Recommended method and device, electronic equipment and medium

Abstract

The present disclosure provides a recommendation method and device, electronic equipment and medium, relates to the technical field of artificial intelligence, and particularly relates to the technical field of intelligent search. The implementation scheme is: receiving a plurality of characters in an input search box; determining, for a group of continuous characters in the plurality of characters, recognition results of at least two different languages corresponding to the continuous characters; and determining, based on the recognition results of the at least two different languages, a recommended search item for the plurality of characters.

Description

Technical Field

[0001] This disclosure relates to the field of artificial intelligence technology, and more particularly to the field of intelligent search technology, specifically to recommendation methods, apparatus, electronic devices, computer-readable storage media, and computer program products. Background Technology

[0002] Artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies mainly include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0003] The methods described in this section are not necessarily methods that had been previously conceived or adopted. Unless otherwise specified, no method described in this section should be assumed to be prior art simply because it is included in this section. Similarly, unless otherwise specified, the issues mentioned in this section should not be considered to be accepted in any prior art. Summary of the Invention

[0004] This disclosure provides a recommended method, apparatus, electronic device, computer-readable storage medium, and computer program product.

[0005] According to one aspect of this disclosure, a recommendation method is provided, comprising: receiving multiple characters in an input search box; determining, for a set of consecutive characters among the multiple characters, recognition results in at least two different languages ​​corresponding to the consecutive characters; and determining recommended search terms for the multiple characters based on the recognition results in at least two different languages.

[0006] According to another aspect of this disclosure, a recommendation apparatus is provided, comprising: a receiving unit configured to receive a plurality of characters in an input search box; a first determining unit configured to determine, for a set of consecutive characters among the plurality of characters, recognition results in at least two different languages ​​corresponding to the consecutive characters; and a second determining unit configured to determine recommended search terms for the plurality of characters based on the recognition results in at least two different languages.

[0007] According to another aspect of this disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the methods described above.

[0008] 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 a computer to perform the methods described above.

[0009] According to another aspect of this disclosure, a computer program product is provided, including a computer program, wherein the computer program implements the above-described method when executed by a processor.

[0010] According to one or more embodiments of this disclosure, the accuracy of search recommendations can be improved.

[0011] 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

[0012] The accompanying drawings exemplify embodiments and form part of the specification, serving together with the textual description to explain exemplary implementations of the embodiments. The illustrated embodiments are for illustrative purposes only and do not limit the scope of the claims. Throughout the drawings, the same reference numerals refer to similar but not necessarily identical elements.

[0013] Figure 1 A schematic diagram of an exemplary system in which the various methods described herein may be implemented according to embodiments of the present disclosure is shown;

[0014] Figure 2 A flowchart illustrating a recommended method according to an embodiment of the present disclosure is shown;

[0015] Figure 3 A schematic diagram of a recommended method according to an embodiment of the present disclosure is shown;

[0016] Figures 4A-4C An application scenario diagram of the recommended method according to embodiments of the present disclosure is shown;

[0017] Figure 5 A structural block diagram of a recommended apparatus according to an embodiment of the present disclosure is shown; and

[0018] Figure 6 A structural block diagram of an exemplary electronic device that can be used to implement embodiments of the present disclosure is shown. Detailed Implementation

[0019] 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 of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0020] In this disclosure, unless otherwise stated, the use of terms such as "first," "second," etc., to describe various elements is not intended to limit the positional, temporal, or importance relationships of these elements; such terms are merely used to distinguish one element from another. In some examples, the first element and the second element may refer to the same instance of that element, while in other cases, based on the context, they may refer to different instances.

[0021] The terminology used in the description of the various examples in this disclosure is for the purpose of describing particular examples only and is not intended to be limiting. Unless the context explicitly indicates otherwise, an element may be one or more unless the number of elements is specifically limited. Furthermore, the term "and / or" as used in this disclosure covers any one of the listed items and all possible combinations thereof.

[0022] When a user performs a search, the system typically provides search results based on multiple characters entered in the search box. To improve search efficiency and accuracy, search applications often offer search recommendation functions based on the multiple characters entered by the user. For example, after a user enters "Spring Festival" in the search box, multiple recommended search terms such as "Spring Festival Gala," "Spring Festival Customs," and "Spring Festival Holiday" can be displayed below the search box for the user to choose from.

[0023] However, the determination of recommended search terms depends on multiple characters entered by the user. This requires the user to correctly input the characters used for the search to obtain accurate recommended search terms. Conversely, if the user enters incorrect characters, incorrect recommended search terms will be generated based on the incorrect characters. Thus, effective search recommendations cannot be provided to the user, resulting in a poor user experience.

[0024] Based on this, this disclosure proposes a recommendation method that, for a set of consecutive characters among multiple characters in an input search box, determines the recognition results in at least two different languages ​​corresponding to that set of consecutive characters, and determines recommended search terms based on these recognition results in at least two different languages. Thus, even if the user enters the wrong language due to delays in language switching, search recommendations can still be performed based on the multilingual recognition results of consecutive characters among multiple characters, avoiding recommendation bias caused by user language errors, improving the accuracy of search recommendations, and enhancing the user experience.

[0025] The embodiments of this disclosure will now be described in detail with reference to the accompanying drawings.

[0026] Figure 1 A schematic diagram of an exemplary system 100 in which the various methods and apparatus described herein can be implemented according to embodiments of this disclosure is shown. Reference Figure 1 The system 100 includes one or more client devices 101, 102, 103, 104, 105 and 106, a server 120, and one or more communication networks 110 coupling the one or more client devices to the server 120. The client devices 101, 102, 103, 104, 105 and 106 can be configured to execute one or more applications.

[0027] In embodiments of this disclosure, server 120 may run one or more services or software applications that enable the execution of any one of the steps in the recommended method.

[0028] In some embodiments, server 120 may also provide other services or software applications, which may include non-virtual and virtual environments. In some embodiments, these services may be provided as web-based services or cloud services, such as to users of client devices 101, 102, 103, 104, 105, and / or 106 under a Software as a Service (SaaS) model.

[0029] exist Figure 1 In the configuration shown, server 120 may include one or more components that implement the functions performed by server 120. These components may include software components, hardware components, or combinations thereof that can be executed by one or more processors. Users operating client devices 101, 102, 103, 104, 105, and / or 106 can sequentially interact with server 120 using one or more client applications to utilize the services provided by these components. It should be understood that various different system configurations are possible and may differ from system 100. Therefore, Figure 1 This is an example of a system used to implement the various methods described herein, and is not intended to be limiting.

[0030] Users can use client devices 101, 102, 103, 104, 105, and / or 106 to receive multiple characters input by the user and provide recommended search terms. The client devices can provide an interface that allows users to interact with the client devices. The client devices can also output information to the user through this interface. Although... Figure 1 Only six client devices are described, but those skilled in the art will understand that this disclosure can support any number of client devices.

[0031] Client devices 101, 102, 103, 104, 105, and / or 106 may include various types of computer devices, such as portable handheld devices, general-purpose computers (such as personal computers and laptops), workstation computers, wearable devices, smart screen devices, self-service terminal devices, service robots, gaming systems, thin clients, various messaging devices, sensors, or other sensing devices. These computer devices can run various types and versions of software applications and operating systems, such as Microsoft Windows, Apple iOS, UNIX-like operating systems, Linux or Linux-like operating systems (such as Google Chrome OS); or include various mobile operating systems, such as Microsoft Windows Mobile OS, iOS, Windows Phone, and Android. Portable handheld devices may include cellular phones, smartphones, tablets, personal digital assistants (PDAs), etc. Wearable devices may include head-mounted displays (such as smart glasses) and other devices. Gaming systems may include various handheld gaming devices, internet-enabled gaming devices, etc. Client devices are capable of executing various applications, such as various internet-related applications, communication applications (such as email applications), short message service (SMS) applications, and can use various communication protocols.

[0032] Network 110 can be any type of network well known to those skilled in the art, and can use any of a variety of available protocols (including but not limited to TCP / IP, SNA, IPX, etc.) to support data communication. By way of example only, one or more networks 110 can be a local area network (LAN), an Ethernet-based network, a token ring network, a wide area network (WAN), the Internet, a virtual network, a virtual private network (VPN), an intranet, an extranet, a blockchain network, a public switched telephone network (PSTN), an infrared network, a wireless network (e.g., Bluetooth, WIFI), and / or any combination of these and / or other networks.

[0033] Server 120 may include one or more general-purpose computers, special-purpose server computers (e.g., PC (personal computer) servers, UNIX servers, mid-range servers), blade servers, mainframe computers, server clusters, or any other suitable arrangement and / or combination. Server 120 may include one or more virtual machines running a virtual operating system, or other computing architectures involving virtualization (e.g., one or more flexible pools of logical storage devices that can be virtualized to maintain virtual storage devices for servers). In various embodiments, server 120 may run one or more services or software applications that provide the functionality described below.

[0034] The computing unit in server 120 can run one or more operating systems, including any of the aforementioned operating systems and any commercially available server operating system. Server 120 can also run any of a variety of additional server applications and / or middleware applications, including HTTP servers, FTP servers, CGI servers, JAVA servers, database servers, etc.

[0035] In some implementations, server 120 may include one or more applications to analyze and merge data feeds and / or event updates received from users of client devices 101, 102, 103, 104, 105 and / or 106. Server 120 may also include one or more applications to display data feeds and / or real-time events via one or more display devices of client devices 101, 102, 103, 104, 105 and / or 106.

[0036] In some implementations, server 120 can be a server for a distributed system or a server integrated with blockchain. Server 120 can also be a cloud server, or an intelligent cloud computing server or intelligent cloud host with artificial intelligence technology. A cloud server is a host product in the cloud computing service system, designed to address the shortcomings of traditional physical hosts and Virtual Private Server (VPS) services, such as high management difficulty and weak business scalability.

[0037] System 100 may also include one or more databases 130. In some embodiments, these databases can be used to store data and other information. For example, one or more of databases 130 can be used to store information such as audio files and video files. Databases 130 can reside at various locations. For example, the databases used by server 120 can be local to server 120, or can be remote from server 120 and can communicate with server 120 via a network-based or dedicated connection. Databases 130 can be of different types. In some embodiments, the databases used by server 120 can be, for example, relational databases. One or more of these databases can store, update, and retrieve data to and from the databases in response to commands.

[0038] In some embodiments, one or more of databases 130 can also be used by applications to store application data. The databases used by applications can be different types of databases, such as key-value repositories, object repositories, or conventional repositories supported by a file system.

[0039] Figure 1 System 100 can be configured and operated in various ways to enable the application of the various methods and apparatuses described in this disclosure.

[0040] Figure 2 A flowchart of a recommendation method according to an exemplary embodiment of this disclosure is shown. This method 200 includes: Step S201, receiving multiple characters in an input search box; Step S202, for a set of consecutive characters among the multiple characters, determining at least two recognition results in different languages corresponding to the consecutive characters; and Step S203, based on the at least two recognition results in different languages, determining a recommended search term for the multiple characters.

[0041] During the search process, if there are situations such as untimely switching of the input language, it is easy to cause errors in the multiple characters entered by the user into the search box. For example, the user originally intended to enter the English word "ant", but the input method was wrongly set to the Chinese input mode. In this case, after the user enters the letter characters "a", "n", and "t" and then presses the confirmation key (such as the space bar, etc.), it may enter the wrong Chinese characters "按天" in the search box.

[0042] Based on the recommendation method proposed in this disclosure, multi-language recognition can be performed simultaneously for a set of consecutive characters among multiple characters input by a user. For example, for the consecutive characters "按天", determine the Chinese recognition result "按天" corresponding to "按天", and the English recognition result "ant" corresponding to "按天". Based on these multi-language recognition results, determine the recommended search terms, which can compensate for the recommendation deviation caused by the user's incorrect language input, improve the accuracy of search recommendations, and enhance the user experience.

[0043] In step S201, the multiple characters in the input search box can be a string in a single language or a string mixed with multiple languages, which is not limited herein.

[0044] In step S202, a set of consecutive characters can be a string in a single language among multiple characters. In other words, when the multiple characters are a string mixed with multiple languages, the multiple characters can be divided into multiple strings in a single language based on the change of language, and multi-language recognition is performed on each string separately.

[0045] According to some embodiments, the consecutive characters can be consecutive Chinese characters, and the consecutive characters are determined based on multiple input letters. And, determining at least two different language recognition results corresponding to the consecutive characters can include: determining the consecutive characters themselves as the Chinese recognition result corresponding to the consecutive characters; and determining the multiple letters used to determine the consecutive characters as the English recognition result corresponding to the consecutive characters.

[0046] In this way, the Chinese and English recognition results corresponding to the Chinese character string can be efficiently and accurately recognized, providing a multi-language recommendation basis for subsequent determination of recommended search terms.

[0047] For example, the consecutive Chinese characters are "按天", and "按天" is determined based on the letter characters "a", "n", and "t" input by the user. In this case, it can be determined that the Chinese recognition result corresponding to "按天" is "按天", and the English recognition result corresponding to "按天" is "ant". Both the Chinese recognition result "按天" and the English recognition result "ant" can be used as the recommendation basis for subsequent determination of recommended search terms.

[0048] In one implementation, the multiple letters used to determine the consecutive Chinese characters can be obtained through the input method application used by the user.

[0049] In another embodiment, during the process of a user inputting consecutive Chinese characters, the letter characters typed by the user can be cached through search applications; and when the user determines to input Chinese characters in the search box, such as when inputting Chinese characters by clicking the space bar, the cached letter characters can be used as the multiple letters corresponding to the Chinese characters.

[0050] According to some embodiments, the consecutive characters can be consecutive letter characters, and determining at least two recognition results in different languages corresponding to the consecutive characters can include: determining the consecutive characters themselves as the English recognition result corresponding to the consecutive characters; and determining the Chinese recognition result corresponding to the consecutive characters based on the Chinese pinyin represented by each of the consecutive characters.

[0051] In this way, the Chinese and English recognition results corresponding to an English character string can be efficiently and accurately recognized, providing a multi-language recommendation basis for subsequent determination of search recommendation items.

[0052] In one embodiment, determining the Chinese recognition result corresponding to the consecutive characters based on the Chinese pinyin represented by each of the consecutive characters can include: for each of the consecutive letter characters, in response to the Chinese pinyin represented by the character being an initial consonant, determining one of the Chinese characters in the Chinese recognition result based on the initial consonant corresponding to the character.

[0053] Specifically, in the case where the Chinese pinyin represented by the character after the initial consonant character is not a final consonant, determining one Chinese character based on the initial consonant character itself; in the case where the Chinese pinyin represented by several consecutive characters after the initial consonant character are all final consonants, determining one Chinese character based on the initial consonant character and the several consecutive final consonant characters.

[0054] For example, the consecutive letter characters are "jtiatq". Based on the Chinese pinyin represented by each of "jtiatq", the Chinese recognition result corresponding to "jtiatq" is determined. Specifically, by distinguishing the initial consonants and final consonants in "jtiatq", "jtiatq" is split into four parts: "j", "tia", "t", and "q", each part corresponding to one Chinese character, and thus the Chinese recognition result corresponding to "jtiatq" is determined as the four Chinese characters "今天天气".

[0055] It can be understood that based on the Chinese pinyin represented by each of the consecutive characters, multiple Chinese recognition results may be able to be determined. In this case, each determined Chinese recognition result can be applied to the subsequent process of determining recommended search items; or the Chinese recognition result with the highest semantic coherence or the highest usage frequency among the multiple Chinese recognition results can be applied to the subsequent process of determining recommended search items.

[0056] After identifying the results in at least two different languages, step S203 can be further executed to determine the recommended search terms to be fed back to the user.

[0057] According to some embodiments, determining recommended search terms for multiple characters based on recognition results in at least two different languages ​​may include: for each of the recognition results in at least two different languages, determining multiple candidate search terms corresponding to that recognition result; sorting the multiple candidate search terms corresponding to each of the at least two recognition results to determine a sorting result; and determining recommended search terms for multiple characters based on the sorting result.

[0058] The sorting of multiple candidate search terms corresponding to each of the at least two recognition results is to perform a unified sorting of the multiple candidate search terms corresponding to each recognition result. In other words, the determined sorting result includes multiple candidate search terms of different recognition results.

[0059] Therefore, based on the comprehensive ranking of candidate search terms corresponding to the recognition results of different languages, it is possible to provide users with recommended search terms under multiple different language recognition results.

[0060] According to some embodiments, for each of the recognition results in at least two different languages, determining multiple candidate search terms corresponding to that recognition result may include: performing semantic analysis on the recognition result to determine at least one recommended expression corresponding to the recognition result; and generating multiple candidate search terms corresponding to the recognition result based on the at least one recommended expression, wherein each candidate search term contains one of the at least one recommended expression. In this way, candidate search terms corresponding to the recognition result in each language can be effectively constructed.

[0061] The recommended expression corresponding to the identification result can be the identification result itself, or it can be an expression obtained after modifying, supplementing, or reasoning about the identification result. Preferably, the recommended expression can be an expression that is related to the identification result and has a high search frequency.

[0062] It is understandable that, since multiple characters in the input search box can simultaneously include multiple sets of consecutive characters, the multiple candidate search terms corresponding to the recognition result can also include recommended expressions corresponding to other consecutive characters, in addition to the recommended expression of the recognition result.

[0063] According to some embodiments, sorting multiple candidate search terms corresponding to each of at least two identification results may include: performing sorting based on the degree of association between each candidate search term and the user profile.

[0064] By combining user profiles to perform ranking, personalized ranking results can be generated for the current user, making the ranking results more suitable for the current user's search expectations, improving the accuracy of recommendations, and enhancing the user experience.

[0065] For example, if the user profile determines that the current user is a "designer", then candidate search terms related to art and design, that is, candidate search terms that are highly associated with "designer", can be given higher weights, so that these candidate search terms can be ranked higher.

[0066] Finally, a predetermined number of candidate search terms that rank highly in the sorting results are selected as recommended search terms. These recommended search terms can be displayed on the search application's interface for the user to choose from.

[0067] Figure 3 A schematic diagram of a recommended method according to an exemplary embodiment of the present disclosure is shown. Figure 3 As shown, the recommended method can be achieved through interaction between the mobile terminal 310 and the server 320.

[0068] The input module 311 in the mobile terminal 310 receives multiple characters entered by the user in the search box and sends the multiple characters to the server 320.

[0069] Server 320 receives the multiple characters. For a group of consecutive characters among the multiple characters, the Chinese recognition module 321 determines the Chinese recognition result, and the English recognition module 322 determines the English recognition result. The Chinese recognition result is transmitted to the Chinese recommendation module 323 through the Chinese recognition module 321 to determine multiple candidate search terms corresponding to the Chinese recognition result. The English recognition result is transmitted to the English recommendation module 324 through the English recognition module 322 to determine multiple candidate search terms corresponding to the English recognition result.

[0070] The server 320 inputs multiple candidate search terms corresponding to the Chinese recognition results and multiple candidate search terms corresponding to the English recognition results into the sorting module 325. Based on the sorting result of the sorting module 325, the server determines the highest-ranked, preset number of candidate search terms as recommended search terms. The server 320 then sends the determined preset number of recommended search terms to the mobile terminal 310.

[0071] The mobile terminal 310 receives a preset number of recommended search items and displays the preset number of recommended search items in the recommendation display module 312 in chronological order.

[0072] In this way, based on the multilingual recognition results, recommended search terms can be determined, compensating for recommendation bias caused by incorrect language input by the user, improving the accuracy of search recommendations, and enhancing the user experience.

[0073] It can be understood that in Figure 3 the recommended method shown, using two recognition methods in Chinese and English is only for the convenience of expression, and the present disclosure does not limit the number of recognition results in different languages determined.

[0074] Figures 4A to 4C Fig. shows an application scenario diagram of a recommended method according to an exemplary embodiment of the present disclosure.

[0075] In Figure 4A , although the user intends to input the English character "ant", since the current is in the Chinese input mode, the input method gives multiple Chinese expressions corresponding to "ant", and after the user presses the space bar, the Chinese expression "by day" is input into the search box.

[0076] In Figure 4B , the user inputs "by day design" in the search box. For the continuous characters "by day", performing Chinese recognition on "by day" gives "by day", and performing English recognition on "by day" gives "ant". Based on the recognition results in two languages of "by day" and "ant", multiple recommended search terms as shown in Figure 4B are obtained.

[0077] In Figure 4C , the user selects "ant design" from multiple recommended search terms. In this way, the content "by day design" wrongly input by the user is corrected to the content "ant design" that the user really intends to input. The improvement of the accuracy of the recommended search terms facilitates the user to select the content they really intend to search for, and improves the user's search efficiency.

[0078] Figure 5 Fig. shows a structural block diagram of a recommended device according to an exemplary embodiment of the present disclosure. As shown in Figure 5 , the recommended device 500 includes: a receiving unit 501 configured to receive multiple characters in the input search box; a first determination unit 502 configured to determine at least two recognition results in different languages corresponding to a set of continuous characters among the multiple characters; and a second determination unit 503 configured to determine recommended search terms for the multiple characters based on the at least two recognition results in different languages.

[0079] According to some embodiments, the continuous characters are continuous Chinese characters and are determined based on the multiple input letters, and wherein the first determination unit includes: a sub-unit for determining the continuous characters themselves as the Chinese recognition results corresponding to the continuous characters; and a sub-unit for determining the multiple letters used to determine the continuous characters as the English recognition results corresponding to the continuous characters.

[0080] According to some embodiments, the consecutive characters are consecutive alphabetic characters, and wherein the first determining unit includes: a subunit for determining the consecutive characters themselves as the English recognition result corresponding to the consecutive characters; and a subunit for determining the Chinese recognition result corresponding to the consecutive characters based on the Pinyin represented by each of the consecutive characters.

[0081] According to some embodiments, the second determining unit includes: a first determining subunit configured to determine a plurality of candidate search terms corresponding to each of the recognition results of at least two different languages; a sorting subunit configured to sort the plurality of candidate search terms corresponding to each of the recognition results of at least two languages ​​to determine a sorting result; and a second determining subunit configured to determine recommended search terms for multiple characters based on the sorting result.

[0082] According to some embodiments, the first determining subunit includes: a subunit for determining at least one recommended expression corresponding to the identification result by performing semantic analysis on the identification result; and a subunit for generating a plurality of candidate search terms corresponding to the identification result based on the at least one recommended expression, wherein each candidate search term contains one of the at least one recommended expression.

[0083] According to some embodiments, the sorting subunit includes a subunit for performing sorting based on the degree of relevance between each candidate search item and the user profile.

[0084] According to embodiments of this disclosure, an electronic device is also provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform any of the methods described above.

[0085] According to embodiments of this disclosure, a non-transitory computer-readable storage medium storing computer instructions is also provided, wherein the computer instructions are used to cause a computer to perform any of the methods described above.

[0086] According to embodiments of this disclosure, a computer program product is also provided, including a computer program, wherein the computer program implements any of the methods described above when executed by a processor.

[0087] The collection, storage, use, processing, transmission, provision, and disclosure 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.

[0088] refer to Figure 6The present invention describes a structural block diagram of an electronic device 600 that can serve as a server or client of the present disclosure, which is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can 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 6 As shown, the electronic device 600 includes a computing unit 601, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. The RAM 603 may also store various programs and data required for the operation of the electronic device 600. The computing unit 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0090] Multiple components in electronic device 600 are connected to I / O interface 605, including: input unit 606, output unit 607, storage unit 608, and communication unit 609. Input unit 606 can be any type of device capable of inputting information to electronic device 600. Input unit 606 can receive input digital or character information and generate key signal inputs related to user settings and / or function control of electronic device, and can include, but is not limited to, a mouse, keyboard, touchscreen, trackpad, trackball, joystick, microphone, and / or remote control. Output unit 607 can be any type of device capable of presenting information, and can include, but is not limited to, a monitor, speaker, video / audio output terminal, vibrator, and / or printer. Storage unit 608 can include, but is not limited to, disk and optical disk. Communication unit 609 allows electronic device 600 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks, and can include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers, and / or chipsets, such as Bluetooth™ devices, 802.11 devices, WiFi devices, WiMax devices, cellular communication devices, and / or the like.

[0091] The computing unit 601 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 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 601 performs the various methods and processes described above, such as the recommendation method. For example, in some embodiments, the recommendation method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the recommendation method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the recommendation 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), complex 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. A machine-readable medium 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 performed in parallel, sequentially, or in a different order, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0099] While embodiments or examples of this disclosure have been described with reference to the accompanying drawings, it should be understood that the methods, systems, and devices described above are merely exemplary embodiments or examples, and the scope of the invention is not limited by these embodiments or examples, but only by the granted claims and their equivalents. Various elements in the embodiments or examples may be omitted or replaced by their equivalents. Furthermore, the steps may be performed in a different order than that described in this disclosure. Further, various elements in the embodiments or examples may be combined in various ways. Importantly, as the technology evolves, many elements described herein can be replaced by equivalents that appear after this disclosure.

Claims

1. A recommendation method, comprising: Receive multiple characters from the input search box, wherein the multiple characters include a set of consecutive Chinese characters determined based on multiple letters entered, wherein the multiple letters are determined by the input method application used by the user, or by caching the letters typed by the user in the search application during the process of the user entering consecutive Chinese characters; For a set of consecutive Chinese characters from the plurality of characters, determine the recognition results in at least two different languages ​​corresponding to the set of consecutive Chinese characters, including: The set of consecutive Chinese characters is identified as the corresponding Chinese character recognition result; and Multiple letters used to identify the set of consecutive Chinese characters are determined as corresponding English recognition results; and Based on the recognition results of the at least two different languages, recommended search terms are determined for the multiple characters.

2. The method according to claim 1, wherein, The determination of recommended search terms for the multiple characters based on the recognition results of the at least two different languages ​​includes: For each of the recognition results in the at least two different languages, determine multiple candidate search terms corresponding to that recognition result; The candidate search terms corresponding to each of the at least two identification results are sorted to determine the sorting result; and Based on the sorting results, recommended search terms for the multiple characters are determined.

3. The method according to claim 2, wherein, For each of the recognition results in the at least two different languages, determining the multiple candidate search terms corresponding to that recognition result includes: By performing semantic analysis on the identification result, at least one recommended statement corresponding to the identification result is determined; and Based on the at least one recommended expression, multiple candidate search terms corresponding to the recognition result are generated, wherein each candidate search term contains one of the at least one recommended expression.

4. The method according to claim 2, wherein, The sorting of multiple candidate search terms corresponding to each of the at least two identification results includes: The ranking is performed based on the degree of relevance between each candidate search term and the user profile.

5. A recommended device, comprising: A receiving unit is configured to receive multiple characters in an input search box, wherein the multiple characters include a set of consecutive Chinese characters determined based on multiple letters entered, wherein the multiple letters are determined by the input method application used by the user, or by caching the letters typed by the user in the search application during the process of the user entering consecutive Chinese characters; The first determining unit is configured to, for a set of consecutive Chinese characters from the plurality of characters, determine recognition results in at least two different languages ​​corresponding to the set of consecutive Chinese characters, including: The set of consecutive Chinese characters is identified as the corresponding Chinese character recognition result; and Multiple letters used to identify the set of consecutive Chinese characters are determined as corresponding English recognition results; and The second determining unit is configured to determine recommended search terms for the plurality of characters based on the recognition results of the at least two different languages.

6. The apparatus according to claim 5, wherein, The second determining unit includes: The first determining subunit is configured to determine, for each of the recognition results in the at least two different languages, a plurality of candidate search terms corresponding to that recognition result; A sorting subunit is configured to sort multiple candidate search terms corresponding to each of the at least two identification results to determine a sorting result; and The second determining subunit is configured to determine recommended search terms for the plurality of characters based on the sorting results.

7. The apparatus according to claim 6, wherein, The first determining subunit includes: A subunit used to determine at least one recommended expression corresponding to the recognition result by performing semantic analysis on the recognition result; and A sub-unit for generating multiple candidate search terms corresponding to the recognition result based on the at least one recommendation statement, wherein each candidate search term contains one of the at least one recommendation statements.

8. The apparatus according to claim 6, wherein, The sorting subunit includes: A subunit used to perform the ranking based on the degree of relevance between each candidate search item and the user profile.

9. An electronic device, comprising: At least one processor; as well as A memory that is communicatively connected to the at least one processor; in 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 1-4.

10. 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 1-4.

11. A computer program product comprising a computer program, wherein, The computer program, when executed by a processor, implements the method of any one of claims 1-4.

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