Automatic data backup processing method and device based on cloud disk APP

Abstract

The invention relates to the technical field of automatic data backup processing. The invention provides an automatic data backup processing method and device based on a cloud disk APP, and the method comprises the steps: collecting journey information and user positioning information recorded by a calendar or a document, and prompting to fill in time information related to a key event when the APP is logged in for the first time; when the calendar database is read each time, score checking and comparison are carried out, whether newly-added travel information exists or not is determined, the newly-added travel information is uploaded to a cloud end, and information related to travel plans, commemorative days and key time is analyzed through a natural language processing model; issuing the analyzed information related to the travel plan, the commemorative day and the key time to a client, and storing the information in a user database; and when monitoring that the travel plan, the commemorative day and the key time in the user database are triggered by changes, automatically executing the corresponding backup task at the appointed time. According to the method, the travel information and holidays input by the user can be intelligently analyzed, the optimal backup time period is automatically set, and it is ensured that the photos are backed up in time under the condition that normal use of equipment by the user is not disturbed.

Description

Technical Field

[0001] The present invention belongs to the technical field of automatic data backup processing, and provides a method and device for automatic data backup processing based on a cloud disk APP. Background Art

[0002] Cloud disk APP is an application based on cloud computing technology. Its main function is to allow users to store personal or corporate data (such as photos, documents, videos, etc.) on cloud servers and access and manage these data anytime and anywhere through the Internet. Users can upload, download, share, synchronize and back up files through the cloud disk APP to achieve secure storage and convenient access to data. Cloud disk APP usually supports data synchronization and backup functions. Users can synchronize data on mobile phones, computers or other devices to the cloud to ensure real-time backup and security of data, while also facilitating data sharing and access between different devices. In most existing cloud disk APPs, users actively open the APP to trigger the upload of photos and videos in the album that they want to back up in the cloud. If the user does not operate the cloud disk APP for a long time, it is easy to miss backing up important and precious photos and videos to the cloud, increasing the possibility of losing good memories in the future.

[0003] The backup timing of existing cloud disk apps is usually after the user logs in and opens the app, manually or automatically scans the newly added photos and videos in the device, and actively triggers uploading to the cloud for backup and storage, or scans and backs up regularly every day. However, this scheduled backup scan consumes a lot of power, and users are reluctant to back up all photos and videos to the cloud. Especially in large-scale video surveillance systems, the loss of image quality may have serious consequences.

[0004] With the popularity of mobile devices and the improvement of photography technology, people are increasingly inclined to use smartphones or digital cameras to record important moments in life and travel experiences. However, since users may be busy with work or travel activities, they may forget or miss the manual triggering of backing up these precious photos in time, resulting in the risk of data loss.

[0005] Therefore, a convenient and intelligent method and device for automatic data backup processing based on a cloud disk APP is needed to solve the above problems. Summary of the invention

[0006] The present invention provides a method and device for automatic data backup processing based on a cloud disk APP to solve the technical problems in the prior art such as cumbersome photo and video backup operations and failure to perform backup at the optimal backup time. The technical problems to be solved by the present invention are achieved through the following technical solutions.

[0007] The first aspect of the present invention proposes a method for automatically backing up data based on a cloud disk APP, the method comprising: collecting itinerary information and user location information recorded in a calendar or document, and prompting to fill in time information related to key events when logging into the APP for the first time; performing a check and comparison each time the calendar database is read to determine whether there is any new itinerary information, uploading the new itinerary information to the cloud, and analyzing information related to travel plans, anniversaries, and key times through a natural language processing model; sending the analyzed information related to travel plans, anniversaries, and key times to a client and saving it in a user database; and automatically executing corresponding backup tasks at a specified time when a change trigger is detected in the travel plans, anniversaries, and key times in the user database.

[0008] The second aspect of the present invention proposes an automatic data backup processing device based on a cloud disk APP, which is the automatic data backup processing method based on a cloud disk APP described in the first aspect of the present invention, and the automatic data backup processing device includes: a collection module, which collects travel information and user location information recorded in calendars or documents, and prompts to fill in time information related to key events when logging into the APP for the first time; a determination module, which performs a check and comparison each time the calendar database is read to determine whether there is any new travel information, uploads the new travel information to the cloud, and analyzes the information related to travel plans, anniversaries, and key times through a natural language processing model; an analysis module, which is used to send the analyzed information related to travel plans, anniversaries, and key times to the client and save it to the user database; a backup module, when it monitors that there are changes in travel plans, anniversaries, and key times in the user database, automatically executes the corresponding backup task at the specified time.

[0009] The third aspect of the present invention provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the automatic data backup processing method described in the first aspect of the present invention.

[0010] A fourth aspect of the present invention provides a computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the automatic data backup processing method described in the first aspect of the present invention.

[0011] The embodiments of the present invention include the following advantages:

[0012] Compared with the prior art, the present invention determines whether there is any new itinerary information by checking and comparing each time the calendar database is read, uploads the new itinerary information to the cloud, and analyzes information related to travel plans, anniversaries, and key times through a natural language processing model, sends the analyzed information related to travel plans, anniversaries, and key times to the client, and saves it to the user database, monitors whether there are change triggers in the travel plans, anniversaries, and key times in the user database, and automatically executes the corresponding backup task at the specified time when it monitors that there are change triggers in the travel plans, anniversaries, and key times in the user database, and can intelligently analyze the itinerary information and holiday dates input by the user, and automatically set the optimal backup time period to ensure that photos are backed up in time without interfering with the user's normal use of the device, without the need for manual intervention by the user, thereby greatly simplifying the operation process.

[0013] In addition, the backed-up photos are automatically categorized and organized based on the user's holiday and itinerary information, making it easier for users to find and recall them later. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a flow chart of the steps of the automatic data backup processing method based on the cloud disk APP of the present invention;

[0015] Figure 2 It is a schematic diagram of an application example of the data automatic backup processing method based on the cloud disk APP of the present invention;

[0016] Figure 3 It is a structural block diagram of the data automatic backup processing device based on the cloud disk APP of the present invention;

[0017] Figure 4 is a schematic structural diagram of an electronic device embodiment according to the present invention;

[0018] Figure 5 It is a schematic diagram of the structure of a computer-readable medium embodiment according to the present invention. DETAILED DESCRIPTION

[0019] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0020] In view of the above problems, the present invention proposes a data automatic backup processing method based on cloud disk APP. The method performs a check and comparison each time the calendar database is read to determine whether there is any new itinerary information, uploads the new itinerary information to the cloud, and analyzes the information related to travel plans, anniversaries, and key times through a natural language processing model, sends the analyzed information related to travel plans, anniversaries, and key times to the client, and saves it to the user database, monitors whether there are changes in the travel plans, anniversaries, and key times in the user database, and automatically executes the corresponding backup task at the specified time when the travel plans, anniversaries, and key times in the user database are monitored.

[0021] Example 1

[0022] Refer to the following Figure 1 , Figure 2 , the contents of the present invention will be described in detail.

[0023] Figure 1 It is a step flow chart of the automatic data backup processing method based on the cloud disk APP of the present invention.

[0024] like Figure 1 As shown, in step S101, the travel information and user location information recorded in the calendar or document are collected, and when logging into the APP for the first time, a prompt is given to fill in the time information related to key events.

[0025] Specifically, the APP is a cloud APP installed on a mobile phone or mobile terminal. When the cloud APP requests the current user to access the itinerary information of the mobile phone calendar, or requests the current user to access the itinerary information recorded in the document, and requests the current user to obtain the user's location information, the itinerary information of the current user is obtained. After the current user grants the calendar reading permission, the user's calendar data is accessed through a specified interface (such as CalendarContractAPI) to obtain some schedules recorded in the user's calendar data.

[0026] When the current user logs in for the first time and opens the APP, the user is prompted to fill in the time information related to key events. The APP is, for example, a cloud disk APP. Specifically, for example, after opening and logging in to the cloud disk, the current user is prompted through the guidance interface to enter dates that are of great significance to the user and require backing up resources to the cloud, such as personal birthdays, family members’ birthdays, anniversaries, etc., and save them in the local database. The current user is also requested to enter memo information related to the current user and family members (such as birthday information, anniversaries, etc.), and event information related to holidays. Alternatively, after the first installation, in order to obtain some important dates for users using the cloud disk APP, it is convenient to complete the automatic backup function according to important dates later, which is also regarded as a function guidance point in the new user function guidance item.

[0027] After the first login, each time the user opens the cloud disk APP, the user will be actively guided to enter or modify the pending new itinerary plans or anniversaries through a guidance prompt animation on the cloud disk homepage, as a supplement to the itinerary plan data read from the mobile phone calendar database and saved in the local database of the user's cloud disk APP.

[0028] For example, a cloud disk APP or client allows users to actively enter backup plans. The entry types can be divided into travel plans, anniversaries, key event dates, etc.

[0029] It should be noted that providing users with an opportunity to actively enter a backup plan, that is, an opportunity to actively enter or correct, can more accurately improve the success rate and accuracy of automatic backup albums, and is more conducive to the setting of automatic backup opportunities. The above is only described as an optional example and cannot be understood as a limitation of the present invention.

[0030] Next, in step S102, each time the calendar database is read, a comparison is performed to determine whether there is any new itinerary information, the new itinerary information is uploaded to the cloud, and the information related to travel plans, anniversaries, and key times is analyzed through a natural language processing model.

[0031] Specifically, the cloud disk APP reads the user's mobile phone calendar data. For example, the cloud disk APP declares the permission to read the calendar and obtain the user's precise location in the program AndroidManifest.<uses-permission android:name="android.permission.READ_CALENDAR" / > .

[0032] For example, when a user opens and logs in to the cloud disk app for the first time, ActivityCompat.requestPermissions is used to request calendar read permissions from the user. After obtaining the user's permission, each time the cloud disk app is opened, the calendar database of the mobile phone (such as the Android system) and the columns related to schedules are read through, for example, the CalendarContract API and ContentResolver:

[0033] CalendarContract.Events.TITLE, CalendarContract.Events.DTSTART, CalendarContr act.Events.DTEND, CalendarContract.Events.EVENT_LOCATION and differentiate the read data from the itinerary records saved locally in the cloud, encrypt the newly added itinerary and upload it to the cloud for subsequent natural language processing analysis.

[0034] In a specific embodiment, the input data specifically includes a collection of all original plans (e.g., represented by originalPlans). Each of these plans has a unique identifier and related fields, such as "type" (travel, anniversary, travel, etc.), and the related fields also include "date", "location", "participants", and "details".

[0035] The updated plan set (for example, represented by updatedPlans) contains only the newly added or modified plan sets input by the user.

[0036] Specifically, a plan dictionary mapping table (or plan hash table) is constructed, with the plan identifier (eg, "id") as the key, so that each plan can be quickly searched to complete the comparison between the original plan and the updated plan.

[0037] Initialize the comparison structure, specifically initialize an empty list to store the newly added or modified plan information and explanations. Process each updated plan, for each plan in the updated plan set, obtain the plan identifier, and extract the plan identifier from it.

[0038] Through the new plan detection, check whether the extracted plan identifier exists in the plan dictionary mapping table to determine whether the plan is updated. When the extracted plan identifier exists in the plan dictionary mapping, it is determined that the plan has not been updated. When the extracted plan identifier does not exist in the plan dictionary mapping, it is determined that the plan has been updated, and the extracted plan identifier is marked as new. Specifically, by calling the function "`determine_contextual_action(updated_plan,is_new=True)", the subsequent operations of the corresponding plan type are determined, such as adjusting the backup time, sending reminders, etc.

[0039] Furthermore, it also includes plan modification detection. When the extracted plan identifier exists in the plan dictionary mapping, the original plan is compared with each field of the updated plan, for example, using a deep comparison method to compare important fields (date, location, details, etc.). If there are different fields, the differences are recorded and marked as "modified". Specifically call "determine_contextual_action(updated_plan,is_new=False)" to obtain subsequent operation suggestions for the plan. If it is determined that the original plan has differences (ie, it has been modified), the plan dictionary mapping table (or plan hash table) is updated with this information, such as adding an information list or modifying an information list.

[0040] For example, set up a function for deep comparison of all fields of two plan objects for modification plan detection.

[0041] Optionally, if the field is a complex type, such as a nested list, perform a recursive comparison.

[0042] Use the plan type (e.g., travel, anniversary) to adjust subsequent actions. For example, for travel type: you may need to update backup strategies, send notifications, and supplement resources. For anniversary type: focus on reminders around important dates and special backup schedules. For travel type, consider device synchronization and data protection measures before and after travel.

[0043] The newly added plan detection result and the modified plan detection result are used as the difference result. After the whole analysis process is finished, the plan dictionary mapping table (or plan hash table) is updated, such as adding an information list or modifying an information list to store detailed information of all newly added or modified plans and corresponding action suggestions.

[0044] Specifically, the above-mentioned plan dictionary mapping table is output for users to view or used to update other functional modules of the system.

[0045] It should be noted that in other embodiments, the logic is extracted and placed in a service module or event-driven framework so that it can respond to new user input and updates in real time. In addition, the notification and prompt system is integrated into the corresponding module to quickly respond to the user's plan change needs. In addition, batch processing or concurrent technology is used to increase the processing speed for large-scale data. The above is only described as an optional example and cannot be understood as a limitation of the present invention.

[0046] The cloud-based app uses a natural language processing model to analyze information related to travel plans, anniversaries, and key times.

[0047] Specifically, the CRNN (Convolutional Recurrent Neural Network) algorithm is used to build a natural language processing model to identify the text content recorded in logs or memos.

[0048] It should be noted that the model constructed by the CRNN (Convolutional Recurrent Neural Network) algorithm is a hybrid neural network for sequence data recognition, which is mainly used in text recognition tasks. The network structure of the CRNN model consists of three main parts: convolutional layers, recurrent layers, and transcription layers. These three main parts are used to identify information related to travel plans, anniversaries, and key times in the text content recorded in logs or memos, such as someone’s birthday, traveling from August 1, 2023 to August 4, 2023, etc.

[0049] A training data set is established using text content labeled with birthday tags, anniversary tags, and travel tags to train the constructed natural language processing model to obtain a trained natural language processing model.

[0050] For data synchronization and coordination, the mobile phone and the cloud need to maintain data consistency, especially when there are conflicts between multiple devices (such as the same user updating calendar data on multiple devices). Real-time data synchronization will be limited by unstable network conditions. A reliable synchronization protocol is implemented through a two-way synchronization mechanism, allowing data to be updated bidirectionally between the mobile phone and the cloud, and using timestamps or version numbers to detect conflicts. In this example, the incremental update refers to the transmission of only data that has changed since the last synchronization, which can effectively reduce unnecessary bandwidth consumption. The updates are temporarily stored and queued on the mobile phone to ensure safe batch transmission even when the network is unstable.

[0051] Preferably, a predetermined protocol (such as HTTPS / TLS protocol) is used for end-to-end encryption to protect the confidentiality of data during transmission, and data compression technology such as gzip is used to reduce the size of data packets to increase transmission speed. WebSockets or HTTP / 2 are also used in conjunction to maintain persistent connections and reduce the overhead of connection establishment, enabling data to be exchanged more quickly, thereby optimizing transmission efficiency while ensuring data confidentiality and integrity transmission.

[0052] It should be noted that the above is only described as an optional example and should not be understood as a limitation to the present invention.

[0053] Next, in step S103, the analyzed information related to the travel plan, anniversary, and key time is sent to the client and saved in the user database.

[0054] In one specific implementation, a specified time point (e.g., a certain time each day) is set to perform natural language processing analysis on the user's mobile phone calendar data, and calendar data related to travel plans, anniversaries, key times, and holidays in all itineraries are extracted and sent back to the client for record preservation, specifically saved in a user database.

[0055] In another specific implementation, natural language processing analysis is performed on the user's mobile phone calendar data within a specified time period (for example, one month, two months, three months, six months, etc. calculated forward from the current moment), and calendar data related to travel plans, anniversaries, key times, holidays in all itineraries are extracted and sent back to the client for record preservation, specifically saved in a user database.

[0056] It should be noted that the above is only described as an optional example and should not be understood as a limitation to the present invention.

[0057] Next, in step S104, when a change trigger is detected in the travel plan, anniversary, or key time in the user database, the corresponding backup task is automatically executed at the specified time.

[0058] Specifically, the cloud APP monitors the user's database in real time to see if there are any changes in travel plans, anniversaries, and key times.

[0059] When changes are detected in the user's database such as travel plans, anniversaries, or key times, specifically when new flight ticket information, train ticket information, or other travel information, new anniversary information, or designated time markers (such as the Mid-Autumn Festival to mark the time to go home) are detected in the user's database, it is a change trigger, and the corresponding backup task will be automatically executed.

[0060] Determine different backup tasks based on different trigger conditions.

[0061] Determine the trigger conditions and backup tasks (i.e., select the backup content).

[0062] For travel plans, back up before departure, specifically 1 to 2 days before the planned trip, and specifically back up photos and videos added in the recent period (such as one month from the current time, that is, the past month) to ensure that new content has been safely backed up. Furthermore, selectively back up during the trip. If there is Wi-Fi during the trip and the device has sufficient power, back up new photos taken every day, especially those marked as favorites. On the day of the trip or after the trip, back up the entire travel folder to ensure that all photos taken during the trip have been backed up.

[0063] For anniversaries, on or before the anniversary: ​​back up photos related to the anniversary event (such as photos taken within the previous week). Tag photos with importance, and tag photos with geographic locations, tags, or specific themes.

[0064] For flights or train trips, back up the content added in the first few hours before departure to ensure data security even if the device is lost during the trip. After arriving at the destination, make adjustments based on whether the itinerary photos have been backed up during the trip.

[0065] Determine the backup content, based on the metadata such as the shooting date and time of the photo, use the backup algorithm to filter out the content within a specific time range (e.g., a specified time calculated from the current time, such as one day, two days, three days, one week, ten days, two weeks, one month, two months, half a year, etc.). Select the content of the relevant geographical location according to different trigger conditions. Geographic location tags and scores (such as "marked" or important marks set by the user).

[0066] For the priority backup conditions of content priority, priority is given to backing up photos marked as "favorite". Photos containing face recognition and activity tags (such as parties, natural scenery). For videos, selection is made based on the length and quality of the video, such as selecting higher quality files (such as files with a resolution greater than a predetermined resolution) or larger files (such as files with a size greater than a set size).

[0067] Specifically, metadata of photos and videos are collected, including shooting date, file size, geographic location information, etc. Based on the trigger conditions, the content is prioritized by importance and shooting date.

[0068] According to the determined priority, set the high priority item as the current backup task. Check the device status (network, power) to decide whether to execute immediately or postpone. After executing the backup, record the backup content, time and conditions for subsequent analysis. Regularly summarize and analyze the backup data and adjust the future backup content and strategy.

[0069] For example, every time there is a change in the database related to the user's travel plans and anniversaries, a scheduled task is set for each trip through, for example, the Android system AlarmManager. If it is a specific date, the scheduled task is set to 23:59 on that day. If it is a continuous period of multiple days, a scheduled task is set at 23:59 every day. When a scheduled task is triggered, BroadcastReceiver is used to receive notification events, and the onReceive method will be called. In the onReceive method, the user's precise geographic location is combined as a basis for determining whether the user has started a certain trip, and the geographic location is used to mark the resources to be backed up, so that users can easily organize travel-related photos and videos.

[0070] In a specific implementation, after obtaining the schedule in the user's calendar and the relevant important dates and itineraries that are actively entered, the specified year, month and day are set to wake up the application through, for example, the AlarmManager of the Android system, and the user's location is obtained in combination with the system positioning service to analyze the user's itinerary, and a decision is made whether to start automatically backing up certain photos and videos of the user and complete uploading them to the cloud. Specifically, when starting a background backup task, the backup condition is set to upload the album resources such as photos and videos that the user has added on that day, and encrypted uploads are started through HTTP requests to complete the intelligent automatic backup task.

[0071] When the backup task is completed, check whether it is the last day of the important travel date. If so, clear the travel plan recorded in the database.

[0072] In another specific implementation, different backup tasks are determined according to different trigger conditions, wherein the trigger conditions include whether data extraction is completed, whether access rights are confirmed, and whether events within a specific time range (e.g., a specified time calculated from the current time, the specified time includes one day, two days, three days, one week, ten days, two weeks, one month, two months, half a year, etc.) are completed. For details, see Figure 2 The event may be, for example, an event involving a certain theme (such as a birthday, anniversary, etc.), an event at a certain location, or the like.

[0073] For example, when ensuring that the application has sufficient permissions to access the user's calendar data, the calendar data for one month forward from the current time is extracted from the mobile phone, specifically by requesting the "READ_CALENDAR" permission through a permission management system such as the Android system.

[0074] Specifically, the calendar database is accessed using Android's content provider, and interaction is performed through, for example, the "CalendarContract" API.

[0075] By querying the calendar event table (for example, using "Events"), filter the events within a specific time range. Specifically, fields such as title, description, date, time, location, etc. are obtained. The specific time range is, for example, a specified time calculated from the current time forward, and the specified time is, for example, one day, two days, three days, one week, ten days, two weeks, one month, two months, half a year, etc.

[0076] For data filtering and preprocessing, filter out unnecessary information and only keep events related to specific keywords (such as travel, birthday, annual meeting, etc.). Minimize the amount of unnecessary data on the Android system side. Structure the data into a format that is easy to transmit and parse, such as JSON.

[0077] The secure transmission of data includes data packaging and encrypted transmission. Specifically, the filtered JSON data is packaged to ensure that all necessary fields are included and the unified format is convenient for subsequent processing.

[0078] Next, the TLS protocol is used to ensure the security of data during network transmission. All data to be transmitted is encrypted to protect user privacy.

[0079] Furthermore, identity authentication is performed and the user's identity is authenticated through OAuth or JWT tokens to ensure the legitimacy of the data request.

[0080] Next, enter the cloud processing stage, where the transmitted data is received on the cloud server. Ensure that the data is processed in the expected format, unpack it and input it into the interface of the above natural language processing model, and analyze and process the received data through the natural language processing model.

[0081] Optionally, the calendar event description is fed into the natural language processing pipeline. Using a pre-trained language model (such as GPT), analysis is performed to identify key activities and important days. Entity recognition (NER) and intent analysis modules are further used to identify event categories, such as travel, birthdays, meetings, etc.

[0082] Based on the above analysis results, event summaries, suggestions (such as preparation, gift purchase reminders, etc.) or classification annotations are automatically generated.

[0083] If more specific information is needed, form a preset set of questions to prepare for the next interaction with the user.

[0084] Send the above analysis results back to the client, either through push notification or directly displayed on the application interface. Ensure that the feedback data such as the above analysis results also follows the secure transmission protocol.

[0085] Optionally, the cloud APP can provide an interactive interface that allows users to view analysis results, edit supplementary information, or accept recommended actions.

[0086] It should be noted that in other embodiments, an option may be provided to mark certain arrangements or analyses as "special attention" to facilitate more detailed processing or reminders next time. The marked events or processed analysis results determined by the user can be stored in the local database of the mobile phone (such as SQLite) for offline use or quick access next time. The above is only described as an optional example and cannot be understood as a limitation of the present invention.

[0087] In an optional implementation, with the user's consent, some anonymous usage data is collected to establish an incremental training data set to help train and improve the natural language processing model, which can further improve the analysis accuracy.

[0088] Preferably, a feedback mechanism is established to allow users to report incorrect analysis results or wrong suggestions so that these feedbacks can be incorporated into model training, thereby gradually improving the accuracy of the algorithm and user satisfaction.

[0089] It should be noted that in other embodiments, the model is also regularly maintained to ensure that it contains the latest specific domain information and recognition capabilities. At the same time, user applications need to be regularly updated to introduce new functions and security updates. The above is only described as an optional example and cannot be understood as a limitation of the present invention.

[0090] In a preferred embodiment, the method further includes a step of determining an optimal backup time.

[0091] Determining the best time to back up your phone's photo albums requires considering a variety of factors, including the user's travel dates, active usage cycles, and the device's connectivity (such as Wi-Fi availability).

[0092] The following is a specific implementation method for designing the backup trigger time.

[0093] When the user is not very active, choose a suitable time window to back up the album to ensure that the data is safely backed up without interfering with the user's daily use.

[0094] For example, enter the following parameters to perform corresponding backup: trip start date (expressed by trip_start_date), trip end date (expressed by anniversary_dates), anniversaries (such as birthdays and anniversaries), the user's active time period when using the phone (specifically expressed as start time and end time, for example, expressed by user_usage_pattern), the user's backup preferences (such as only in Wi-Fi network, when the battery is greater than 50%, for example, expressed by preferred_backup_conditions), the current device's network status (Wi-Fi / data network, for example, expressed by device_status), and the battery status.

[0095] It further includes determining the time period when backup is not suitable, specifically not performing backup during travel (i.e. avoiding backup during trip_start_date to trip_end_date), and not performing backup during the user's high-frequency usage period (specifically determining the user's usual active time period through user_usage_pattern, such as 8AM to 10PM).

[0096] Determining the optimal backup time includes calculating an ideal backup window.

[0097] In a specific implementation, a user time prediction model is established using a deep algorithm, and user data (such as mobile phone identification, user account identification, etc.) labeled with active time periods, inactive time periods, unused time periods, and low-frequency use time periods are used to establish a training data set, and the user time prediction model is trained to obtain a trained user time prediction model. The mobile phone identification of the current user is input into the trained user time prediction model to obtain the active time period, inactive time period, unused time period, low-frequency use time period corresponding to the current user and the score of each time period, thereby using the obtained inactive time period, unused time period, and low-frequency use time period as an ideal backup window.

[0098] Optionally, a nighttime backup priority method is adopted, that is, nighttime is regarded as an inactive period for users, such as 12AM to 6AM at night, as an inactive period.

[0099] Backup after the trip: You can trigger a backup at night on trip_end_date+1 day, assuming that there are many photos during the trip.

[0100] A suitable time before or after the anniversary: ​​For all anniversary_dates, backup is done overnight on the day before, or a suitable time after the anniversary.

[0101] Check device conditions: Verify preferred_backup_conditions to ensure the device is in the required conditions (such as connected to Wi-Fi and sufficient battery).

[0102] Dynamic adjustment and notification: If the current time meets the backup conditions but is not within the scheduled window, the backup will be performed on the nearest night. User notifications are provided to allow users to decide to manually trigger the backup when necessary.

[0103] Compared with the prior art, the present invention determines whether there is any new itinerary information by checking and comparing each time the calendar database is read, uploads the new itinerary information to the cloud, and analyzes information related to travel plans, anniversaries, and key times through a natural language processing model, sends the analyzed information related to travel plans, anniversaries, and key times to the client, and saves it to the user database, monitors whether there are change triggers in the travel plans, anniversaries, and key times in the user database, and automatically executes the corresponding backup task at the specified time when it monitors that there are change triggers in the travel plans, anniversaries, and key times in the user database, and can intelligently analyze the itinerary information and holiday dates input by the user, and automatically set the optimal backup time period to ensure that photos are backed up in time without interfering with the user's normal use of the device, without the need for manual intervention by the user, thereby greatly simplifying the operation process.

[0104] In addition, the backed-up photos are automatically categorized and organized based on the user's holiday and itinerary information, making it easier for users to find and recall them later.

[0105] Example 2

[0106] The following are embodiments of the device of the present invention, which can be used to implement the method embodiments of the present invention. For details not disclosed in the device embodiments of the present invention, please refer to the method embodiments of the present invention.

[0107] Figure 3 This is a schematic diagram of an example of a data automatic backup processing device based on a cloud disk APP according to the present invention. Figure 3 , a data automatic backup processing device based on a cloud disk APP is described. The data automatic backup processing device is used to execute the data automatic backup processing method based on a cloud disk APP described in the first aspect of the present invention.

[0108] like Figure 3 As shown, the data automatic backup processing device includes a collection module 310, a determination module

[0109] In a specific implementation, the collection module 310 collects travel information and user location information recorded in the calendar or document, and prompts to fill in time information related to key events when logging into the APP for the first time. The determination module 320 performs a check and comparison each time it reads the calendar database to determine whether there is any new travel information, uploads the new travel information to the cloud, and analyzes the information related to travel plans, anniversaries, and key times through a natural language processing model. The analysis module 330 is used to send the analyzed information related to travel plans, anniversaries, and key times to the client and save it to the user database. When the backup module 340 monitors changes in travel plans, anniversaries, and key times in the user database, it automatically executes the corresponding backup task at the specified time.

[0110] According to an optional implementation manner, when a change trigger is detected in the travel plan, anniversary, or key time in the user database, the corresponding backup task is automatically executed at the specified time.

[0111] When the user database is monitored for new flight ticket information, train ticket information or other travel information, new anniversary information, and information changes with specified time stamps, that is, there is a change trigger, the corresponding backup task will be automatically determined to be executed.

[0112] According to an optional implementation, in the event of conflicts between multiple devices, a two-way synchronization mechanism is used to allow data to be updated bidirectionally between the mobile phone and the cloud.

[0113] According to an optional implementation manner, the optimal backup time is determined according to the data change time, specifically including calculating an ideal backup window and determining the ideal backup window using a self-built user time prediction model.

[0114] Specifically, the content is prioritized according to the trigger conditions, importance and shooting date, and the high priority item is set as the current backup task based on the determined priority.

[0115] According to an optional implementation method, a designated time point is set, natural language processing analysis is performed on the user's mobile phone calendar data, and calendar data related to travel plans, anniversaries, key times, and holidays in all itineraries are extracted and returned to the client.

[0116] Perform natural language processing analysis on the user's mobile phone calendar data within a specified time period, extract calendar data related to travel plans, anniversaries, key times, and holidays in all itineraries, and return it to the client.

[0117] According to an optional implementation, a CRNN algorithm is used to construct a natural language processing model for identifying text content recorded in a log or memo;

[0118] A training data set is established using text content labeled with birthday tags, anniversary tags, and travel tags to train the constructed natural language processing model to obtain a trained natural language processing model.

[0119] According to an optional implementation, different backup tasks are determined according to different trigger conditions, wherein the trigger conditions include whether data extraction is completed, whether access rights are confirmed, and whether screening of events within a specific time range is completed, wherein the specific time range is specifically a specified time calculated from the current time forward, and the specified time includes one day, two days, three days, one week, ten days, two weeks, one month, two months, and half a year.

[0120] It should be noted that due to Figure 3 The data automatic backup processing method and the data automatic backup processing device based on the cloud disk APP are implemented Figure 1 The data automatic backup processing method in the examples is roughly the same, so the description of the same parts is omitted.

[0121] Compared with the prior art, the present invention determines whether there is any new itinerary information by checking and comparing each time the calendar database is read, uploads the new itinerary information to the cloud, and analyzes information related to travel plans, anniversaries, and key times through a natural language processing model, sends the analyzed information related to travel plans, anniversaries, and key times to the client, and saves it to the user database, monitors whether there are change triggers in the travel plans, anniversaries, and key times in the user database, and automatically executes the corresponding backup task at the specified time when it monitors that there are change triggers in the travel plans, anniversaries, and key times in the user database, and can intelligently analyze the itinerary information and holiday dates input by the user, and automatically set the optimal backup time period to ensure that photos are backed up in time without interfering with the user's normal use of the device, without the need for manual intervention by the user, thereby greatly simplifying the operation process.

[0122] In addition, the backed-up photos are automatically categorized and organized based on the user's holiday and itinerary information, making it easier for users to find and recall them later.

[0123] Figure 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

[0124] like Figure 4 As shown, the electronic device is presented in the form of a general computing device. The processor may be one or more and work in coordination. The present invention does not exclude distributed processing, that is, the processor may be dispersed in different physical devices. The electronic device of the present invention is not limited to a single entity, but may also be the sum of multiple physical devices.

[0125] The memory stores a computer executable program, which is usually a machine-readable code. The computer-readable program can be executed by the processor to enable the electronic device to perform the method of the present invention, or at least part of the steps in the method.

[0126] The memory includes a volatile memory, such as a random access memory unit (RAM) and / or a cache memory unit, and may also be a non-volatile memory, such as a read-only memory unit (ROM).

[0127] Optionally, in this embodiment, the electronic device further includes an I / O interface, which is used for the electronic device to exchange data with an external device. The I / O interface can represent one or more of several types of bus structures, including a storage unit bus or a storage unit controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of a variety of bus structures.

[0128] It should be understood that Figure 4 The electronic device shown is only an example of the present invention, and the electronic device of the present invention may also include elements or components not shown in the above examples. For example, some electronic devices also include display units such as display screens, and some electronic devices also include human-computer interaction elements such as buttons, keyboards, etc. As long as the electronic device can execute the computer-readable program in the memory to implement the method of the present invention or at least part of the steps of the method, it can be considered as an electronic device covered by the present invention.

[0129] Through the above description of the implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by combining software with necessary hardware. Figure 5 As shown, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes a number of commands to enable a computing device (which can be a personal computer, a server, or a network device, etc.) to execute the above method according to the embodiment of the present invention.

[0130] The software product may be any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, a system, device or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0131] The computer readable storage medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The readable storage medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with a command execution system, device, or device. The program code contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

[0132] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0133] The computer-readable medium carries one or more programs. When the one or more programs are executed by a device, the computer-readable medium implements the data interaction method of the present disclosure.

[0134] Those skilled in the art will appreciate that the above modules can be distributed in the device according to the description of the embodiment, or can be changed accordingly and only used in one or more devices different from the embodiment. The modules of the above embodiments can be combined into one module, or further divided into multiple sub-modules.

[0135] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several commands to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiment of the present invention.

[0136] It should be noted that the above detailed descriptions are exemplary and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the present application belongs.

[0137] In the above detailed description, reference is made to the accompanying drawings, which form a part of this document. In the accompanying drawings, similar symbols typically identify similar components unless the context indicates otherwise. The illustrated embodiments described in the detailed description, drawings, and claims are not meant to be limiting. Other embodiments may be used, and other changes may be made, without departing from the spirit or scope of the subject matter presented herein.

[0138] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for automatically backing up data based on a cloud disk APP, characterized in that: The automatic data backup processing method comprises: Collect travel information and user location information recorded in calendars or documents, and prompt users to fill in time information related to key events when logging into the APP for the first time; Every time the calendar database is read, a comparison is performed to determine whether there is any new travel information. The new travel information is uploaded to the cloud, and the information related to travel plans, anniversaries, and key times is analyzed through the natural language processing model; Send the analyzed information related to travel plans, anniversaries, and key times to the client and save it in the user database; When changes are detected in the user's database such as travel plans, anniversaries, or key times, the corresponding backup task will be automatically executed at the specified time.

2. The method for automatic data backup processing according to claim 1, characterized in that: When a change in the user's travel plan, anniversary, or key time is detected in the user database, the corresponding backup task is automatically executed at the specified time, including: When the user database is monitored for new flight ticket information, train ticket information or other travel information, new anniversary information, and information changes with specified time stamps, that is, there is a change trigger, the corresponding backup task will be automatically determined to be executed.

3. The data automatic backup processing method according to claim 1, characterized in that: include: In the event of conflicts between multiple devices, a two-way synchronization mechanism allows data to be updated bidirectionally between the mobile phone and the cloud.

4. The method for automatic data backup processing according to claim 1, characterized in that: include: Determine the best backup time based on the data change time, including calculating the ideal backup window and using the self-built user time prediction model to determine the ideal backup window; Specifically, the content is prioritized according to the trigger conditions, importance and shooting date, and the high priority item is set as the current backup task based on the determined priority.

5. The method for automatic data backup processing according to claim 1, characterized in that: include: Set a specified time point, perform natural language processing analysis on the user's mobile phone calendar data, extract calendar data related to travel plans, anniversaries, key times, and holidays in all itineraries, and return it to the client; Perform natural language processing analysis on the user's mobile phone calendar data within a specified time period, extract calendar data related to travel plans, anniversaries, key times, and holidays in all itineraries, and return it to the client.

6. The method for automatic data backup processing according to claim 1, characterized in that: include: Using the CRNN algorithm, a natural language processing model is constructed to identify the text content recorded in logs or memos; A training data set is established using text content labeled with birthday tags, anniversary tags, and travel tags to train the constructed natural language processing model to obtain a trained natural language processing model.

7. The method for automatic data backup processing according to claim 1, characterized in that: include: Different backup tasks are determined according to different trigger conditions, wherein the trigger conditions include whether data extraction is completed, whether access rights are confirmed, and whether events within a specific time range are screened. The specific time range is specifically a specified time calculated from the current time forward, and the specified time includes one day, two days, three days, one week, ten days, two weeks, one month, two months, and half a year.

8. A data automatic backup processing device based on a cloud disk APP, characterized in that: It executes the data automatic backup processing method according to any one of claims 1 to 7, and the data automatic backup processing device comprises: The collection module collects the travel information and user location information recorded in the calendar or documents, and prompts users to fill in the time information related to key events when logging into the APP for the first time; The determination module performs a check and comparison every time the calendar database is read to determine whether there is any new itinerary information, uploads the new itinerary information to the cloud, and analyzes the information related to travel plans, anniversaries, and key times through the natural language processing model; The analysis module is used to send the analyzed information related to travel plans, anniversaries, and key times to the client and save it to the user database; The backup module automatically executes the corresponding backup task at the specified time when it detects changes in travel plans, anniversaries, and key times in the user database.

9. The data automatic backup processing device according to claim 8, characterized in that: include: When the user database is monitored for new flight ticket information, train ticket information or other travel information, new anniversary information, and information changes with specified time stamps, that is, there is a change trigger, the corresponding backup task will be automatically determined to be executed.

10. The data automatic backup processing device according to claim 8, characterized in that: include: In the event of conflicts between multiple devices, a two-way synchronization mechanism allows data to be updated bidirectionally between the mobile phone and the cloud.

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