CN113778951A - File addition method, device, equipment and storage medium - Google Patents
File addition method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN113778951A CN113778951A CN202111087221.3A CN202111087221A CN113778951A CN 113778951 A CN113778951 A CN 113778951A CN 202111087221 A CN202111087221 A CN 202111087221A CN 113778951 A CN113778951 A CN 113778951A
- Authority
- CN
- China
- Prior art keywords
- file
- additional
- link
- score
- trained
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 55
- 238000012544 monitoring process Methods 0.000 claims abstract description 26
- 239000013598 vector Substances 0.000 claims description 41
- 230000006870 function Effects 0.000 claims description 16
- 238000012549 training Methods 0.000 claims description 16
- 238000004590 computer program Methods 0.000 claims description 13
- 230000000007 visual effect Effects 0.000 claims description 7
- 238000000605 extraction Methods 0.000 claims description 3
- 238000013473 artificial intelligence Methods 0.000 abstract description 6
- 238000005516 engineering process Methods 0.000 description 8
- 230000008569 process Effects 0.000 description 6
- 238000004364 calculation method Methods 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 241000219357 Cactaceae Species 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000008094 contradictory effect Effects 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012886 linear function Methods 0.000 description 1
- 238000012417 linear regression Methods 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000003058 natural language processing Methods 0.000 description 1
- 238000012887 quadratic function Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/14—Details of searching files based on file metadata
- G06F16/148—File search processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/16—File or folder operations, e.g. details of user interfaces specifically adapted to file systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0481—Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
- G06F3/0482—Interaction with lists of selectable items, e.g. menus
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Human Computer Interaction (AREA)
- Library & Information Science (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention relates to the field of artificial intelligence, and provides a method, a device, equipment and a storage medium for adding a file, wherein the method comprises the following steps: the method comprises the steps of obtaining unique identification information of a user, monitoring the use condition of the user on each file in real time according to the unique identification information, inputting the use condition of each file into a pre-trained additional judgment model, obtaining a first additional score of each file, and forming a link for a target file according to the first additional score. Therefore, corresponding links are generated for some common or more important files, efficient use and checking can be achieved, and user experience is improved.
Description
Technical Field
The present invention relates to the field of artificial intelligence, and in particular, to a method, an apparatus, a device, and a storage medium for adding a file.
Background
In daily office work, a large amount of note information needs to be recorded in chatting, various note information is respectively stored in different files, when the note information needs to be used or checked, the note information needs to be searched from each folder, and some common or more important files cannot be used or checked quickly and efficiently, so that a file adding method is urgently needed.
Disclosure of Invention
The invention mainly aims to provide a method, a device, equipment and a storage medium for adding files, and aims to solve the problem that some common or more important files cannot be used or viewed quickly and efficiently.
The invention provides a method for adding files, which comprises the following steps:
acquiring unique identification information of a user;
monitoring the first use condition of the user for each first file in real time according to the unique identification information;
inputting the first use condition of each first file into a pre-trained additional judgment model to obtain a first additional score of each first file;
taking the first file with the first additional value larger than a preset additional value in each first file as a target file, and extracting a file name, a suffix and a storage position of the target file;
forming a first link based on the storage location and generating a name of the first link based on the file name and the suffix;
adding the first link and the name to a flash directory.
Further, before the step of inputting the first usage of each first file into a pre-trained additional judgment model to obtain the first additional score of each first file, the method further includes:
acquiring second use conditions of corresponding second files of each second link in the quick directories of the users and corresponding second additional scores;
converting the second use condition into a multi-dimensional vector according to a preset dimension; wherein the multi-dimensional vector is Xj＝(x1j，x2j…xij…xnj)，XjA multidimensional vector, x, representing a second use case of a jth second fileijAn ith dimension vector representing a second use case of the jth second file;
inputting each multi-dimensional vector and the corresponding second additional score into an additional judgment initial model for training to obtain the pre-trained additional judgment model; whereinThe initial model is determined as hw(x)＝w0+w1x1+w2x2+wixi...+wnxnWherein h isw(x) Is the second top-up score, w0，w1，...，wnAre all the parameter values to be trained, xiRepresenting an ith vector of the multi-dimensional vectors.
Further, after the step of inputting each multidimensional vector and the corresponding second additional score into an additional judgment initial model for training to obtain the pre-trained additional judgment model, the method includes:
acquiring actual additional scores of second use conditions of the second files and predicted additional scores of the pre-trained additional judgment model;
calculating the loss value of the pre-trained additional judgment model according to a loss function formula; wherein the loss function is formulated as:
yjrepresents the actual additional score, h, corresponding to the second usage of the j second filesw(xij) A predicted addition score obtained by inputting a second use case of a jth second file into the pre-trained addition judgment model, n represents a dimension of the multidimensional vector,
a value of a parameter that is preset is indicated,
a loss value representing the pre-trained additional judgment model;
judging whether the loss value is larger than a preset loss value or not;
if the loss value is larger than the preset loss value, the pre-trained additional judgment model continues to be trained until the pre-trained additional judgment model with the loss value smaller than the preset loss value is obtained.
Further, after the step of adding the first link and the name to the fast directory, the method further includes:
detecting whether the unused time of each first link in the quick directory reaches a preset time or not;
and clearing the first link reaching the preset time from the rapid directory.
Further, before the step of obtaining the first usage of each first file by the user in real time according to the unique identifier information, the method further includes:
judging whether each first file establishes a first link in the fast directory or not;
monitoring for the first file for which the first link has been established in the fast directory is stopped.
Further, before the step of detecting whether the unused time of each first link in the fast directory reaches the preset time, the method further includes:
extracting a first additional score of the target file;
according to the formula t ═ f (x)i) + calculating the preset time corresponding to the first additional score of the target file; wherein t represents a preset time, f (x)i) Representing the functional relationship between the additional score and the corresponding time, b representing the minimum value of the preset time, xiRepresenting a first append score for the ith first file.
Further, before the step of adding the first link and the name to the fast directory, the method further includes:
establishing a target folder of the rapid directory; wherein the target folder is used for storing various first links;
putting the link mode of the target folder into a right mouse button menu;
and designing a visual click link corresponding to the link mode on a UI layer in a right mouse button menu.
The invention also provides a device for adding files, which comprises:
the acquisition module is used for acquiring the unique identification information of the user;
the monitoring module is used for monitoring the first use condition of each first file by the user in real time according to the unique identification information;
the input module is used for inputting the first use condition of each first file into a pre-trained additional judgment model to obtain a first additional score of each first file;
an extraction module, configured to take the first file with the first additional score being greater than a preset additional score in each first file as a target file, and extract a file name, a suffix, and a storage location of the target file;
the generating module is used for forming a first link based on the storage position and generating the name of the first link based on the file name and the suffix;
and the adding module is used for adding the first link and the name into a quick directory.
The invention also provides a computer device comprising a memory storing a computer program and a processor implementing the steps of any of the above methods when the processor executes the computer program.
The invention also provides a computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the method of any of the above.
The invention has the beneficial effects that: the method comprises the steps of obtaining unique identification information of a user, monitoring the use condition of the user on each file in real time according to the unique identification information, inputting the use condition of each file into a pre-trained additional judgment model to obtain an additional score of each file, and forming a link for a target file according to the additional score. Therefore, corresponding links are generated for some common or more important files, efficient use and checking can be achieved, and user experience is improved.
Drawings
FIG. 1 is a flowchart illustrating a method for adding a file according to an embodiment of the present invention;
FIG. 2 is a block diagram schematically illustrating a structure of a device for adding a file according to an embodiment of the present invention;
fig. 3 is a block diagram illustrating a structure of a computer device according to an embodiment of the present application.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that all directional indicators (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative position relationship between the components, the motion situation, etc. in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indicator is changed accordingly, and the connection may be a direct connection or an indirect connection.
The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and B, may mean: a exists alone, A and B exist simultaneously, and B exists alone.
In addition, the descriptions related to "first", "second", etc. in the present invention are only for descriptive purposes and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present invention.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
The artificial intelligence infrastructure generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.
Referring to fig. 1, the present invention provides a method for adding a first file, including:
s1: acquiring unique identification information of a user;
s2: monitoring the first use condition of the user on each first file in real time according to the unique identification information;
s3: inputting the first use condition of each first file into a pre-trained additional judgment model to obtain an additional score of each first file;
s4: taking the first file with the first additional value larger than a preset additional value in each first file as a target file, and extracting a file name, a suffix and a storage position of the target file;
s5: forming a first link based on the storage location and generating a name of the first link based on the file name and the suffix;
s6: adding the first link and the name to a flash directory.
As described in the above step S1, the unique identification information of the user is obtained, and the unique identification information at least includes one or more of account information, identity information, and phone number of the user. Since each user has corresponding unique identifier information, such as identity information, IP address, phone, etc., the unique identifier information can be obtained to identify the corresponding user, so as to facilitate rapid detection of the fast directory corresponding to the user.
As described in step S2, monitoring the first usage of each first file by the user in real time according to the unique identifier information; the first use condition at least comprises times corresponding to the times that the user opens each first file. That is, the first usage of each first file by the user may be obtained based on the unique identifier information, and if the first usage is an APP, the first usage of each first file may be called by the user in the APP, or the first usage of each first file by the user in a computer system or a monitoring computer system may also be called by the user in the computer system or the monitoring computer system.
As described in step S3, the first usage of each first file is input to a pre-trained addition determination model, and a first addition score of each first file is obtained. The pre-trained additional judgment model is trained according to the use condition of the file and the corresponding additional score, different use conditions correspond to different additional scores, different additional scores can be set by related personnel, and the model is trained as a training set, so that the corresponding pre-trained additional judgment model is obtained.
As described in step S4, the first file with the first addition value larger than the preset addition value among the first files is used as the target file, and the file name, suffix, and storage location of the target file are extracted. The target file with the first additional score larger than the preset additional score is identified as a first file to be added by the user, and then the file name, the suffix and the storage position of the first file are extracted based on the requirement, so that a directory for quickly finding out the first file is formed subsequently, namely a corresponding first link is generated in the directory.
As described in the above step S5, a first link is formed based on the storage location, and the name of the first link is generated based on the file name and the suffix. Specifically, a corresponding file path is generated based on the storage location, and the file name and the suffix of the file path are used as the name of the link, so that the user can conveniently identify the content in the first link.
As described in step S6, the first link and the name are added to the fast directory, that is, sent to the fast directory, where the fast directory is a fast opening manner for a user, and may be set in any directory, for example, under a right-click menu of a mouse, or on a desktop. In a preferred embodiment, the link can be set in any one of the hierarchical menus of an APP, for example, the hierarchical menu of the APP, and the link is added to the storage location in the hierarchical menu, and then the UI layer is correspondingly set to display the link.
In one embodiment, before the step S3 of inputting the first usage of each first file into a pre-trained addition judgment model to obtain the first addition score of each first file, the method includes:
s201: acquiring second use conditions of corresponding second files of each second link in the quick directories of the users and corresponding second additional scores;
s202: converting the second use condition into a multi-dimensional vector according to a preset dimension; wherein the multi-dimensional vector is Xj＝(x1j，x2j…xij…xnj)，XjA multidimensional vector, x, representing a second use case of a jth second fileijAn ith dimension vector representing a second use case of the jth second file;
s203: inputting each multi-dimensional vector and the corresponding second additional score into an additional judgment initial model for training to obtain the pre-trained additional judgment model; wherein the additional judgment initial model ishw(x)＝w0+w1x1+w2x2+wixi...+wnxnWherein h isw(x) Is the second top-up score, w0，w1，...，wnAre all the parameter values to be trained, xiRepresenting an ith vector of the multi-dimensional vectors.
As described in steps S201 to S203, training of the pre-trained additional determination model is realized.
In step S201, a second use condition of each link corresponding to the second file and a corresponding second additional score are obtained, where the second use condition may be monitored by a corresponding operation and maintenance monitoring system, for example, the operation and maintenance monitoring system may be any one of Zabbix, Cacti, and Hyperic, and the corresponding second additional score is obtained by a corresponding user by himself or by related personnel through unified scoring, so as to form a corresponding training set.
In step S202, the corresponding second usage is converted into a multidimensional vector, where the dimension of the multidimensional vector may include the number of times of usage, the usage time, the degree of correlation with the work of the user, and the like.
In step S203, each multidimensional vector is input to the additional judgment initial model for training to obtain a pre-trained additional judgment model, so that the calculation result can approach the result of the user' S own additional second file, and the function of the additional judgment initial model can be hw(x)＝w0+w1x1+w2x2+wixi...+wnxnThen calculating the parameter value w by linear regression algorithm and each multidimensional vector0，w1，...，wnAnd then adding the calculated parameter value to the function to obtain a pre-trained addition judgment model, and converting the obtained second use condition into a corresponding addition time length according to the corresponding relation between the second use condition and the addition time length.
In an embodiment, the step S203 of inputting each multidimensional vector and the corresponding second additional score into an additional judgment initial model for training to obtain the pre-trained additional judgment model includes:
s2031: acquiring actual additional scores of second use conditions of the second files and predicted additional scores of the pre-trained additional judgment model;
s2032: calculating the loss value of the pre-trained additional judgment model according to a loss function formula; wherein the loss function is formulated as:
yjrepresents the actual additional score, h, corresponding to the second usage of the j second filesw(xij) A predicted addition score obtained by inputting a second use condition of the jth second file into the pre-trained addition judgment model, wherein n represents a dimension of the multidimensional vector,
a value of a parameter that is preset is indicated,
a loss value representing the pre-trained additional judgment model;
s2033: judging whether the loss value is larger than a preset loss value or not;
s2034: if the loss value is larger than the preset loss value, the pre-trained additional judgment model continues to be trained until the pre-trained additional judgment model with the loss value smaller than the preset loss value is obtained.
As described in steps S2031 to S2034, the parameter detection of the pre-trained additional determination model is realized. Calculating the loss value by acquiring the actual use score of the second use condition of the user and inputting the second use condition into the predicted additional score obtained in the pre-trained additional judgment model, wherein the calculated loss function is
It is to be noted that wiAnd judging a parameter value corresponding to the ith dimension in the pre-trained additional judgment model, judging whether the pre-trained additional judgment model meets the requirement according to the calculated loss value, and if not, continuing training until the loss value of the pre-trained additional judgment model is less than the preset loss value. Therefore, the training of the precision of the pre-trained additional judgment model is realized, so that the obtained pre-trained additional judgment model can accurately predict whether to add the first file or not based on the first use condition.
In one embodiment, after the step S6 of adding the first link and the name to the flash directory, the method further includes:
s701: detecting whether the unused time of each first link in the quick directory reaches a preset time or not;
s702: and clearing the first link reaching the preset time from the rapid directory.
As described in the above steps S601-S602, the real-time update of the first link in the fast directory is realized. The method includes that whether a time label corresponding to a first link of the fast directory reaches preset time or not is periodically detected, when the corresponding failure time is reached, the corresponding first link is moved out, namely the first link is expired, so that the first link needs to be moved out of the fast directory, in addition, in some embodiments, a user can be informed whether the first link is moved out or not when the first link is moved out, if the user selects to continue to store, unused time of the first link is reset again, and accordingly real-time updating of data of the fast directory is achieved. Specifically, the method for detecting whether the time stamp of each first link in the fast directory reaches the preset time may be to periodically traverse all first links in the fast directory, detect the expiration time corresponding to each first link, then obtain the current time, and if the current time reaches or exceeds the preset time, indicate that the first link may be moved out of the fast directory.
In an embodiment, before the step S2 of obtaining the first usage of each first file by the user in real time according to the unique identifier information, the method further includes:
s101: judging whether each first file is linked in the quick directory or not;
s102: monitoring for the first file for which the first link has been established in the fast directory is stopped.
As described in steps S101-S102, monitoring of the first file that has already established the link in the fast directory is reduced, repeated monitoring of the first file is avoided, and monitoring resources are wasted, that is, it is determined whether each of the first files has already established the first link in the fast directory. The first file with the link established may be marked, for example, a special character may be set in the file name of the first file for marking, or the first file may be marked in other manners, and subsequently, when the mark is detected, the monitoring of the first file is stopped, so that the monitoring resource is saved, and the use performance of the monitoring is improved.
In an embodiment, before the step S701 of detecting whether the unused time of each first link in the fast directory reaches a preset time, the method further includes:
s7001: extracting a first additional score of the target first file;
s7002: according to the formula t ═ f (x)i) + b, calculating the preset time corresponding to the first additional score of the target file; wherein t represents a preset time, f (x)i) Representing the functional relationship between the first additional score and the corresponding time, b representing the minimum value of the preset time, xiRepresenting a first append score for the ith first file.
As described in the above steps S7001 to S7002, it is realized that a preset time is set for each target file, that is, a first append score obtained by the above-mentioned pre-trained append determination model is extracted, and then, f (x) is determined based on the formula t ═ f (x)i) + b calculating to obtain the first additional score of each target fileWherein f (x)i) In function xiShould be set to be larger than a certain value, i.e. the first additional score needs to be larger than the preset additional score, and in addition, f (x)i) The function may be a linear function, a quadratic function, or a complex function, and this is not limited in the present application, and it should be noted that f (x) isi) The function should be with xiThe increasing function increases the value of (a), that is, as the first additional score increases, the duration of the corresponding preset time is longer.
In one embodiment, before the step S6 of adding the link and the name to the fast directory, the method further includes:
s501: establishing a target folder of the rapid directory; wherein the target folder is used for storing various first links;
s502: putting the link mode of the target folder into a right mouse button menu;
s503: and designing a visual click link corresponding to the link mode on a UI layer in a right mouse button menu.
As described above in steps S501-S503, visual addition of links is achieved. The corresponding target folder is established in the fast directory, or the corresponding target folder is selected, then the link in the target folder is copied to the forbidden zone, then the link mode of the target folder is put into a right-click menu of the mouse, namely the link mode of the corresponding target folder can be stored in the right-click menu of the mouse, then the corresponding visual click link is designed in the UI layer, subsequently, when a user searches for the corresponding first file, only the right-click is needed, and then the corresponding target folder is opened to find the target file, so that the target file can be quickly found.
Referring to fig. 2, the present invention further provides a file appending apparatus, including:
an obtaining module 10, configured to obtain unique identification information of a user;
the monitoring module 20 is configured to monitor, in real time, a first use condition of each first file by the user according to the unique identifier information;
an input module 30, configured to input the first use condition of each first file into a pre-trained additional judgment model, so as to obtain a first additional score of each first file;
an extracting module 40, configured to take the first file with the first additional score being greater than a preset additional score in each first file as a target file, and extract a file name, a suffix, and a storage location of the target file;
a generating module 50, configured to form a first link based on the storage location, and generate a name of the first link based on the file name and the suffix;
an appending module 60 for adding the first link and the name to the fast directory.
In one embodiment, the apparatus for appending the first file further includes:
the added score acquisition module is used for acquiring second use conditions of second files corresponding to each second link in the fast directories of the users and corresponding second added scores;
the vector conversion module is used for converting the second use condition into a multi-dimensional vector according to a preset dimension; wherein the multi-dimensional vector is Xj＝(x1j，x2j…xij…xnj)，XjA multidimensional vector, x, representing a second use case of a jth second fileijAn ith dimension vector representing a second use case of the jth second file;
the model training module is used for inputting each multi-dimensional vector and the corresponding second additional score into an additional judgment initial model for training to obtain the pre-trained additional judgment model; wherein the additional judgment initial model is hw(x)＝w0+w1x1+w2x2+wixi...+wnxnWherein h isw(x) Is the second top-up score, wo，w1，...，wnAre all the parameter values to be trained, xiRepresenting an ith vector of the multi-dimensional vectors.
In one embodiment, the apparatus for appending the first file further includes:
the predicted additional score acquisition module is used for acquiring the actual additional score of the second use condition of each second file and the predicted additional score of the pre-trained additional judgment model;
loss value calculation module for
Calculating the loss value of the pre-trained additional judgment model according to a loss function formula; wherein the loss function is formulated as:
yjrepresents the actual additional score, h, corresponding to the second usage of the j second filesw(xij) A predicted addition score obtained by inputting a second use case of a jth second file into the pre-trained addition judgment model, n represents a dimension of the multidimensional vector,
a value of a parameter that is preset is indicated,
a loss value representing the pre-trained additional judgment model;
the loss value judging module is used for judging whether the loss value is larger than a preset loss value or not;
and the continuous training module is used for continuously training the pre-trained additional judgment model if the loss value is greater than the preset loss value until the pre-trained additional judgment model with the loss value less than the preset loss value is obtained.
In one embodiment, the apparatus for appending the first file further includes:
the time detection module is used for detecting whether the unused time of each first link in the quick directory reaches preset time or not;
and the link clearing module is used for clearing the first link reaching the preset time from the quick directory.
In one embodiment, the apparatus for appending the first file further includes:
the first file judging module is used for judging whether each first file establishes a first link in the fast directory;
a stopping module for stopping monitoring of the first file for which the first link has been established in the fast directory.
In one embodiment, the apparatus for appending the first file further includes:
the additional score extraction module is used for extracting a first additional score of the target file;
a preset time calculation module for calculating the preset time according to the formula t ═ f (x)i) + b, calculating the preset time corresponding to the first additional score of the target file; wherein t represents a preset time, f (x)i) Representing the functional relationship between the additional score and the corresponding time, b representing the minimum value of the preset time, xiRepresenting a first append score for the ith first file.
In one embodiment, the apparatus for appending the first file further includes:
the target first folder establishing module is used for establishing a target folder of the rapid directory; wherein the target folder is used for storing various first links;
the putting-in module is used for putting the link mode of the target folder into a right mouse button menu;
and the visual click link design module is used for designing the visual click link corresponding to the link mode on a UI layer in a right mouse button menu.
The invention has the beneficial effects that: the method comprises the steps of obtaining unique identification information of a user, monitoring the first using condition of the user on each first file in real time according to the unique identification information, inputting the first using condition of each first file into a pre-trained additional judgment model to obtain a first additional score of each first file, and forming a link for a target first file according to the first additional score. Therefore, corresponding links are generated for some common or more important first files, efficient use and checking can be achieved, and user experience is improved.
Referring to fig. 3, a computer device, which may be a server and whose internal structure may be as shown in fig. 3, is also provided in the embodiment of the present application. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the computer designed processor is used to provide computational and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used for storing various additional first files and the like. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program may implement the method for adding the first file according to any one of the above embodiments when executed by the processor.
Those skilled in the art will appreciate that the architecture shown in fig. 3 is only a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects may be applied.
The embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method for adding the first file according to any of the above embodiments can be implemented.
It will be understood by those skilled in the art that all or part of the processes of the methods of the above embodiments may be implemented by hardware associated with instructions of a computer program, which may be stored on a non-volatile computer-readable storage medium, and when executed, may include processes of the above embodiments of the methods. Any reference to memory, storage, database, or other medium provided herein and used in the examples may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), double-rate SDRAM (SSRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and bus dynamic RAM (RDRAM).
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, apparatus, article, or method that includes the element.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (10)
1. A method for adding a file, comprising:
acquiring unique identification information of a user;
monitoring the first use condition of the user for each first file in real time according to the unique identification information;
inputting the first use condition of each first file into a pre-trained additional judgment model to obtain a first additional score of each first file;
taking the first file with the first additional value larger than a preset additional value in each first file as a target file, and extracting a file name, a suffix and a storage position of the target file;
forming a first link based on the storage location and generating a name of the first link based on the file name and the suffix;
adding the first link and the name to a flash directory.
2. The method for adding files according to claim 1, wherein, before the step of inputting the first usage of each first file into a pre-trained addition judgment model to obtain the first addition score of each first file, the method further comprises:
acquiring second use conditions of corresponding second files of each second link in the quick directories of the users and corresponding second additional scores;
converting the second use condition into a multi-dimensional vector according to a preset dimension; wherein the multi-dimensional vector is Xj＝(x1j，x2j…xij…xnj)，XjA multidimensional vector, x, representing a second use case of a jth second fileijAn ith dimension vector representing a second use case of the jth second file;
inputting each multi-dimensional vector and the corresponding second additional score into an additional judgment initial model for training to obtain the pre-trained additional judgment model; wherein the additional judgment initial model is hw(x)＝w0+w1x1+w2x2+wixi...+wnxnWherein h isw(x) Is the second top-up score, w0，w1，...，wnAre all the parameter values to be trained, xiRepresenting an ith vector of the multi-dimensional vectors.
3. The method for appending the file according to claim 2, wherein the step of inputting each of the multidimensional vectors and the corresponding second appending score into an appending judgment initial model for training to obtain the pre-trained appending judgment model, after the step of inputting each of the multidimensional vectors and the corresponding second appending score into the appending judgment initial model, comprises:
acquiring actual additional scores of second use conditions of the second files and predicted additional scores of the pre-trained additional judgment model;
calculating the loss value of the pre-trained additional judgment model according to a loss function formula; wherein the loss function is formulated as:
yjrepresents the actual additional score, h, corresponding to the second usage of the j second filesw(xij) A predicted addition score obtained by inputting a second use case of a jth second file into the pre-trained addition judgment model, n represents a dimension of the multidimensional vector,
a value of a parameter that is preset is indicated,
a loss value representing the pre-trained additional judgment model;
judging whether the loss value is larger than a preset loss value or not;
if the loss value is larger than the preset loss value, the pre-trained additional judgment model continues to be trained until the pre-trained additional judgment model with the loss value smaller than the preset loss value is obtained.
4. The method for adding files according to claim 1, wherein the step of adding the first link and the name to a flash directory is followed by the step of:
detecting whether the unused time of each first link in the quick directory reaches a preset time or not;
and clearing the first link reaching the preset time from the rapid directory.
5. The method for appending files according to claim 1, wherein, before the step of obtaining the first usage of each first file by the user in real time according to the unique identifier information, the method further comprises:
judging whether each first file establishes a first link in the fast directory or not;
monitoring for the first file for which the first link has been established in the fast directory is stopped.
6. The method for appending a file according to claim 4, wherein before the step of detecting whether the unused time of each of the first links in the fast directory reaches a preset time, the method further comprises:
extracting a first additional score of the target file;
according to the formula t ═ f (x)i) + b, calculating the preset time corresponding to the first additional score of the target file; wherein t represents a preset time, f (x)i) Representing the functional relationship between the additional score and the corresponding time, b representing the minimum value of the preset time, xiRepresenting a first append score for the ith first file.
7. The method for appending a file according to claim 1, wherein the step of adding the first link and the name to a flash directory is preceded by the step of:
establishing a target folder of the rapid directory; wherein the target folder is used for storing various first links;
putting the link mode of the target folder into a right mouse button menu;
and designing a visual click link corresponding to the link mode on a UI layer in a right mouse button menu.
8. An apparatus for adding a file, comprising:
the acquisition module is used for acquiring the unique identification information of the user;
the monitoring module is used for monitoring the first use condition of each first file by the user in real time according to the unique identification information;
the input module is used for inputting the first use condition of each first file into a pre-trained additional judgment model to obtain a first additional score of each first file;
an extraction module, configured to take the first file with the first additional score being greater than a preset additional score in each first file as a target file, and extract a file name, a suffix, and a storage location of the target file;
the generating module is used for forming a first link based on the storage position and generating the name of the first link based on the file name and the suffix;
and the adding module is used for adding the first link and the name into a quick directory.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111087221.3A CN113778951B (en) | 2021-09-16 | 2021-09-16 | File adding method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111087221.3A CN113778951B (en) | 2021-09-16 | 2021-09-16 | File adding method, device, equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113778951A true CN113778951A (en) | 2021-12-10 |
| CN113778951B CN113778951B (en) | 2024-04-26 |
Family
ID=78851419
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111087221.3A Active CN113778951B (en) | 2021-09-16 | 2021-09-16 | File adding method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113778951B (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011028716A (en) * | 2009-06-26 | 2011-02-10 | Victor Co Of Japan Ltd | Backup device and backup method |
| CN104185834A (en) * | 2012-03-28 | 2014-12-03 | 宇龙计算机通信科技(深圳)有限公司 | Error correction method for operation objects and communication terminal |
| CN108319602A (en) * | 2017-01-17 | 2018-07-24 | 广州市动景计算机科技有限公司 | Data base management method and Database Systems |
| CN108898588A (en) * | 2018-06-22 | 2018-11-27 | 中山仰视科技有限公司 | Therapeutic effect appraisal procedure based on time series, electronic equipment |
| CN111104831A (en) * | 2018-10-29 | 2020-05-05 | 香港城市大学深圳研究院 | Visual tracking method, device, computer equipment and medium |
| CN111400261A (en) * | 2020-01-21 | 2020-07-10 | 行星算力(深圳)科技有限公司 | Method for rapidly adding or deleting folders by IPFS (Internet protocol file system) |
| CN112749131A (en) * | 2020-06-11 | 2021-05-04 | 腾讯科技（上海）有限公司 | Information duplicate elimination processing method and device and computer readable storage medium |
| CN112925753A (en) * | 2021-03-25 | 2021-06-08 | 平安科技（深圳）有限公司 | File additional writing method and device, electronic equipment and storage medium |
-
2021
- 2021-09-16 CN CN202111087221.3A patent/CN113778951B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011028716A (en) * | 2009-06-26 | 2011-02-10 | Victor Co Of Japan Ltd | Backup device and backup method |
| CN104185834A (en) * | 2012-03-28 | 2014-12-03 | 宇龙计算机通信科技(深圳)有限公司 | Error correction method for operation objects and communication terminal |
| CN108319602A (en) * | 2017-01-17 | 2018-07-24 | 广州市动景计算机科技有限公司 | Data base management method and Database Systems |
| CN108898588A (en) * | 2018-06-22 | 2018-11-27 | 中山仰视科技有限公司 | Therapeutic effect appraisal procedure based on time series, electronic equipment |
| CN111104831A (en) * | 2018-10-29 | 2020-05-05 | 香港城市大学深圳研究院 | Visual tracking method, device, computer equipment and medium |
| CN111400261A (en) * | 2020-01-21 | 2020-07-10 | 行星算力(深圳)科技有限公司 | Method for rapidly adding or deleting folders by IPFS (Internet protocol file system) |
| CN112749131A (en) * | 2020-06-11 | 2021-05-04 | 腾讯科技（上海）有限公司 | Information duplicate elimination processing method and device and computer readable storage medium |
| CN112925753A (en) * | 2021-03-25 | 2021-06-08 | 平安科技（深圳）有限公司 | File additional writing method and device, electronic equipment and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 李生武;张选德;: "基于自注意力机制的多域卷积神经网络的视觉追踪", 计算机应用, no. 08 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113778951B (en) | 2024-04-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107609163B (en) | Medical knowledge map generation method, storage medium and server | |
| CN109815333B (en) | Information acquisition method and device, computer equipment and storage medium | |
| CN109800307B (en) | Product evaluation analysis method and device, computer equipment and storage medium | |
| JP6306400B2 (en) | Skill evaluation apparatus, program and method for evaluating worker skill in crowdsourcing | |
| CN111192025A (en) | Occupational information matching method and device, computer equipment and storage medium | |
| WO2022148038A1 (en) | Information recommendation method and device | |
| CN110516210B (en) | Text similarity calculation method and device | |
| CN111461301A (en) | Serialized data processing method and device, and text processing method and device | |
| CN113704436A (en) | User portrait label mining method and device based on session scene | |
| CN112685475A (en) | Report query method and device, computer equipment and storage medium | |
| CN112732898A (en) | Document abstract generation method and device, computer equipment and storage medium | |
| CN111597422A (en) | Buried point mapping method and device, computer equipment and storage medium | |
| CN110413994B (en) | Hot topic generation method and device, computer equipment and storage medium | |
| CN113128526B (en) | Image recognition method and device, electronic equipment and computer-readable storage medium | |
| CN110609618A (en) | Man-machine conversation method and device, computer equipment and storage medium | |
| CN110245314A (en) | A kind of web page fingerprint generation method | |
| CN109660621A (en) | A kind of content delivery method and service equipment | |
| CN113342927A (en) | Sensitive word recognition method, device, equipment and storage medium | |
| CN113778951A (en) | File addition method, device, equipment and storage medium | |
| CN112364620B (en) | Text similarity judging method and device and computer equipment | |
| CN115345166A (en) | Method, device, equipment and storage medium for identifying disease diagnosis name of medical text | |
| CN106815592B (en) | Text data processing method and device and wrong word recognition methods and device | |
| CN113312481A (en) | Text classification method, device and equipment based on block chain and storage medium | |
| CN113657496A (en) | Information matching method, device, equipment and medium based on similarity matching model | |
| EP3136260A1 (en) | Information analysis system, information analysis method and information analysis program |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |