Data analysis method and device, electronic equipment and storage medium

Abstract

The embodiment of the application provides a data analysis method and device, electronic equipment and a storage medium. The target network disk is mounted through the client, the target network disk includes a plurality of file directories, and the to-be-analyzed data is uploaded to a specified file target, so that the server can analyze the to-be-analyzed data by using the intelligent analysis algorithm corresponding to the specified file directory, online data analysis is realized, different file directories correspond to different intelligent analysis algorithms, the user only needs to upload the to-be-analyzed data to the specified file target, and data analysis can be realized, the user does not need to set an upload path, and the user does not need to manually select an intelligent analysis algorithm, the operation is cumbersome, the user is convenient to use, the convenience of data analysis can be improved, and in addition, the to-be-analyzed data is retained in the target network disk, so that even if the user replaces the local client equipment, the to-be-analyzed data and the analysis result can still be obtained from the network disk, and the convenience of data analysis is further improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer, in particular to a data analysis method and device, electronic equipment and storage medium. BACKGROUND

[0002] In the process of working locally, users often encounter scenarios of intelligent analysis of data. In related technologies, users need to upload data to be analyzed to a server through a client application or a webpage, and analyze the data by using intelligent algorithms in the server. However, by using the above method, users need to select data to be analyzed by using a client application or a webpage, and need to select intelligent algorithms to be used by using a client application or a webpage, which is complicated and inconvenient for users to use, resulting in inconvenience of data analysis. SUMMARY

[0003] Embodiments of the present application aim to provide a data analysis method and device, electronic equipment and storage medium to improve the convenience of data analysis. The specific technical solutions are as follows:

[0004] In a first aspect, the embodiments of the present application provide a data analysis method applied to a client, which comprises:

[0005] Displaying each file directory of a target network disk that has been mounted, wherein different file directories correspond to different intelligent analysis algorithms;

[0006] Obtaining a file storage instruction input by a user based on the displayed each file directory, the file storage instruction indicating that data to be analyzed is stored in a specified file directory;

[0007] In response to the file storage instruction, uploading the data to be analyzed to the specified file directory of the target network disk in the server, so that the server analyzes the data to be analyzed by using the intelligent analysis algorithm corresponding to the specified file directory;

[0008] Downloading an analysis result of the data to be analyzed from the server.

[0009] In a possible implementation, the method further comprises:

[0010] Sending a mounting request for a target network disk to a server;

[0011] Obtaining attribute information of the target network disk sent by the server;

[0012] Based on the attribute information of the target network disk, mounting the target network disk locally.

[0013] In a possible implementation, the mounting the target network disk locally based on the attribute information of the target network disk comprises:

[0014] generating mounting protocol data for the first port based on the attribute information of the target network disk;

[0015] converting the mounting protocol data for the first port into mounting protocol data for a second port, wherein the second port is a port listened to by the server;

[0016] sending the mounting protocol data for the second port to the server to complete mounting the target network disk locally.

[0017] In a possible implementation, the specified file directory includes a first folder, and the first folder is used to store to-be-analyzed data.

[0018] The uploading of the to-be-analyzed data into the specified file directory of the target network disk of the server in response to the file storage instruction includes:

[0019] The uploading of the to-be-analyzed data into the first folder of the specified file directory of the target network disk of the server in response to the file storage instruction.

[0020] In a possible implementation, the specified file directory includes a second folder, and the second folder is used to store analysis results.

[0021] The downloading of the analysis results of the to-be-analyzed data from the server includes:

[0022] In a case where the to-be-analyzed data is analyzed successfully, the analysis results of the to-be-analyzed data are downloaded from the second folder of the specified file directory of the target network disk of the server.

[0023] In a possible implementation, the method further includes:

[0024] obtaining a to-be-searched keyword for a target network disk, sending a target search instruction containing the to-be-searched keyword to the server, so that the server searches description sentences corresponding to the target network disk by using the to-be-searched keyword, to obtain search results of the to-be-searched keyword, wherein the description sentences corresponding to the target network disk are description sentences extracted from target data for a fourth folder in the target network disk uploaded by the client;

[0025] receiving search results returned by the server according to the target search instruction.

[0026] In a second aspect, an embodiment of the present application provides a data analysis method, applied to a server, and the method includes:

[0027] receiving data uploaded by a client for a specified file directory in a target network disk, and storing the data in the specified file directory in the target network disk, wherein the target network disk comprises file directories, and different file directories correspond to different intelligent analysis algorithms;

[0028] analyzing the data by using a target intelligent analysis algorithm corresponding to the specified file directory, to obtain an analysis result of the data;

[0029] sending the analysis result of the data to the client.

[0030] In a possible implementation, the specified file directory comprises a first folder, and the first folder is used to store data to be analyzed.

[0031] The storing of the data to be analyzed in the specified file directory in the target network disk comprises:

[0032] storing the data to be analyzed in a first folder of the specified file directory in the target network disk.

[0033] In a possible implementation, the specified file directory comprises a second folder, and the second folder is used to store an analysis result.

[0034] The method further comprises:

[0035] storing the analysis result of the data in a second folder of the specified file directory;

[0036] copying the data to be analyzed from the first folder of the specified file directory to the second folder of the specified file directory.

[0037] In a possible implementation, the specified file directory comprises a third folder, and the third folder is used to store data to be analyzed that fails in analysis.

[0038] The method further comprises:

[0039] In the case that the data to be analyzed fails in analysis, copying the data to be analyzed from the first folder of the specified file directory to the third folder of the specified file directory.

[0040] In a possible implementation, the method further comprises:

[0041] receiving target data uploaded by a client for a fourth folder in a target network disk, and storing the target data in the fourth folder of the specified file directory in the target network disk;

[0042] extracting a description phrase from the target data, to obtain a description phrase corresponding to the target network disk;

[0043] receiving a target search instruction sent by a client, wherein the target search instruction includes a network disk identifier of a network disk to be detected and a keyword to be searched;

[0044] determining a network disk to be searched according to the network disk identifier of the network disk to be detected in the target search instruction;

[0045] searching a description phrase corresponding to the network disk to be searched by using the keyword to be searched, to obtain a search result of the keyword to be searched;

[0046] sending the search result to the client.

[0047] In a third aspect, an embodiment of the present application provides a data analysis apparatus applied to a client, and the apparatus comprises:

[0048] a file directory display module configured to display each file directory of a target network disk mounted, wherein different file directories correspond to different intelligent analysis algorithms;

[0049] a file storage instruction acquisition module configured to acquire a file storage instruction input by a user based on each displayed file directory, the file storage instruction indicating that to-be-analyzed data is stored in a specified file directory;

[0050] a to-be-analyzed data sending module configured to upload the to-be-analyzed data into the specified file directory of the target network disk of a server in response to the file storage instruction, so that the server analyzes the to-be-analyzed data by using an intelligent analysis algorithm corresponding to the specified file directory;

[0051] an analysis result acquisition module configured to download an analysis result of the to-be-analyzed data from the server.

[0052] In a possible implementation, the apparatus further comprises a target network disk mounting module configured to: send a mounting request for a target network disk to a server; acquire attribute information of the target network disk sent by the server; and mount the target network disk locally based on the attribute information of the target network disk.

[0053] In a possible implementation, the target network disk mounting module is specifically configured to: generate mounting protocol data for a first port based on the attribute information of the target network disk; convert the mounting protocol data for the first port into mounting protocol data for a second port, wherein the second port is a port listened to by the server; and send the mounting protocol data for the second port to the server, so as to complete mounting the target network disk locally.

[0054] In a possible implementation, the specified file directory includes a first folder, and the first folder is used to store the data to be analyzed; and the data to be analyzed sending module is specifically configured to: in response to the file storage instruction, upload the data to be analyzed into the first folder of the specified file directory of the target network disk of the server.

[0055] In a possible implementation, the specified file directory includes a second folder, and the second folder is used to store the analysis result; and the analysis result obtaining module is specifically configured to: in the case that the analysis of the data to be analyzed is successful, download the analysis result of the data to be analyzed from the second folder of the specified file directory of the target network disk of the server.

[0056] In a possible implementation, the apparatus further includes a retrieval result obtaining module, configured to: obtain a keyword to be retrieved for a target network disk, send a target retrieval instruction containing the keyword to be retrieved to the server, so that the server retrieves a description sentence corresponding to the target network disk by using the keyword to be retrieved, to obtain a retrieval result of the keyword to be retrieved, wherein the description sentence corresponding to the target network disk is a description sentence extracted from target data of a fourth folder in the target network disk uploaded by the client; and receive the retrieval result returned by the server according to the target retrieval instruction.

[0057] In a fourth aspect, an embodiment of the present application provides a data analysis apparatus, applied to a server, and the apparatus includes:

[0058] a data to be analyzed obtaining module, configured to receive data to be analyzed uploaded by a client for a specified file directory in a target network disk, and store the data to be analyzed into the specified file directory of the target network disk, wherein the target network disk includes file directories, and different file directories correspond to different intelligent analysis algorithms;

[0059] an analysis result generating module, configured to analyze the data to be analyzed by using a target intelligent analysis algorithm corresponding to the specified file directory, to obtain an analysis result of the data to be analyzed;

[0060] an analysis result sending module, configured to send the analysis result of the data to be analyzed to the client.

[0061] In a possible implementation, the specified file directory includes a first folder, and the first folder is used to store the data to be analyzed; and the data to be analyzed obtaining module is specifically configured to: store the data to be analyzed into the first folder of the specified file directory of the target network disk.

[0062] In a possible implementation, the specified file directory includes a second folder, and the second folder is used to store analysis results.

[0063] The device further includes an analysis result storage module, configured to store the analysis result of the to-be-analyzed data in the second folder of the specified file directory, and to copy the to-be-analyzed data from the first folder of the specified file directory to the second folder of the specified file directory.

[0064] In a possible implementation, the specified file directory includes a third folder, and the third folder is used to store to-be-analyzed data that fails in analysis; the device further includes a to-be-analyzed data copying module, configured to, in a case where the to-be-analyzed data fails in analysis, copy the to-be-analyzed data from the first folder of the specified file directory to the third folder of the specified file directory.

[0065] In a possible implementation, the device further includes a keyword searching module, configured to receive target data uploaded by a client for a fourth folder in a target network disk, and to store the target data in the fourth folder of a specified file directory of the target network disk; extract a description sentence from the target data to obtain a description sentence corresponding to the target network disk; receive a target searching instruction sent by the client, wherein the target searching instruction includes a network disk identifier of a to-be-detected network disk and a to-be-searched keyword; determine a to-be-searched network disk according to the network disk identifier of the to-be-detected network disk in the target searching instruction; search the description sentence corresponding to the to-be-searched network disk by using the to-be-searched keyword to obtain a searching result of the to-be-searched keyword; and send the searching result to the client.

[0066] In a fifth aspect, an electronic device is provided, including a processor and a memory;

[0067] The memory is configured to store a computer program.

[0068] The processor is configured to execute the program stored in the memory, and implement the data analysis method in any of the embodiments of the present application.

[0069] In a sixth aspect, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program. The computer program is executed by a processor to implement the data analysis method in any of the embodiments of the present application.

[0070] In a seventh aspect, a computer program product is provided. When the computer program product is executed on a computer, the computer program product causes the computer to execute the data analysis method in any of the embodiments of the present application.

[0071] The embodiments of the present application have the following beneficial effects:

[0072] The data analysis method, device, electronic device and storage medium provided by the embodiments of the present application mount a target network disk through a client, the target network disk includes a plurality of file directories, and the to-be-analyzed data is uploaded to a specified file target, so that the server can analyze the to-be-analyzed data by using the intelligent analysis algorithm corresponding to the specified file directory, online analysis of the data is realized, the user can download the analysis result of the to-be-analyzed data through the client, different file directories correspond to different intelligent analysis algorithms, the user only needs to upload the to-be-analyzed data to the specified file target, and the analysis of the data can be realized, without the user setting an upload path and manually selecting an intelligent analysis algorithm, the operation is complicated, the user is convenient to use, and the convenience of data analysis can be improved. In addition, the to-be-analyzed data is retained in the target network disk, even if the user replaces the local client device, the to-be-analyzed data and the analysis result can still be obtained from the network disk, and the convenience of data analysis is further improved. Of course, any product or method implementing the present application does not necessarily need to achieve all the advantages described above. BRIEF DESCRIPTION OF DRAWINGS

[0073] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art based on these drawings.

[0074] Figure 1 It is a first schematic diagram of the data analysis method of the embodiments of the present application.

[0075] Figure 2 It is a schematic diagram of the network disk mounting of the embodiments of the present application.

[0076] Figure 3 It is a schematic diagram of the specified file directory of the embodiments of the present application.

[0077] Figure 4 It is a second schematic diagram of the data analysis method of the embodiments of the present application.

[0078] Figure 5 It is a third schematic diagram of the data analysis method of the embodiments of the present application.

[0079] Figure 6 It is a fourth schematic diagram of the data analysis method of the embodiments of the present application.

[0080] Figure 7 It is a first schematic diagram of the data analysis device of the embodiments of the present application.

[0081] Figure 8Fig. 2 is a second schematic diagram of the data analysis device according to an embodiment of the present application;

[0082] Figure 9 Fig. 1 is a schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0083] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art based on the present application belong to the scope of protection of the present application.

[0084] First, the terms in the present application are explained:

[0085] NAS (Network Attached Storage): NAS refers to a device connected to a network with data storage function, also known as "network storage", which is a special data storage server.

[0086] SMB (Server Message Block): It is a communication protocol between a client and a server connected by Web.

[0087] AI retrieval: provides keyword search for file content and locates the position of the keyword in the file for all files (including pictures, documents, audio, video, etc.) under the specified directory.

[0088] Inverted index: also called reverse index, there is a forward index for every reverse index. In simple terms, the forward index is to find value by key, and the reverse index is to find key by value.

[0089] MD5 (Message-Digest Algorithm MD5): a widely used cryptographic hash function that can produce a 128-bit (16-byte) hash value to ensure the integrity of information transmission.

[0090] ES (Elasticsearch) is an open source high-extensible distributed full-text search engine. It can store and retrieve data in near real time, has good scalability, and can be expanded to hundreds of servers to handle PB-level data.

[0091] In the process of local work, the user needs to upload the data to be analyzed to the server through a client application or a webpage, and analyze the data by using the intelligent algorithm in the server. However, by using the above method, the user needs to select the data to be analyzed by using the client application or the webpage, and needs to select the intelligent algorithm to be used by using the client application or the webpage, which is complicated and inconvenient for the user to use, and causes inconvenience for data analysis.

[0092] Therefore, the embodiment of the present application provides a data analysis method applied to a client, as shown in Figure 1 , the method comprises:

[0093] S101, display each file directory of the target network disk mounted, wherein different file directories correspond to different intelligent analysis algorithms.

[0094] The data analysis method in the embodiment of the present application is applied to the client, so it can be realized through the client. In an example, the client can be a smart phone, a smart camera, a personal computer, etc.

[0095] The target network disk is a network disk mounted by the client. In an example, the network disk can be a NAS network disk. Each file directory of the target network disk mounted by the client is displayed in the client, and different file directories correspond to different intelligent analysis algorithms, for example, a list control file directory corresponds to a list control intelligent analysis algorithm, a video structured file directory corresponds to a video structured intelligent analysis algorithm, a picture structured file directory corresponds to a picture structured intelligent analysis algorithm, a voice recognition file directory corresponds to a voice recognition intelligent analysis algorithm, an ID card batch recognition file directory corresponds to an ID card batch recognition intelligent analysis algorithm, an OCR general document recognition file directory corresponds to an OCR general document recognition intelligent analysis algorithm, and an OCR record conflict detection file directory corresponds to an OCR record conflict detection intelligent analysis algorithm.

[0096] The list control intelligent analysis algorithm is used to place the face photos of people to be controlled in the directory in advance, automatically analyze and model these face photos, and compare the models of the face photos output by the video structured and picture structured analysis, and if a certain similarity is met, an alarm prompt is given in the archiving folder (the second folder).

[0097] The video structured intelligent analysis algorithm is used to read the video file under the directory, call the video structured algorithm, extract the information of people, vehicles and faces in the video file, and generate the corresponding report file.

[0098] The picture structured intelligent analysis algorithm is used to read the picture file under the directory, call the picture structured algorithm, extract the information of people, vehicles and faces in the picture file, and generate the corresponding report file.

[0099] The voice recognition intelligent analysis algorithm is used to read the audio or audio-video files under the directory, call the voice recognition algorithm, identify the dialogue content and corresponding time interval in the material, and generate a corresponding report file

[0100] The identity card batch recognition intelligent analysis algorithm is used to read the identity card pictures under the directory, call the OCR recognition algorithm, identify the text information on the identity card pictures, and save it as a report file

[0101] The OCR general document recognition intelligent analysis algorithm is used to read the text pictures under the directory, call the OCR general document recognition algorithm, identify the text on the document pictures, and save it as a report file, which is suitable for identifying important documents, record pictures, etc.

[0102] The OCR record conflict detection intelligent analysis algorithm is used to read the record document pictures under the directory, call the OCR record conflict algorithm, extract the record key information, and analyze and judge, alarm and remind the parallel time inquiry and the record of the inquired, and generate a report file.

[0103] S102, obtaining a file storage instruction input by a user based on each file directory displayed, indicating to store the to-be-analyzed data in a specified file directory.

[0104] Based on each file directory displayed, the user determines which intelligent analysis algorithm needs to be used, and the file directory corresponding to the intelligent analysis algorithm to be used is referred to as a specified file directory. The user issues a file storage instruction to store the to-be-analyzed data in the specified file directory, and the client obtains the file storage instruction issued by the user. In an example, the file storage instruction can be a paste instruction, and the user can issue the file storage instruction by pasting the to-be-analyzed data into the specified file directory.

[0105] S103, in response to the file storage instruction, uploading the to-be-analyzed data to the specified file directory of the target network disk of the server, so that the server analyzes the to-be-analyzed data by using the intelligent analysis algorithm corresponding to the specified file directory.

[0106] In response to a file storage instruction issued by the user, the client uploads the data to be analyzed to a specified file directory of the target network disk of the server. After receiving the data to be analyzed, the server can analyze the data to be analyzed by using the intelligent analysis algorithm corresponding to the specified file directory, so as to obtain the analysis result of the data to be analyzed. For example, after the data to be analyzed is uploaded to the voice recognition file directory of the target network disk, the server can analyze the data to be analyzed in the voice recognition file directory by using the voice recognition intelligent analysis algorithm, so as to obtain the voice recognition result of the data to be analyzed. In one example, after the data to be analyzed is uploaded, the user can issue an instruction indicating to perform analysis, so that the server starts to analyze the data to be analyzed by using the intelligent analysis algorithm corresponding to the specified file directory.

[0107] S104, downloading the analysis result of the data to be analyzed from the server.

[0108] After the server completes the analysis of the data to be analyzed, the client downloads the analysis result of the data to be analyzed from the server. In one example, the server can feed back the analysis progress of the data to be analyzed to the client, and the client can display the analysis progress of the data to be analyzed locally, so as to facilitate the user to understand the analysis progress.

[0109] The network disk in the related art is implemented by uploading files through a client or a webpage. In the embodiments of the present application, as shown in FIG. 1, Figure 2 As shown in FIG. 1, the computer resource manager is restored by using the mounting mode, so as to realize the data uploading and intelligent analysis function, which is simple, convenient, easy to learn and understand, and can obtain the analysis result at one time. Even if the user does not have the knowledge of intelligent algorithm, the user can also use it, and the application range of the user is wider.

[0110] In the embodiments of the present application, the target network disk is mounted by using the client, the target network disk includes a plurality of file directories, and the data to be analyzed is uploaded to a specified file directory, so that the server can analyze the data to be analyzed by using the intelligent analysis algorithm corresponding to the specified file directory, the online analysis of the data is realized, the user can download the analysis result of the data to be analyzed through the client, different file directories correspond to different intelligent analysis algorithms, the user only needs to upload the data to be analyzed to the specified file directory, and the analysis of the data can be realized without setting the uploading path by the user or manually selecting the intelligent analysis algorithm by the user. The operation is complicated, the user uses conveniently, the convenience of data analysis is improved; in addition, the data to be analyzed is retained in the target network disk, even if the user replaces the local client device, the data to be analyzed and the analysis result can still be obtained from the network disk, and the convenience of data analysis is further improved.

[0111] Before displaying the file directory of the target network disk, the target network disk needs to be mounted locally on the client. In a possible implementation, the method further includes:

[0112] Step 1: sending a mounting request for the target network disk to the server.

[0113] The mounting request includes the identifier of the target network disk, and can further include user identity or permission verification information, for example, an SMS verification code, an account password, and the like, so that the server performs permission verification, thereby determining whether the client sending the mounting request has the permission to use the target network disk.

[0114] Step 2: obtaining the attribute information of the target network disk sent by the server.

[0115] After the mounting request is verified, the server sends the attribute information of the target network disk to the client, and the attribute information of the target network disk can include the size, usage, and mounting address of the target network disk. The client receives the attribute information of the target network disk sent by the server.

[0116] Step 3: mounting the target network disk locally based on the attribute information of the target network disk.

[0117] The client mounts the target network disk locally based on the attribute information of the target network disk. For example, as shown in FIG. 10, a personal computer is taken as an example, and the mounted target network disk, network disk 1, is displayed in a network location. Figure 2

[0118] In a possible implementation, the mounting of the target network disk locally based on the attribute information of the target network disk includes:

[0119] Step A: generating mounting protocol data for a first port based on the attribute information of the target network disk;

[0120] Step B: converting the mounting protocol data for the first port into mounting protocol data for a second port, where the second port is a port listened to by the server;

[0121] Step C: sending the mounting protocol data for the second port to the server, so as to complete the mounting of the target network disk locally.

[0122] ​Due to the possible existence of scene environment constraints of the client and the server, for example, the restriction of using network communication ports such as 445, 593, 1025, 2745, 3127, 135, 6129, 3389, 22, Telnet, 137, 138, 139, 135, 901, and the like. In view of such restrictions, the client needs to use the SMB, SSHFS (Secure Shell Filesystem), SFTP (Secure File Transfer Protocol), CIFS (Common Internet File System), NFS (Network File System), and the like mounting protocols to forward other ports through the 445 port to realize cross-port communication according to the port listened by the server. This design does not limit other mounting protocols such as the like. In one example, the server listens to the 7445 port, and the client requests the 445 port, which can realize the mounting protocol by forwarding the 445 port data to the remote 7445 through the proxy service of the client.

[0123] In the embodiment of the present application, in the case that the port of the client is different from that of the server, the network disk in the server is mounted by the client through port conversion, which is suitable for the scenario that the port of the client is different from that of the server.

[0124] In a possible implementation, the specified file directory includes a first folder, and the first folder is used to store the to-be-analyzed data.

[0125] The uploading of the to-be-analyzed data into the specified file directory of the target network disk of the server in response to the file storage instruction includes:

[0126] The uploading of the to-be-analyzed data into the first folder of the specified file directory of the target network disk of the server in response to the file storage instruction.

[0127] In one example, as shown in Figure 3 the first folder is a folder named "new file here", and after the uploading of the to-be-analyzed data is completed, the user can click the AI analysis option to start analyzing the data in the first folder by using the intelligent analysis algorithm corresponding to the specified file directory.

[0128] In a possible implementation, the specified file directory includes a second folder, and the second folder is used to store the analysis result.

[0129] The downloading of the analysis result of the to-be-analyzed data from the server includes:

[0130] In the case that the analysis of the to-be-analyzed data is successful, the analysis result of the to-be-analyzed data is downloaded from a second folder of a specified file directory of the target network disk of the server.

[0131] In one example, as shown in Figure 3 the second folder is a folder named "Archived". After the analysis of the data in the first folder is completed, the server stores the analysis result in the second folder, and the client downloads the analysis result of the to-be-analyzed data from the second folder of the specified file directory of the target network disk of the server.

[0132] In the embodiments of the present application, the to-be-analyzed data and the analysis result are managed by different folders, which facilitates the management of data.

[0133] During the analysis of the to-be-analyzed data, the server can also extract the description words of the to-be-analyzed data, such as the description words of the features of the people in the video, such as the text words after the audio is converted into text, such as the description words of the text information and the description information in the picture, and the like, thereby providing a data retrieval service based on keywords. In one possible implementation, the method further includes:

[0134] Step 1: Obtain the to-be-retrieved keywords for the target network disk, and send a target retrieval instruction containing the to-be-retrieved keywords to the server.

[0135] Step 2: Receive the retrieval result returned by the server according to the target retrieval instruction.

[0136] In one example, the target network disk can further include a fourth folder, in which the user can store the target data to be detected, and the server can extract the description words of the target data, thereby matching the to-be-retrieved keywords in the target retrieval instruction to complete the retrieval of data.

[0137] In the embodiments of the present application, the user can retrieve the data in the target network disk by keywords, which can further facilitate the management and analysis of data.

[0138] The embodiments of the present application also provide a data analysis method applied to a server, as shown in Figure 4 , the method includes:

[0139] S401: Receive the to-be-analyzed data uploaded by the client for a specified file directory of a target network disk, and store the to-be-analyzed data in the specified file directory of the target network disk, wherein the target network disk includes file directories, and different file directories correspond to different intelligent analysis algorithms.

[0140] The data analysis method in the embodiments of the present application is applied to a server, and thus can be implemented by the server. The manner in which the client uploads the to-be-analyzed data for a specified file directory in a target network disk can refer to the data analysis method applied to the client, which will not be described here again.

[0141] S402, analyzing the to-be-analyzed data by using a target intelligent analysis algorithm corresponding to the specified file directory, to obtain an analysis result of the to-be-analyzed data.

[0142] S403, sending the analysis result of the to-be-analyzed data to the client.

[0143] In the embodiments of the present application, the target network disk is mounted by the client, the target network disk includes a plurality of file directories, and the to-be-analyzed data is uploaded to a specified file target, so that the server can analyze the to-be-analyzed data by using an intelligent analysis algorithm corresponding to the specified file directory, online analysis of the data is realized, the user can download the analysis result of the to-be-analyzed data through the client, different file directories correspond to different intelligent analysis algorithms, the user only needs to upload the to-be-analyzed data to the specified file target, and thus the analysis of the data can be realized, the user does not need to set an upload path, and the user does not need to manually select an intelligent analysis algorithm, which is complicated in operation and convenient for the user to use, and the convenience of data analysis can be improved. In addition, the to-be-analyzed data is retained in the target network disk, so that even if the user replaces the local client device, the to-be-analyzed data and the analysis result can still be obtained from the network disk, and the convenience of data analysis is further improved.

[0144] In a possible implementation, the specified file directory includes a first folder, and the first folder is used to store the to-be-analyzed data; and the method of storing the to-be-analyzed data in the specified file directory of the target network disk includes: storing the to-be-analyzed data in the first folder of the specified file directory of the target network disk.

[0145] In a possible implementation, the specified file directory includes a second folder, and the second folder is used to store the analysis result; and the method further includes:

[0146] Step one, storing the analysis result of the to-be-analyzed data in the second folder of the specified file directory.

[0147] Step two, transferring the to-be-analyzed data from the first folder of the specified file directory to the second folder of the specified file directory.

[0148] In addition to storing the analysis result of the to-be-analyzed data, the second folder can also archive the to-be-analyzed data that has completed analysis, so as to facilitate the user to view the to-be-analyzed data and the analysis result in the same folder.

[0149] In one example, for example Figure 5 As shown, the server can include a mounting service, an application service, and an analysis service. The mounting service is used to mount the target hard drive. The mounting method for the target hard drive can be found in the above embodiments and will not be repeated here. After the client successfully mounts the target hard drive of the server, it monitors the file directory of the target hard drive through the application service. The client uploads data files to the specified file directory. Once the application service detects a new file in the target file directory, it will repeatedly calculate the file size and MD5 value until the file size and MD5 value are fixed, and then confirm that the file upload is complete. The client triggers the submission of a smart analysis command by right-clicking. After receiving the command, the application service obtains the size of the file to be analyzed and determines the type of smart algorithm to be used, and generates a smart analysis task. The application service sends the smart analysis task to the analysis service. The analysis service uses the GPU to load the corresponding smart analysis algorithm and perform file reading and analysis. After the analysis is completed, the analysis service returns the analysis results to the application service, and the application service stores the analysis results in a second folder. The client can download and display the analysis results by opening the analysis results in the second folder.

[0150] In one possible implementation, the designated file directory includes a third folder for storing the data to be analyzed that failed to be analyzed; the method further includes:

[0151] If the analysis of the data to be analyzed fails, the data to be analyzed will be transferred from the first folder of the specified file directory to the third folder of the specified file directory.

[0152] In one example, for example Figure 3 As shown, the third folder is named "Pending Verification". If the analysis of the data fails, the server will transfer the data from the first folder to the third folder, allowing users to easily view the failed data and facilitating data management.

[0153] During the analysis of the data to be analyzed, the server can also extract descriptive terms from the data, such as descriptive terms about the gender, age, and clothing of people in a video; textual terms after audio is converted into text; and descriptive terms about text and descriptions in images, thereby providing keyword-based data retrieval services. In one possible implementation, the method further includes:

[0154] Step A: Receive the target data uploaded by the client for the fourth folder in the target cloud drive, and store the target data in the fourth folder of the specified file directory of the target cloud drive.

[0155] Step B: Extract descriptive terms from the target data to obtain the descriptive terms corresponding to the target cloud drive.

[0156] Step C: Receive the target search instruction sent by the client, wherein the target search instruction includes the cloud drive identifier to be detected and the keywords to be searched.

[0157] Step D: Determine the cloud drive to be searched according to the cloud drive identifier in the target search instruction.

[0158] Step E: Use the keywords to be searched to search the descriptive phrases corresponding to the cloud drive to be searched, and obtain the search results of the keywords to be detected.

[0159] Step F: Send the search results to the client.

[0160] The fourth folder is more like a storage drive that users frequently use in their daily lives, where they can freely store and edit files. The server automatically analyzes the content of the files in this folder, extracting all the textual information that the file can describe or contains, i.e., extracting descriptive terms. For example, text information can be extracted from text documents or image data, audio information from audio files, and structured information about people, vehicles, and faces from images or videos. For example, for people or faces, structured descriptive information such as gender, age group, and clothing colors will be output; for vehicles, structured descriptive information such as license plate, vehicle type, and body color will be output. Finally, this textual information is stored in a database and provided for external retrieval services. After a large number of files have accumulated in the fourth folder, users can not only search for the files they want by filename, but also retrieve related files by the textual information or descriptive content contained within them.

[0161] In one example, for example Figure 6 As shown, the server can include a mount service, an application service, an analytics service, and a storage service. The mount service is used to mount the target hard drive. After successfully mounting the target hard drive on the server, the client can upload data files to the fourth folder of the target hard drive.

[0162] On the server side, the application service performs real-time file detection on the fourth folder. Once a new file is detected, its size and MD5 value are repeatedly calculated until they stabilize. After confirming the file upload is complete, an analysis task is automatically triggered, notifying the analysis service to invoke the corresponding intelligent analysis algorithm for file reading and analysis. The application service can invoke different intelligent analysis algorithms based on different file types; for example, image files can utilize image classification algorithms for content pre-detection. In one example, the file types and intelligent analysis algorithm types are shown in Table 1.

[0163] Table 1

[0164]

[0165] After the analysis is completed, the application service stores the analysis result into a storage service, in an example, the storage service can use an ES architecture. The storage service performs word segmentation processing on the result text information in memory, and establishes an inverted index of the word segmentation, which is associated with original file information, for example, can include the URL path of the mounting directory of the original file, the related attributes of the description sentence in the file, for example, the coordinate frame of the description sentence in the picture file; the relative time, context information, etc. of the description sentence in the audio. These information help the client to retrieve the corresponding file when the keyword is retrieved, and also better locate the position of the keyword in the file to improve the retrieval and presentation effect.

[0166] Since all operations on files or folders under the fourth folder are open, in an example, full life cycle detection can also be performed on the data under the fourth folder, and this function can be implemented by the application service. When the user modifies the data content under the fourth folder, the application service can delete all index information corresponding to the data in the storage service and automatically submit an analysis task again to rebuild the index data. When the user modifies the file name or file directory, since the content of the file is not modified, only the file name or file directory in the storage service needs to be modified for the file that has been analyzed. For the file being analyzed, only the task being analyzed needs to be stopped in time and the intermediate result data needs to be deleted. When the user deletes the file being analyzed or the analyzed file, the application service also needs to stop the task being analyzed in time and delete the intermediate or final analysis result data of the file.

[0167] The embodiment of the application further provides a data analysis device, which is applied to a client, and refers to Figure 7 , the device comprises:

[0168] The file directory display module 701 is configured to display each file directory of the mounted target network disk, wherein different file directories correspond to different intelligent analysis algorithms.

[0169] The file storage instruction acquisition module 702 is configured to acquire a file storage instruction input by a user based on each displayed file directory, the file storage instruction indicating storage of to-be-analyzed data into a specified file directory.

[0170] The to-be-analyzed data sending module 703 is configured to upload the to-be-analyzed data into the specified file directory of the target network disk on the server in response to the file storage instruction, so that the server analyzes the to-be-analyzed data by using the intelligent analysis algorithm corresponding to the specified file directory.

[0171] The analysis result obtaining module 704 is configured to download the analysis result of the data to be analyzed from the server.

[0172] In a possible implementation, the apparatus further includes a target network disk mounting module configured to: send a mounting request for a target network disk to a server; obtain attribute information of the target network disk sent by the server; and mount the target network disk locally based on the attribute information of the target network disk.

[0173] In a possible implementation, the target network disk mounting module is specifically configured to: generate mounting protocol data for a first port based on the attribute information of the target network disk; convert the mounting protocol data for the first port into mounting protocol data for a second port, where the second port is a port listened to by the server; and send the mounting protocol data for the second port to the server, so as to mount the target network disk locally.

[0174] In a possible implementation, the specified file directory includes a first folder, and the first folder is configured to store data to be analyzed; and the data to be analyzed sending module is specifically configured to: in response to the file storage instruction, upload the data to be analyzed into the first folder of the specified file directory of the target network disk of the server.

[0175] In a possible implementation, the specified file directory includes a second folder, and the second folder is configured to store an analysis result; and the analysis result obtaining module is specifically configured to: in a case where the data to be analyzed is successfully analyzed, download the analysis result of the data to be analyzed from the second folder of the specified file directory of the target network disk of the server.

[0176] In a possible implementation, the apparatus further includes a retrieval result obtaining module configured to: obtain a keyword to be retrieved for a target network disk; send a target retrieval instruction including the keyword to be retrieved to the server, so that the server retrieves a description sentence corresponding to the target network disk by using the keyword to be retrieved, to obtain a retrieval result of the keyword to be retrieved, where the description sentence corresponding to the target network disk is a description sentence extracted from target data uploaded by the client and corresponding to a fourth folder in the target network disk; and receive the retrieval result returned by the server according to the target retrieval instruction.

[0177] The embodiment of the application further provides a data analysis apparatus applied to a server, as shown in Figure 8 , the apparatus includes:

[0178] The to-be-analyzed data obtaining module 801 is configured to receive to-be-analyzed data uploaded by a client and directed to a specified file directory in a target network disk, and store the to-be-analyzed data in the specified file directory in the target network disk, wherein the target network disk includes file directories, and different file directories correspond to different intelligent analysis algorithms;

[0179] The analysis result generating module 802 is configured to analyze the to-be-analyzed data by using a target intelligent analysis algorithm corresponding to the specified file directory, to obtain an analysis result of the to-be-analyzed data.

[0180] The analysis result sending module 803 is configured to send the analysis result of the to-be-analyzed data to the client.

[0181] In a possible implementation, the specified file directory includes a first folder, and the first folder is used to store to-be-analyzed data; and the to-be-analyzed data obtaining module is specifically configured to store the to-be-analyzed data in the first folder of the specified file directory in the target network disk.

[0182] In a possible implementation, the specified file directory includes a second folder, and the second folder is used to store analysis results.

[0183] The apparatus further includes an analysis result storing module, configured to store the analysis result of the to-be-analyzed data in the second folder of the specified file directory, and to transfer the to-be-analyzed data from the first folder of the specified file directory to the second folder of the specified file directory.

[0184] In a possible implementation, the specified file directory includes a third folder, and the third folder is used to store to-be-analyzed data that fails in analysis; and the apparatus further includes a to-be-analyzed data transferring module, configured to, in a case where the to-be-analyzed data fails in analysis, transfer the to-be-analyzed data from the first folder of the specified file directory to the third folder of the specified file directory.

[0185] In a possible implementation, the apparatus further includes a keyword searching module configured to: receive target data uploaded by a client for a fourth folder in a target network disk, and store the target data into the fourth folder of a file directory designated by the target network disk; extract a description sentence from the target data to obtain a description sentence corresponding to the target network disk; receive a target searching instruction sent by the client, wherein the target searching instruction includes a network disk identifier of a network disk to be detected and a keyword to be searched; determine a network disk to be searched according to the network disk identifier of the network disk to be detected in the target searching instruction; search the description sentence corresponding to the network disk to be searched by using the keyword to be searched to obtain a searching result of the keyword to be searched; and send the searching result to the client.

[0186] The embodiment of the present application further provides an electronic device, including: a processor and a memory.

[0187] The memory is used for storing a computer program.

[0188] The processor is used for executing the computer program stored in the memory, so as to realize the data analysis method in the present application.

[0189] Optionally, referring to Figure 9 The electronic device provided by the embodiment of the present application further includes a communication interface 902 and a communication bus 904, wherein the processor 901, the communication interface 902 and the memory 903 complete mutual communication through the communication bus 904.

[0190] The communication bus mentioned in the electronic device can be a PCI (Peripheral Component Interconnect, peripheral component interconnect) bus or an EISA (Extended Industry Standard Architecture, extended industry standard architecture) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or only one type of bus.

[0191] The communication interface is used for communication between the electronic device and other devices.

[0192] The memory can include a RAM (Random Access Memory, random access memory) and can also include a NVM (Non-Volatile Memory, non-volatile memory), for example, at least one disk memory. Optionally, the memory can also be at least one storage device located away from the aforementioned processor.

[0193] The processor described above can be a general processor, including a CPU (Central Processing Unit), a NP (Network Processor), etc.; or can be a DSP (Digital Signal Processing), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

[0194] The embodiment of the present application further provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the data analysis method described in any of the embodiments of the present application.

[0195] In another embodiment of the present application, a computer program product containing instructions is provided, which, when executed on a computer, causes the computer to perform the data analysis method described in any of the above embodiments.

[0196] In the above embodiments, the implementation can be achieved entirely or partially by software, hardware, firmware, or any combination thereof. When implemented by software, the implementation can be achieved entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the entire or partial process or function described in the embodiments of the present application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer readable storage medium or transferred from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions can be transferred from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line) or wireless (such as infrared, wireless, microwave, etc.) mode. The computer readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. integrated with one or more available media. The available media can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk, SSD), etc.

[0197] It should be noted that, in the present document, the technical features in various alternatives can be combined as long as there is no conflict, and these alternatives are within the scope of the present application. The relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or device. Without more limitations, the element defined by the statement "comprises a" does not exclude the presence of other identical elements in the process, method, article or device that includes the element.

[0198] Each of the embodiments in the present specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the difference from other embodiments. In particular, for the embodiments of the device, electronic equipment and storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the part of the method embodiments.

[0199] The above only describes the preferred embodiments of the present application, and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A data analysis method, characterized by, The method applied to the client comprises: Displaying file directories of the mounted target network disk, wherein different file directories correspond to different intelligent analysis algorithms; Obtaining a file storage instruction input by a user based on the displayed file directories, the file storage instruction indicating that the to-be-analyzed data is to be stored in a specified file directory, the specified file directory being a file directory corresponding to an intelligent analysis algorithm to be used, the file storage instruction comprising a paste instruction for pasting the to-be-analyzed data into the specified file directory; In response to the file storage instruction, uploading the to-be-analyzed data into the specified file directory of the target network disk on the server, so that the server analyzes the to-be-analyzed data by using the intelligent analysis algorithm corresponding to the specified file directory; Downloading the analysis result of the to-be-analyzed data from the server.

2. The method of claim 1, wherein, The method further comprises: Sending a mounting request for a target network disk to a server; Obtaining attribute information of the target network disk sent by the server; Based on the attribute information of the target network disk, mounting the target network disk locally.

3. The method of claim 2, wherein, The mounting of the target network disk locally based on the attribute information of the target network disk comprises: Based on the attribute information of the target network disk, generating mounting protocol data for a first port; Converting the mounting protocol data for the first port into mounting protocol data for a second port, wherein the second port is a port listened to by the server; Sending the mounting protocol data for the second port to the server to complete the mounting of the target network disk locally.

4. The method of claim 1, wherein, The specified file directory comprises a first folder for storing to-be-analyzed data; The uploading of the to-be-analyzed data into the specified file directory of the target network disk on the server in response to the file storage instruction comprises: In response to the file storage instruction, uploading the to-be-analyzed data into the first folder of the specified file directory of the target network disk on the server.

5. The method of claim 4, wherein, The specified file directory comprises a second folder for storing analysis results; The downloading of the analysis result of the to-be-analyzed data from the server comprises: In the case that the to-be-analyzed data is successfully analyzed, downloading the analysis result of the to-be-analyzed data from the second folder of the specified file directory of the target network disk on the server.

6. The method of claim 1, wherein, The method further comprises: Obtaining a to-be-searched keyword for a target network disk, sending a target search instruction containing the to-be-searched keyword to the server, so that the server searches a description sentence corresponding to the target network disk by using the to-be-searched keyword, and obtains a search result of the to-be-searched keyword, wherein the description sentence corresponding to the target network disk is a description sentence extracted from target data for a fourth folder in the target network disk uploaded from the client, and the fourth folder is used to store target data to be searched; Receiving the search result returned by the server according to the target search instruction.

7. A data analysis method characterized by, The method applied to the server comprises: The receiving client uploads the to-be-analyzed data for a specified file directory in a target network disk after obtaining a file storage instruction input by a user, and stores the to-be-analyzed data into the specified file directory in the target network disk, wherein the target network disk comprises file directories, different file directories correspond to different intelligent analysis algorithms, the specified file directory is a file directory corresponding to an intelligent analysis algorithm to be used, and the file storage instruction comprises a paste instruction of pasting the to-be-analyzed data into the specified file directory. The to-be-analyzed data is analyzed by using a target intelligent analysis algorithm corresponding to the specified file directory, and an analysis result of the to-be-analyzed data is obtained. The analysis result of the to-be-analyzed data is sent to the client.

8. The method of claim 7, wherein, The specified file directory comprises a first folder, and the first folder is used to store to-be-analyzed data. The to-be-analyzed data is stored into the first folder of the specified file directory in the target network disk. The specified file directory comprises a second folder, and the second folder is used to store analysis results.

9. The method of claim 8, wherein, The method further comprises: The analysis result of the to-be-analyzed data is stored into the second folder of the specified file directory. The to-be-analyzed data is transferred from the first folder of the specified file directory to the second folder of the specified file directory. The specified file directory comprises a third folder, and the third folder is used to store to-be-analyzed data that fails in analysis.

10. The method of claim 8, wherein, The method further comprises: In a case where the to-be-analyzed data fails in analysis, the to-be-analyzed data is transferred from the first folder of the specified file directory to the third folder of the specified file directory. The method further comprises:

11. The method of claim 7, wherein, The receiving client uploads target data for a fourth folder in a target network disk, and stores the target data into the fourth folder of the specified file directory in the target network disk, wherein the fourth folder is used to store target data to be detected. Descriptive phrases are extracted from the target data, and descriptive phrases corresponding to the target network disk are obtained. The receiving client sends a target search instruction, wherein the target search instruction comprises a network disk identifier of a to-be-detected network disk and a to-be-searched keyword. The to-be-detected network disk is determined according to the network disk identifier of the to-be-detected network disk in the target search instruction. The to-be-searched keyword is used to search the descriptive phrases corresponding to the to-be-detected network disk, and a search result of the to-be-searched keyword is obtained. The search result is sent to the client. The apparatus is applied to a client and comprises:

12. A data analysis device, characterized by A file directory display module is configured to display each file directory of a mounted target network disk, wherein different file directories correspond to different intelligent analysis algorithms. ​ The file storage instruction obtaining module is configured to obtain a file storage instruction input by a user based on each file directory displayed, the file storage instruction indicating that the to-be-analyzed data is to be stored in a specified file directory, the specified file directory being a file directory corresponding to a smart analysis algorithm to be used, and the file storage instruction including a paste instruction for pasting the to-be-analyzed data into the specified file directory. The to-be-analyzed data sending module is configured to upload the to-be-analyzed data into the specified file directory of the target network disk on the server in response to the file storage instruction, so that the server analyzes the to-be-analyzed data by using the smart analysis algorithm corresponding to the specified file directory. The analysis result obtaining module is configured to download an analysis result of the to-be-analyzed data from the server.

13. A data analysis device, characterized by The apparatus applied to the server includes: The to-be-analyzed data obtaining module is configured to receive to-be-analyzed data uploaded by a client to a specified file directory in a target network disk after the client obtains a file storage instruction input by a user, and store the to-be-analyzed data into the specified file directory in the target network disk, wherein the target network disk includes file directories, different file directories correspond to different smart analysis algorithms, the specified file directory is a file directory corresponding to a smart analysis algorithm to be used, and the file storage instruction includes a paste instruction for pasting the to-be-analyzed data into the specified file directory. The analysis result generating module is configured to analyze the to-be-analyzed data by using a target smart analysis algorithm corresponding to the specified file directory, to obtain an analysis result of the to-be-analyzed data. The analysis result sending module is configured to send the analysis result of the to-be-analyzed data to the client.

14. An electronic device, comprising: The apparatus includes a processor and a memory. The memory is configured to store a computer program. The processor is configured to execute the program stored in the memory, to implement the data analysis method in any one of claims 1-11.

15. A computer-readable storage medium, characterized in that, The computer program stored in the computer readable storage medium is executed by the processor to implement the data analysis method in any one of claims 1-11.

16. A computer program product, characterised in that, When the computer program is executed on a computer, the computer is caused to execute the data analysis method in any one of claims 1-11.

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