operation may be the same as the first operation.
S2, constructing a track vector according to the historical reading track, and marking the information image by utilizing the track vector to obtain a first track image.
In one practical application scenario of the invention, the historical reading track is the same as the existing information data and mostly is text data, so that in order to improve the analysis efficiency of the historical reading track, the embodiment of the invention constructs the track vector according to the historical reading track.
In the embodiment of the present invention, the constructing a track vector according to the historical reading track includes:
extracting browsing duration of a user on each information data in the historical reading track in a second unit time;
and carrying out vector conversion on each information data in the historical reading track according to the browsing time length to obtain a track vector.
Wherein the second unit may be the same as the first unit time described above. In detail, the embodiment of the invention can extract the browsing time length of each piece of existing information data in the historical reading track through computer sentences (java sentences, python sentences and the like) with a data extraction function.
Specifically, the vector conversion is performed on each existing information data in the historical reading track according to the browsing duration to obtain a track vector, which includes:
vector conversion is carried out on each piece of existing information data in the historical reading track by using the following vector conversion algorithm:
wherein, the liquid crystal display device comprises a liquid crystal display device,is +.>Browsing duration of individual existing information data, +.>Is->Track vector of existing information data +.>For the minimum browsing duration in the historical reading track, < > in->And the maximum browsing duration in the historical reading track is set.
For exampleThe contained historical reading tracks include: b1 When the trajectory vector of the 3 rd existing information data is calculated by the vector conversion algorithm described above, the trajectory vector of the 3 rd existing information data is calculated in =0.13 hours, b2=2.5 hours, b3=0.5 hours, b4=2.8 hours, b5=1.5 hours, b6=2.8 hours, b7=0.37 hours, b8=2.5 hours, b9=1.25 hours>And 6 th existing information data track vector +.>The method can obtain:
in the embodiment of the invention, the track vector is calculated according to the browsing time length of the user on each piece of the existing information data, so that the larger the value of the track vector is, the more carefully the user browses the existing information data corresponding to the track vector, and further, the information image can be marked by multiplying, adding and other operations on the track vector and the vector in the information image, so that the browsing track of the user is displayed in the information image, and the first track image is obtained.
S3, performing reading track analysis on the first track image by utilizing a pre-constructed countermeasure generation network to obtain a second track image.
In the embodiment of the invention, the countermeasure generation network is a deep learning model and comprises a generator and a discriminator, wherein the generator is a prediction result (second track image) for generating input data, and the discriminator is used for discriminating the difference between the prediction result (second track image) and a standard result (first track image) corresponding to the input data.
In the embodiment of the present invention, referring to fig. 3, the step of performing a reading track analysis on the first track image by using a pre-constructed countermeasure generation network to obtain a second track image includes:
s31, mapping the track vector in the first track map to a pre-constructed vector space by using a generator in the countermeasure generation network to obtain vector characterization;
s32, constructing an objective function by utilizing a preset adjusting function and the vector representation;
s33, calculating the first track image by utilizing the objective function to obtain a second track image.
In detail, the generator may map the trajectory vectors in the first trajectory graph to a pre-constructed vector space using the following function, resulting in a vector characterization:
wherein, the liquid crystal display device comprises a liquid crystal display device,is->Track vector of the existing information data, softmax () is normalized exponential function, a (z) is +.>Vector representations corresponding to the track vectors of the existing information data.
Specifically, after the vector representation is obtained, a preset adjustment function and the vector representation can be utilized to construct an objective function.
Illustratively, the objective function is:
wherein a (z) is the vector representation, G (z) is a preset adjustment function, and G (z) is the objective function.
In an embodiment of the present invention, the adjustment function includes, but is not limited to: linear kernel function, polynomial kernel function, sigmoid kernel function.
S4, calculating the coincidence ratio of the first track image and the second track image;
in the embodiment of the invention, the contact ratio of the first track image and the second track image can be judged by utilizing a discriminator in the countermeasure generation network.
In an embodiment of the present invention, the calculating the contact ratio between the first track image and the second track image includes:
calculating a loss value between each track vector in the first track image and the second track image by using a loss function of a discriminator in the countermeasure generation network;
and taking the average value of the loss values as the coincidence ratio of the first track image and the second track image.
For example, the first track image contains tracksVector a, trajectory vector B and trajectory vector C, and the second trajectory image includes trajectory vector a, trajectory vector B and trajectory vector C, the penalty function of the discriminators in the countermeasure generation network may be used to calculate a penalty value between trajectory vector a and trajectory vector aLoss value between track vector B and track vector B +.>Loss value between track vector C and track vector C +.>And will->、/>And->And the average value of the first track image and the second track image is used as the coincidence degree of the first track image and the second track image.
S5, judging whether the contact ratio is larger than a preset threshold value or not;
if the contact ratio is smaller than or equal to the preset threshold, the following S6 is executed, and if the contact ratio is larger than the preset threshold, the following S7 is executed.
S6, adjusting parameters of the countermeasure generation network, and returning to the step S3.
In the embodiment of the present invention, if the contact ratio is smaller than or equal to the preset threshold, it is indicated that the accuracy of the countermeasure generation network is low, so that the parameters of the countermeasure generation network need to be adjusted.
In one embodiment of the present invention, the parameters of the countermeasure generation network may be adjusted using a preset optimization algorithm, including but not limited to: a batch gradient descent algorithm, a small batch gradient descent algorithm, and a random gradient descent algorithm.
For example, the current parameters of the countermeasure generation network are input into the optimization algorithm, the input current parameters are optimally calculated by the optimization algorithm, the optimized parameters output by the optimization algorithm are obtained, and the current parameters of the countermeasure generation network are replaced by the optimized parameters, so that the adjustment of the parameters in the countermeasure generation network is realized.
In detail, the adjusting the parameters of the countermeasure generation network includes:
acquiring current parameters in the countermeasure generation network;
calculating the update gradient of the current parameter by using a preset optimization algorithm;
and updating the current parameters according to the updating gradient to obtain optimized parameters.
According to the embodiment of the invention, the current parameters can be extracted from the countermeasure generation network through a computer sentence with a parameter extraction function, and then the current parameters are updated by using a preset optimization algorithm.
When the current parameter is updated according to the update gradient, the current parameter and the update gradient can be utilized to perform preset arithmetic operation.
For example, the current parameter is 10, the current parameter is calculated by using a preset optimization algorithm, so that an update gradient of the current parameter is 0.1, and the current parameter can be updated to 10 (1+0.1) =11 according to the update gradient 0.1;
alternatively, the current parameter may be updated to 10+0.1=10.1 according to the update gradient 0.1.
And after the parameters of the countermeasure generation network are adjusted, returning to the step S3, and carrying out reading track analysis on the first track image again.
S7, outputting the countermeasure generation network to obtain a reading track generation network;
in the embodiment of the invention, if the contact ratio is greater than the preset threshold value, the accuracy of the countermeasure generation network is satisfied, and the countermeasure generation network can be output to obtain the reading track generation network.
S8, obtaining information data to be analyzed, and performing reading track analysis on the information data to be analyzed by using the reading track generation network to obtain a virtual reading track diagram of the user.
In the embodiment of the invention, the information data to be analyzed comprises information data which is not displayed to a user, and the information data to be analyzed can be grasped from a database for storing the information data to be analyzed.
According to the embodiment of the invention, the reading track generation network is utilized to analyze the reading track of the information data to be analyzed, so that the virtual reading track diagram can be obtained, and the virtual reading track diagram can be used for predicting the reading track of a user.
For example, when news a, news B, news C and news D exist in the information data to be analyzed, the reading track generation network is utilized to analyze the reading track of the information data to be analyzed, so that it can be obtained that the user may read news a, news C and news D, not read news B, and read news a first, then read news D and finally read news C.
According to the embodiment of the invention, the track vector is generated through the historical reading track respectively, the track vector is utilized to mark the information image generated by the existing information data, so that the first track image containing the user reading track is obtained, the efficiency of analyzing the information data is improved, the first track image is utilized to train the pre-constructed countermeasure generation network, the trained network is utilized to analyze the reading track of the information data to be analyzed, the preference of the user on each data in the information data to be analyzed is obtained, and the accuracy of the network is utilized to realize the accurate analysis of the information. Therefore, the virtual reading trajectory graph generation method provided by the invention can solve the problem of lower accuracy of analysis of the user preference information.
Fig. 4 is a functional block diagram of a virtual reading trajectory graph generating device according to an embodiment of the present invention.
The virtual reading trajectory graph generating device 100 of the present invention may be installed in an electronic device. According to the implemented functions, the virtual reading trajectory graph generating device 100 may include a first conversion module 101, a second conversion module 102, a first analysis module 103, a contact ratio calculation module 104, a parameter adjustment module 105, a network output module 106, and a second analysis module 107. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
In the present embodiment, the functions concerning the respective modules/units are as follows:
the first conversion module 101 is configured to obtain existing information data of a user and a historical reading track in the existing information, and construct an information image according to the existing information data;
the second conversion module 102 is configured to construct a track vector according to the historical reading track, and mark the information image by using the track vector to obtain a first track image;
the first analysis module 103 is configured to perform a reading track analysis on the first track image by using a pre-constructed countermeasure generation network, so as to obtain a second track image;
the contact ratio calculating module 104 is configured to calculate a contact ratio between the first track image and the second track image;
the parameter adjustment module 105 is configured to adjust parameters of the countermeasure generation network if the contact ratio is less than or equal to a preset threshold, and return to a step of performing reading track analysis on the first track image;
the network output module 106 is configured to output the countermeasure generation network as a reading track generation network if the overlap ratio is greater than the preset threshold;
the second analysis module 107 is configured to obtain information data to be analyzed, and perform a reading track analysis on the information data to be analyzed by using the reading track generation network, so as to obtain a virtual reading track diagram of the user.
In detail, each module in the virtual reading trajectory graph generating device 100 in the embodiment of the present invention adopts the same technical means as the virtual reading trajectory graph generating method described in fig. 1 to 3, and can generate the same technical effects, which is not described herein.
Fig. 5 is a schematic structural diagram of an electronic device for implementing a virtual reading trajectory graph generating method according to an embodiment of the present invention.
The electronic device may comprise a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may further comprise a computer program, such as a front-end monitoring program, stored in the memory 11 and executable on the processor 10.
The processor 10 may be formed by an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be formed by a plurality of integrated circuits packaged with the same function or different functions, including one or more central processing units (Central Processing unit, CPU), a microprocessor, a digital processing chip, a graphics processor, a combination of various control chips, and so on. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the entire electronic device using various interfaces and lines, and executes various functions of the electronic device and processes data by running or executing programs or modules (e.g., executing a front-end monitoring program, etc.) stored in the memory 11, and calling data stored in the memory 11.
The memory 11 includes at least one type of readable storage medium including flash memory, a removable hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, such as a mobile hard disk of the electronic device. The memory 11 may in other embodiments also be an external storage device of the electronic device, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used not only for storing application software installed in an electronic device and various types of data, such as codes of a front-end monitoring program, but also for temporarily storing data that has been output or is to be output.
The communication bus 12 may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus, or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.
The communication interface 13 is used for communication between the electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), or alternatively a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device and for displaying a visual user interface.
Fig. 5 shows only an electronic device with components, it being understood by a person skilled in the art that the structure shown in fig. 5 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or may combine certain components, or may be arranged in different components.
For example, although not shown, the electronic device may further include a power source (such as a battery) for supplying power to the respective components, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device may further include various sensors, bluetooth modules, wi-Fi modules, etc., which are not described herein.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
The virtual reading trajectory graph generating program stored in the memory 11 of the electronic device 1 is a combination of a plurality of instructions, and when executed in the processor 10, may implement:
acquiring the existing information data of a user and a historical reading track in the existing information, and constructing an information image according to the existing information data;
constructing a track vector according to the historical reading track, and marking the information image by utilizing the track vector to obtain a first track image;
performing reading track analysis on the first track image by utilizing a pre-constructed countermeasure generation network to obtain a second track image;
calculating the coincidence ratio of the first track image and the second track image;
if the contact ratio is smaller than or equal to a preset threshold value, adjusting parameters of the countermeasure generation network, and returning to the step of analyzing the reading track of the first track image;
outputting the countermeasure generation network if the contact ratio is greater than the preset threshold value, so as to obtain a reading track generation network;
and obtaining information data to be analyzed, and carrying out reading track analysis on the information data to be analyzed by utilizing the reading track generation network to obtain a virtual reading track diagram of the user.
Specifically, the specific implementation method of the above instructions by the processor 10 may refer to the description of the relevant steps in the corresponding embodiment of fig. 1, which is not repeated herein.
Further, the modules/units integrated in the electronic device 1 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).
The present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement:
acquiring the existing information data of a user and a historical reading track in the existing information, and constructing an information image according to the existing information data;
constructing a track vector according to the historical reading track, and marking the information image by utilizing the track vector to obtain a first track image;
performing reading track analysis on the first track image by utilizing a pre-constructed countermeasure generation network to obtain a second track image;
calculating the coincidence ratio of the first track image and the second track image;
if the contact ratio is smaller than or equal to a preset threshold value, adjusting parameters of the countermeasure generation network, and returning to the step of analyzing the reading track of the first track image;
outputting the countermeasure generation network if the contact ratio is greater than the preset threshold value, so as to obtain a reading track generation network;
and obtaining information data to be analyzed, and carrying out reading track analysis on the information data to be analyzed by utilizing the reading track generation network to obtain a virtual reading track diagram of the user.
In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units or means recited in the system claims can also be implemented by means of software or hardware by means of one unit or means. The terms second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (6)
1. The virtual reading trajectory graph generation method is characterized by comprising the following steps:
acquiring existing information data of a user and a historical reading track of the existing information, and constructing an information image according to the existing information data;
constructing a track vector according to the historical reading track, and marking the information image by utilizing the track vector to obtain a first track image;
performing reading track analysis on the first track image by utilizing a pre-constructed countermeasure generation network to obtain a second track image;
calculating the coincidence ratio of the first track image and the second track image;
if the contact ratio is smaller than or equal to a preset threshold value, adjusting parameters of the countermeasure generation network, and returning to the step of analyzing the reading track of the first track image;
outputting the countermeasure generation network if the contact ratio is greater than the preset threshold value, so as to obtain a reading track generation network;
obtaining information data to be analyzed, and performing reading track analysis on the information data to be analyzed by utilizing the reading track generation network to obtain a virtual reading track diagram of the user;
wherein said constructing an information image from said existing information data comprises: dividing the existing information data according to a first unit time to obtain an information subset; determining the information reading quantity and the information total quantity of each information subset; constructing an information image according to the information reading quantity and the information total quantity of each information subset;
said constructing an information image based on the information reading quantity and the information total quantity of each of said information subsets, comprising: factorization is carried out on the total information quantity of the existing information data to obtain an information matrix; performing a first operation on the information reading quantity of each information subset and a preset unit gray value to obtain matrix gray; performing a second operation by using the matrix gray scale and the information matrix to obtain an information image;
the constructing a track vector according to the historical reading track includes: extracting browsing duration of a user on each information data in the historical reading track in a second unit time; performing vector conversion on each information data in the historical reading track according to the browsing time length to obtain a track vector;
the step of performing vector conversion on each information data in the historical reading track according to the browsing time length to obtain a track vector comprises the following steps: vector conversion is carried out on each piece of existing information data in the historical reading track by using the following vector conversion algorithm:
wherein, the liquid crystal display device comprises a liquid crystal display device,is +.>Browsing duration of individual existing information data, +.>Is->Track vector of existing information data +.>For the minimum browsing duration in the historical reading track, < > in->And the maximum browsing duration in the historical reading track is set.
2. The method for generating a virtual reading trajectory graph according to claim 1, wherein the step of performing reading trajectory analysis on the first trajectory image using a pre-constructed countermeasure generation network to obtain a second trajectory image includes:
mapping the track vector in the first track map to a pre-constructed vector space by using a generator in the countermeasure generation network to obtain vector characterization;
constructing an objective function by using a preset adjusting function and the vector representation;
and calculating the first track image by using the objective function to obtain a second track image.
3. The method for generating a virtual reading trajectory graph according to claim 1, wherein calculating the coincidence degree of the first trajectory image and the second trajectory image includes:
calculating a loss value between each track vector in the first track image and the second track image by using a loss function of a discriminator in the countermeasure generation network;
and taking the average value of the loss values as the coincidence ratio of the first track image and the second track image.
4. A virtual reading trajectory graph generating device for implementing the virtual reading trajectory graph generating method according to any one of claims 1 to 3, characterized in that the device comprises:
the first conversion module is used for acquiring the existing information data of the user and the historical reading track of the existing information, and constructing an information image according to the existing information data;
the second conversion module is used for constructing a track vector according to the historical reading track, and marking the information image by utilizing the track vector to obtain a first track image;
the first analysis module is used for carrying out reading track analysis on the first track image by utilizing a pre-constructed countermeasure generation network to obtain a second track image;
the contact ratio calculating module is used for calculating the contact ratio of the first track image and the second track image;
the parameter adjustment module is used for adjusting the parameters of the countermeasure generation network and returning to the step of carrying out reading track analysis on the first track image if the contact ratio is smaller than or equal to a preset threshold value;
the network output module is used for outputting the countermeasure generation network if the contact ratio is larger than the preset threshold value, so as to obtain a reading track generation network;
and the second analysis module is used for acquiring information data to be analyzed, and carrying out reading track analysis on the information data to be analyzed by utilizing the reading track generation network to obtain a virtual reading track diagram of the user.
5. An electronic device, the electronic device comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the virtual read trajectory graph generation method of any one of claims 1 to 3.
6. A computer-readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the virtual reading trajectory graph generation method of any one of claims 1 to 3.
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