Search suggestion methods, devices, equipment, and storage media

Abstract

This disclosure provides a search suggestion method, apparatus, device, and storage medium. This disclosure relates to the field of computer technology, and more particularly to the fields of intelligent search and cloud services. The specific implementation involves: searching for suggestion information based on search terms in a suggestion information database associated with storage space; the suggestion information database is a database established based on resources within the storage space; if candidate suggestion information matching the search terms exists in the suggestion information database, input suggestion information is obtained based on the candidate suggestion information. In this embodiment, the search suggestion is performed using a suggestion information database associated with storage space, and the obtained input suggestion information is associated with resources within the storage space, thereby helping to prompt the user to input information that is more relevant to resources within the storage space during the search.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and in particular to the fields of intelligent search and cloud services. Background Technology

[0002] Personal data is increasingly being used in internet products, such as messages received in instant messaging (IM) and personal resources stored in cloud storage. Over time, this personal data accumulates significantly. Currently, most products provide search suggestions based on the frequency of searches for public resources. Summary of the Invention

[0003] This disclosure provides a search suggestion method, apparatus, device, and storage medium.

[0004] According to one aspect of this disclosure, a search suggestion method is provided, comprising:

[0005] In the suggestion information database associated with the storage space, suggestions are searched based on search terms. The suggestion information database is a database built based on the resources within the storage space.

[0006] If candidate suggestions matching the search term exist in the suggestion information database, input suggestions are obtained based on the candidate suggestions.

[0007] According to another aspect of this disclosure, a search suggestion device is provided, comprising:

[0008] The first search module is used to search for prompt information in the prompt information database associated with the storage space based on search terms. The prompt information database is a database built based on the resources in the storage space.

[0009] The suggestion module is used to obtain input suggestion information based on the candidate suggestion information that matches the search term in the suggestion information database.

[0010] According to another aspect of this disclosure, an electronic device is provided, comprising:

[0011] At least one processor; and

[0012] The memory is communicatively connected to the at least one processor; wherein,

[0013] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the methods of any embodiment of the present disclosure.

[0014] According to another aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are used to cause the computer to perform a method according to any embodiment of this disclosure.

[0015] According to another aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements a method according to any embodiment of this disclosure.

[0016] In this embodiment of the disclosure, a prompt information library associated with the storage space is used for search prompts. The obtained input prompt information is associated with the resources in the storage space, which helps to prompt the user to enter information that is more consistent with the resources in the storage space when searching.

[0017] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0018] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein:

[0019] Figure 1 This is a schematic flowchart of a search suggestion method according to an embodiment of the present disclosure;

[0020] Figure 2 This is a flowchart illustrating a search suggestion method according to another embodiment of the present disclosure;

[0021] Figure 3 This is a flowchart illustrating a search suggestion method according to another embodiment of the present disclosure;

[0022] Figure 4 This is a schematic diagram of the structure of a search suggestion device according to an embodiment of the present disclosure;

[0023] Figure 5 This is a schematic diagram of the structure of a search suggestion device according to another embodiment of the present disclosure;

[0024] Figure 6 This is a schematic diagram of the structure of a search suggestion device according to another embodiment of the present disclosure;

[0025] Figure 7 This is a schematic diagram of the structure of a search suggestion device according to another embodiment of the present disclosure;

[0026] Figure 8 This is a schematic diagram illustrating an application scenario of the search suggestion method according to an embodiment of this disclosure;

[0027] Figure 9This is a block diagram of an electronic device used to implement the search suggestion method of the embodiments of this disclosure. Detailed Implementation

[0028] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0029] Figure 1 This is a flowchart illustrating a search suggestion method according to an embodiment of the present disclosure. The method may include:

[0030] S101. In the prompt information database associated with the storage space, a prompt information search is performed based on the search term. The prompt information database is a database built based on the resources in the storage space.

[0031] S102. If there are candidate prompts in the prompt information database that match the search term, obtain the input prompt information based on the candidate prompts.

[0032] In this embodiment, the storage space may include various resources such as audio, video, text, and program files. Data in different users' storage spaces is typically isolated. Users increasingly need to search for information within their own storage spaces. However, due to the large capacity of hard drives, cloud drives, and other storage spaces, the number of resources they can store is also very large, and users may not be able to remember all the information about the resources. When searching a storage space, a user may only be able to roughly remember a small amount of information about the resource name, resulting in a large amount of data retrieved, requiring a secondary search within the search results. However, if search suggestions are provided to users using the search frequency of public resources, the suggested information may not be related to the resources within the storage space, and searching based on these suggestions may not yield accurate search results. In this embodiment, "search" can also be referred to as "retrieval" or "query."

[0033] In this embodiment, a suggestion database associated with the storage space is used for search suggestions. The obtained input suggestion information is associated with resources within the storage space, thereby helping to prompt the user to input information that is more relevant to the resources within the storage space during the search. Furthermore, the more accurate the input search information, the faster and more accurate the search for resources within the storage space is achieved, improving search efficiency.

[0034] In this embodiment, the prompt information database can be stored on a server, such as a cloud server (also known as cloud computing, cloud services, etc.), on a client, such as a computer, mobile phone, or PDA, or in a storage space that needs to be searched. The prompt information database can store various keywords related to resources within the storage space. Keywords, also called key words, can include, but are not limited to, words, single characters, phrases, and short sentences. The length of the keywords to be stored can be set according to specific needs and application scenarios. Prompt information, also called prompt words, can include, but are not limited to, words, single characters, phrases, and short sentences. The length of the prompt information to be displayed can be set according to specific needs and application scenarios.

[0035] In one example, after a user enters a search term, the client can send a search request containing that term to the server. The search term can include, but is not limited to, single characters, words, and phrases. Upon receiving the search request, the server can search for suggestions based on the search term in a suggestion database stored on the server or in its storage space. Since the suggestion database is a database built based on resources within the storage space, the keywords stored therein are associated with those resources. If a keyword matching the search term is found in the suggestion database, it can be used as a candidate suggestion. The server can then use this candidate suggestion to derive the input suggestion and send it to the client. Alternatively, the server can send the candidate suggestion to the client, allowing the client to derive the input suggestion. If no keyword matching the search term is found in the suggestion database, the server can return a search failure result to the client or not return any information. The client can choose not to receive a prompt upon receiving a search failure result or not receiving any information.

[0036] In one example, after a user enters a search term, the client can search for suggestions based on that term in a suggestion database stored in storage space or elsewhere locally. If a keyword matching the search term is found in the suggestion database, it can be used as a candidate suggestion, and the client can then use this candidate suggestion to determine the input suggestion. If no keyword matching the search term is found in the suggestion database, the client can choose not to provide a suggestion.

[0037] Furthermore, matching within the suggestion database can employ methods such as exact matching and fuzzy matching. For instance, if exact matching fails to find candidate suggestions matching the search term, fuzzy matching can then be used to retrieve matching suggestions.

[0038] Figure 2This is a flowchart illustrating a search suggestion method according to another embodiment of the present disclosure. The method of this embodiment includes one or more features of the search suggestion method embodiments described above. The method may further include:

[0039] S201. Extract keywords from the identification information of resources within the storage space;

[0040] S202, Count the number of times keywords appear;

[0041] S203. Save the keywords and their corresponding frequency of occurrence into the prompt information database.

[0042] In this embodiment, the notification information database can be established and maintained by a server or by a client. The database can be updated at regular intervals, such as every few hours, daily, or weekly, or it can be updated upon detecting changes in storage space.

[0043] In one example, after extracting keywords from the resource identification information in the storage space, the server can count the occurrences of each keyword and then save the keywords and their occurrences to the server's local hint information database. Furthermore, the server can send this hint information database to the client. When the server updates its local hint information database, it can also send update information to the client to update the client's saved hint information database.

[0044] In one example, after extracting keywords from the resource identification information in the storage space, the client can count the occurrences of each keyword and then save the keywords and their occurrences to the client's local hint information database. Furthermore, the client can also send this hint information database to the server. When updating its local hint information database, the client can also send update information to the server to update the server's stored hint information database.

[0045] In this embodiment, the resource identification information can be processed such as word segmentation to extract keywords and count the keywords of multiple resources. For example, keyword A appears 5 times, and keyword B appears 3 times. Each keyword and its frequency can be saved in a table or similar format. By extracting keywords from the resource identification information in the storage space and correspondingly saving the keywords and their frequencies in the prompt information database, the prompt information database is associated with the resources in the storage space. This supports search prompts associated with the resources in the storage space, improves the accuracy of prompts, and thus improves search efficiency.

[0046] In one possible implementation, the storage space includes user cloud storage space, and the resource identification information includes the names of files stored in the user cloud storage space. Extracting keywords from the resource identification information in the storage space includes: extracting keywords from the names of files stored in the user cloud storage space.

[0047] In this embodiment, data resources within the cloud storage spaces of different users are typically isolated, but data resource sharing between users is also supported. Users can log in to their own cloud storage spaces using their own accounts and perform operations such as adding, deleting, and modifying resources within their cloud storage spaces. The resources stored in the cloud storage spaces of different users may be different. Users may include individual users, enterprise users, etc., and this embodiment does not impose any limitations.

[0048] In this embodiment of the disclosure, resources may include files such as audio, video, text, and programs. Resource identification information may include the file name. The server or client can extract keywords from the names of files stored in the user's cloud storage space. For example, if the file name includes "Picture Book 'XXX,' suitable for children aged 1 to 3," the keywords extracted from that name may include "XXX." After extracting keywords from the file names in the user's cloud storage space, the keywords in the file names and their frequency of occurrence can be correspondingly stored in a prompt information database. This establishes an association between the prompt information database and the resources in the user's cloud storage space, supporting search prompts associated with files in the user's cloud storage space, improving prompt accuracy, and thus improving the search efficiency for files in the user's cloud storage space.

[0049] In one possible implementation, searching for prompt information based on search terms in a prompt information database associated with the storage space includes:

[0050] If the suggestion information store contains M suggestions that match the search term, the N suggestions that appear most frequently among the M suggestions are selected as candidate suggestions, where M is greater than N, N is the maximum number of candidate suggestions that can be displayed, the frequency of occurrence is sorted in descending order, and M and N are positive integers.

[0051] In this embodiment, if a large number of prompts are found in the prompt information database based on a certain search term, a portion of them can be selected as candidate prompts. The maximum number N of candidate prompts that can be displayed can be preset. If the number M of prompts found in the prompt information database based on a certain search term is greater than N, N prompts can be selected from the M prompts as candidate prompts. Candidate prompts can be selected randomly or according to their frequency of occurrence. For example, the M prompts can be arranged in descending order of their frequency of occurrence, and the top N prompts can be retained as candidate prompts. For example, if the search term is "less," the prompts found in the prompt information database are: "children's music," 10 times; "children's English," 3 times; "children's picture books," 6 times; and "ethnic minority customs," 1 time. If N is set to 2, then the top two, "children's music" and "children's picture books," are selected as candidate prompts.

[0052] Furthermore, if the number of prompts obtained from the prompt information database based on a certain search term is less than or equal to N, then all the prompts obtained from the search can be used as candidate prompts.

[0053] In this embodiment of the disclosure, selecting the top-ranked prompt information as candidate prompt information can improve the accuracy of the prompts.

[0054] In one possible implementation, the input prompt information is obtained based on the candidate prompt information, including:

[0055] Sort the multiple candidate prompts in descending order of their frequency of occurrence to obtain the sorting result;

[0056] Display input suggestions on the user interface, including the sorting results.

[0057] In this embodiment, if the candidate prompts are not sorted, they can be arranged in descending order of frequency to obtain a sorting result. If the candidate prompts are already sorted, the sorting step can be omitted. The sorting result includes the candidate prompts in descending order. For example, the candidate prompts before sorting include "Children's Music" (10 times), "Children's English" (3 times), "Children's Picture Books" (6 times), and "Ethnic Minority Customs" (1 time). The sorting result can include: "Children's Music" (10 times), "Children's Picture Books" (6 times), "Children's English" (3 times), and "Ethnic Minority Customs" (1 time). Generally, the more times a resource appears in the identifier information within the storage unit, the greater the likelihood of it being selected by the user. Including the sorting result in the input prompts displayed on the user interface helps improve the accuracy of the prompts. In one example, the descending sorting step can be performed by the server, and then the server sends the sorting result to the client, which displays the input prompts including the sorting result. In another example, the descending sorting step can be performed by the client, and then the client displays the input prompts including the sorting result. In this embodiment of the disclosure, the client may display input prompts on the user interface in various ways. For example, it may display them as a drop-down list in the search box, or as a prompt window near the search box.

[0058] In this embodiment of the disclosure, by inputting prompt information, prompts can be made for resources associated with resources in the storage space. The accuracy is high, which improves the accuracy of the information entered in the search box in the storage space, and thus enables the user to quickly obtain the search results they need in the storage space.

[0059] Figure 3 This is a flowchart illustrating a search suggestion method according to another embodiment of the present disclosure. The method of this embodiment includes one or more features of the search suggestion method embodiments described above. The method may further include:

[0060] S301. In response to the selection operation in the input prompt message, the selected information is entered into the search box of the storage space;

[0061] S302. Search for resources within the storage space based on the information entered in the search box.

[0062] In this embodiment of the disclosure, after seeing the input prompts displayed on the user interface, the user can select the information they need to input. For example, the displayed input prompts include "children's music" and "children's picture books." If the user selects "children's picture books," they can enter "children's picture books" in the search box within the storage space. Then, if the search can be automatic or in response to actions such as the user clicking the search button, resources related to "children's picture books" can be searched within the storage space. For example, files whose names include "children's picture books" can be searched within the user's cloud storage space.

[0063] Figure 4 This is a schematic diagram of a search suggestion device according to an embodiment of the present disclosure. The device may include:

[0064] The first search module 401 is used to search for prompt information in a prompt information database associated with the storage space based on search terms. The prompt information database is a database built based on the resources in the storage space.

[0065] The prompt module 402 is used to obtain input prompt information based on the candidate prompt information that matches the search term when there are candidate prompt information in the prompt information library.

[0066] Figure 5 This is a schematic diagram of a search suggestion device according to another embodiment of the present disclosure. The device of this embodiment includes one or more features of the search suggestion device embodiment described above. The device may further include:

[0067] Extraction module 501 is used to extract keywords from the identification information of resources in the storage space;

[0068] Module 502 is used to count the frequency of keyword occurrences.

[0069] The storage module 503 is used to save keywords and their corresponding frequency of occurrence into the prompt information database.

[0070] In one possible implementation, the storage space includes a user cloud storage space, the resource identification information includes the names of files stored in the user cloud storage space, and the extraction module 501 is used to extract keywords from the names of files stored in the user cloud storage space.

[0071] In one possible implementation, the first search module 401 is configured to:

[0072] If the suggestion information store contains M suggestions that match the search term, the N suggestions that appear most frequently among the M suggestions are selected as candidate suggestions, where M is greater than N, N is the maximum number of candidate suggestions that can be displayed, the frequency of occurrence is sorted in descending order, and M and N are positive integers.

[0073] Figure 6 This is a schematic diagram of a search suggestion device according to another embodiment of the present disclosure, which includes one or more features of the search suggestion device embodiment described above. In one possible implementation, the suggestion module 402 includes:

[0074] The sorting submodule 601 is used to sort multiple candidate prompts in descending order of their frequency of occurrence to obtain the sorting result.

[0075] Display submodule 602 is used to display input prompts on the user interface, including sorting results.

[0076] Figure 7 This is a schematic diagram of a search suggestion device according to another embodiment of the present disclosure. The device of this embodiment includes one or more features of the search suggestion device embodiment described above. The device further includes:

[0077] The selection module 701, in response to the selection operation in the input prompt message, inputs the selected information into the search box of the storage space;

[0078] The second search module 702 is used to perform resource searches within the storage space based on the information entered in the search box.

[0079] For a description of the specific functions and examples of each module and submodule of the search suggestion device in this embodiment, please refer to the relevant descriptions of the corresponding steps in the above-described search suggestion method embodiments, which will not be repeated here.

[0080] Figure 8 This is a schematic diagram illustrating an application scenario of the search suggestion method according to an embodiment of this disclosure. Taking personal cloud storage space as an example, the search suggestion method may include an offline component and an online component, wherein:

[0081] I. Offline Part:

[0082] First, obtain the names of resources within the user's personal cloud storage space, such as file names. Then, perform keyword extraction processing on the resource names. For example, if a resource is named "Audio Picture Book 'I Am a Math Fan'", the keyword "I Am a Math Fan" can be extracted.

[0083] The frequency of each extracted keyword is calculated. For example, keywords a, b, and c are extracted from user file 1; keywords b, c, and d are extracted from user file 2; and keywords a, b, and d are extracted from user file n. The counts show a appears twice, b three times, c twice, and d twice. Then, the keywords and their frequencies are stored in a keyword database. The keyword database can be updated at regular intervals, such as daily, weekly, or monthly, or updated when changes in cloud storage resources are detected.

[0084] II. Online Section:

[0085] If a user initiates a search by entering a single character, such as "I," the system can query the database (i.e., the suggestion dictionary) for keywords that begin with "I." Then, the search results can be sorted by the frequency of each keyword, with the most frequent keywords appearing at the top. Furthermore, the total number of keywords displayed can be limited, for example, to N. For instance, "my music," 10 times; "my heart soars," 8 times; "my videos," 3 times; "you and me," 1 time. If the limit for the number of suggested keywords, N, is 2, then when the user enters "I," the suggestion effect could be: "1. My music, 2. My heart soars."

[0086] The acquisition, storage, and application of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0087] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0088] Figure 9 A schematic block diagram of an example electronic device 900 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0089] like Figure 9As shown, device 900 includes a computing unit 901, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 902 or a computer program loaded from storage unit 908 into random access memory (RAM) 903. RAM 903 may also store various programs and data required for the operation of device 900. The computing unit 901, ROM 902, and RAM 903 are interconnected via bus 904. Input / output (I / O) interface 905 is also connected to bus 904.

[0090] Multiple components in device 900 are connected to I / O interface 905, including: input unit 906, such as keyboard, mouse, etc.; output unit 907, such as various types of monitors, speakers, etc.; storage unit 908, such as disk, optical disk, etc.; and communication unit 909, such as network card, modem, wireless transceiver, etc. Communication unit 909 allows device 900 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0091] The computing unit 901 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 901 performs the various methods and processes described above, such as the search suggestion method. For example, in some embodiments, the search suggestion method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 908. In some embodiments, part or all of the computer program may be loaded and / or installed on device 900 via ROM 902 and / or communication unit 909. When the computer program is loaded into RAM 903 and executed by the computing unit 901, one or more steps of the search suggestion method described above may be performed. Alternatively, in other embodiments, the computing unit 901 may be configured to perform the search suggestion method by any other suitable means (e.g., by means of firmware).

[0092] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0093] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0094] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0095] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0096] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0097] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0098] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0099] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A search suggestion method, comprising: In the suggestion information database associated with the storage space, suggestion information is searched based on search terms. The suggestion information database is a database built based on the resources within the storage space. The suggestion information database includes keywords of the resources stored in the storage space and their frequency of occurrence. The storage space includes the user's cloud storage space, and a user's cloud storage space includes the user's own data resources. If candidate prompts matching the search term exist in the prompt information database, input prompts are obtained based on the candidate prompts; wherein, the candidate prompts are determined based on the frequency of occurrence of multiple keywords matching the search term in the prompt information database.

2. The method according to claim 1, further comprising: Extract keywords from the identification information of resources within the storage space; Count the number of times the keywords appear; The keywords and their corresponding frequency of occurrence are saved in the prompt information database.

3. The method according to claim 2, wherein, The resource identification information includes the names of files stored in the user's cloud storage space. Keywords are extracted from the resource identification information in the storage space, including: Extract the keywords from the names of the files stored in the user's cloud storage space.

4. The method according to any one of claims 1 to 3, wherein searching for prompt information in a prompt information database associated with the storage space based on search terms includes: If the prompt information library contains M prompt information that match the search term, the prompt information with the highest N occurrences among the M prompt information is selected as candidate prompt information, where M is greater than N, N is the maximum number of candidate prompt information that can be displayed, the occurrence counts are sorted in descending order, and M and N are positive integers.

5. The method according to any one of claims 1 to 3, wherein, The input prompt information is obtained based on the candidate prompt information, including: The candidate prompts are sorted in descending order of their frequency of occurrence to obtain the sorting result; The input prompt information is displayed on the user interface, and the input prompt information includes the sorting results.

6. The method according to claim 5, further comprising: In response to the selection operation in the input prompt information, the selected information is entered into the search box of the storage space; The resource is searched within the storage space based on the information entered in the search box.

7. A search suggestion device, comprising: The first search module is used to search for prompt information in a prompt information database associated with the storage space based on search terms. The prompt information database is a database built based on the resources in the storage space. The prompt information database includes keywords of the resources stored in the storage space and their frequency of occurrence. The storage space includes the user's cloud storage space, and a user's cloud storage space includes the user's own data resources. The prompting module is used to obtain input prompting information based on the candidate prompting information when there are candidate prompting information matching the search term in the prompting information database; wherein the candidate prompting information is determined based on the occurrence frequency of multiple keywords matching the search term in the prompting information database.

8. The apparatus according to claim 7, further comprising: The extraction module is used to extract keywords from the identification information of resources within the storage space; The statistics module is used to count the number of times the keywords appear; The storage module is used to save the keywords and their corresponding frequency of occurrence into the prompt information database.

9. The apparatus according to claim 8, wherein, The resource identification information includes the names of files stored in the user's cloud storage space, and the extraction module is used to extract the keywords from the names of files stored in the user's cloud storage space.

10. The apparatus according to any one of claims 7 to 9, wherein the first search module is configured to: If the suggestion information library contains M suggestions that match the search term, the suggestion that appears most frequently among the M suggestions is selected as candidate suggestions. M is greater than N, where N is the maximum number of candidate prompts that can be displayed, the occurrence counts are arranged in descending order, and M and N are positive integers.

11. The apparatus according to any one of claims 7 to 9, wherein, The prompting module includes: The sorting submodule is used to sort the multiple candidate prompts in descending order of their frequency of occurrence to obtain a sorting result. The display submodule is used to display the input prompt information on the user interface, the input prompt information including the sorting results.

12. The apparatus of claim 11, further comprising: The selection module, in response to the selection operation in the input prompt information, inputs the selected information into the search box of the storage space; The second search module is used to perform resource searches within the storage space based on the information entered in the search box.

13. An electronic device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.

14. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-6.

15. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1-6.

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