Method, apparatus, and system for processing information, electronic device, medium, and program product

Abstract

The present disclosure relates to the technical field of computers, and relates to a method, apparatus, and system for processing information, an electronic device, a medium, and a program product. The method for processing information comprises: in response to an input operation by a user on a client, acquiring link information corresponding to the input operation, the link information comprising at least one uniform resource locator; determining a tag corresponding to each uniform resource locator, the length of the tag corresponding to each uniform resource locator being smaller than the length of said uniform resource locator; using a machine learning model to process at least one tag corresponding to the at least one uniform resource locator, and obtaining intermediate information corresponding to the input operation, the intermediate information comprising the at least one tag; and sending the intermediate information to the client, so that the client, on the basis of the intermediate information, displays to the user output information corresponding to the input operation. According to the present disclosure, the smoothness of the client displaying the output information to the user can be improved, thereby improving user experience.

Description

Information processing method, device and system, electronic device, medium, program product TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of computer, and particularly relates to an information processing method, device and system, electronic device, medium and program product. BACKGROUND

[0002] In the related art, a uniform resource location (URL) corresponding to an input operation of a user on a client is obtained, and a machine learning model is used to process the uniform resource location to obtain output information corresponding to the input operation, and the output information is sent to the client for display to the user.

[0003] SUMMARY

[0004] This summary is provided to introduce a selection of concepts, which are further described below in the detailed description. This summary is not intended to identify key or essential features of the claimed subject matter, nor is it used to limit the scope of the claimed subject matter's scope.

[0005] According to a first aspect of some embodiments of the present disclosure, an information processing method is provided, comprising:

[0006] In response to an input operation of a user on a client, obtaining link information corresponding to the input operation, the link information comprising at least one uniform resource location;

[0007] Determining a mark corresponding to each uniform resource location, wherein the length of the mark corresponding to each uniform resource location is less than the length of each uniform resource location;

[0008] Using a machine learning model to process at least one mark corresponding to the at least one uniform resource location to obtain intermediate information corresponding to the input operation, wherein the intermediate information comprises the at least one mark;

[0009] Sending the intermediate information to the client so that the client displays output information corresponding to the input operation to the user according to the intermediate information.

[0010] According to a second aspect of some embodiments of the present disclosure, an information processing method is provided, comprising:

[0011] receive, from the server, intermediate information corresponding to the input operation of the user on the client, wherein the intermediate information is obtained by processing at least one token corresponding to at least one uniform resource locator corresponding to the input operation of the user on the client by the server using a machine learning model, and the intermediate information comprises the at least one token, and a length of the token corresponding to each uniform resource locator is less than a length of the uniform resource locator;

[0012] receive, from the server, correspondence information between the at least one uniform resource locator and the at least one token;

[0013] replace each token in the intermediate information with the uniform resource locator corresponding to the token according to the correspondence information, to obtain output information;

[0014] display the output information to the user, so that the user links to the uniform resource locator corresponding to each token through the output information.

[0015] According to a third aspect of some embodiments of the present disclosure, an information processing apparatus is provided, comprising:

[0016] an obtaining module configured to obtain link information corresponding to an input operation of a user on a client, wherein the link information comprises at least one uniform resource locator;

[0017] a determining module configured to determine a token corresponding to each uniform resource locator, wherein a length of the token corresponding to each uniform resource locator is less than a length of the uniform resource locator;

[0018] a processing module configured to process at least one token corresponding to the at least one uniform resource locator using a machine learning model, to obtain intermediate information corresponding to the input operation of the user on the client, wherein the intermediate information comprises the at least one token;

[0019] a sending module configured to send the intermediate information to the client, so that the client displays output information corresponding to the input operation of the user on the client to the user according to the intermediate information.

[0020] According to a fourth aspect of some embodiments of the present disclosure, an information processing apparatus is provided, comprising:

[0021] The first receiving module is configured to receive intermediate information corresponding to an input operation of a user on the client from a server in response to the input operation, wherein the intermediate information is obtained by processing at least one label corresponding to at least one uniform resource locator corresponding to the input operation by the server using a machine learning model, and the intermediate information includes the at least one label, and a length of the label corresponding to each uniform resource locator is less than a length of the uniform resource locator;

[0022] The second receiving module is configured to receive correspondence information between the at least one uniform resource locator and the at least one label from the server.

[0023] The replacing module is configured to replace each label in the intermediate information with a uniform resource locator corresponding to the label according to the correspondence information, to obtain the output information.

[0024] The displaying module is configured to display the output information to the user, so that the user links to the uniform resource locator corresponding to each label through the output information.

[0025] According to a fifth aspect of some embodiments of the present disclosure, an information processing system is provided, comprising:

[0026] The server is configured to perform the information processing method of the first aspect.

[0027] The client is configured to perform the information processing method of the second aspect.

[0028] According to a sixth aspect of some embodiments of the present disclosure, an electronic device is provided, comprising a memory and a processor coupled to the memory, wherein the processor is configured to perform the information processing method of any one of the embodiments of the present disclosure based on instructions stored in the memory.

[0029] According to a seventh aspect of some embodiments of the present disclosure, a computer readable storage medium is provided, which stores a computer program, and the program is executed by a processor to perform the information processing method of any one of the embodiments of the present disclosure.

[0030] According to an eighth aspect of some embodiments of the present disclosure, a computer program product is provided, which, when running on a computer, causes the computer to implement an information processing method.

[0031] Other features, aspects, and advantages of the present disclosure will become apparent from the following detailed description of the exemplary embodiments with reference to the following accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0032] Preferred embodiments of the present disclosure are described herein below with reference to the accompanying drawings. The accompanying drawings, which are included to provide a further understanding based on the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the present disclosure and together with the detailed description serve to explain the present disclosure. It is to be understood that the drawings are solely for purposes of illustration and are not intended to limit the present disclosure in any way. In the drawings:

[0033] FIG. 1 is a flowchart illustrating an information processing method according to some embodiments of the present disclosure;

[0034] FIG. 2A is a flowchart illustrating an information processing method according to other embodiments of the present disclosure;

[0035] FIG. 2B is a flowchart illustrating an information processing method according to yet other embodiments of the present disclosure;

[0036] FIG. 2C is a flowchart illustrating an information processing method according to yet other embodiments of the present disclosure;

[0037] FIG. 3 is a flowchart illustrating an information processing method according to yet other embodiments of the present disclosure;

[0038] FIG. 4 is a flowchart illustrating an information processing method according to yet other embodiments of the present disclosure;

[0039] FIG. 5 is a flowchart illustrating an information processing method according to yet other embodiments of the present disclosure;

[0040] FIG. 6 is a flowchart illustrating an information processing method according to yet other embodiments of the present disclosure;

[0041] FIG. 7 is a block diagram illustrating an information processing apparatus according to some embodiments of the present disclosure;

[0042] FIG. 8 is a block diagram illustrating an information processing apparatus according to other embodiments of the present disclosure;

[0043] FIG. 9 is a block diagram illustrating an information processing system according to some embodiments of the present disclosure;

[0044] FIG. 10 is a block diagram illustrating an electronic device according to some embodiments of the present disclosure;

[0045] FIG. 11 is a block diagram illustrating an electronic device according to other embodiments of the present disclosure.

[0046] It is to be understood that the sizes of the respective portions shown in the drawings are not necessarily drawn to scale. Identical or similar components shown in the drawings are denoted by the same or similar reference numerals. Thus, once a component is defined in one drawing, it can not be discussed further in subsequent drawings. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the present disclosure will be described clearly and completely below in combination with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only some of the embodiments of the present disclosure, but not all the embodiments. The description of the embodiments below is actually only illustrative, and is by no means any limitation on the present disclosure and its application or use. It should be understood that the present disclosure can be implemented in various forms, and should not be interpreted as being limited to the embodiments set forth herein.

[0048] It should be understood that each step described in the method embodiments of the present disclosure can be performed in different order and / or in parallel. In addition, the method embodiments can include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect. Unless otherwise specified, the relative arrangement of the components and steps, numerical expressions, and numerical values set forth in these embodiments should be interpreted as merely illustrative, not limiting the scope of the present disclosure.

[0049] The term "comprise" and variations of the term, such as "comprising", "includes", "including" and "contains", "containing", used in the present disclosure means an open term that includes at least the recited elements, but does not exclude other elements. In addition, the term "comprise" and variations of the term used in the present disclosure means an open term that includes at least the recited elements, but does not exclude other elements, i.e. "comprise but not limited to". Therefore, comprising and containing are synonymous. The term "based on" means "at least partially based on".

[0050] Throughout the specification, the term "one embodiment", "some embodiments" or "embodiments" means that the specific features, structures or characteristics described in connection with the embodiment are included in at least one embodiment of the present disclosure. For example, the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; and the term "some embodiments" means "at least some embodiments". Moreover, the appearance of the phrase "in one embodiment", "in some embodiments" or "in embodiments" at various places in the specification does not necessarily all refer to the same embodiment, but can refer to different embodiments.

[0051] It should be noted that the "first", "second", and the like concepts mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not intended to limit the order or interdependence of the functions performed by these devices, modules or units. Unless otherwise specified, the "first", "second", and the like concepts are not intended to imply a given order or any other manner of given order in time, space, ranking or any other manner.

[0052] It should be noted that the modification of "one", "multiple" mentioned in the present disclosure is illustrative but not restrictive, and those skilled in the art should understand that "one or more" should be understood unless otherwise explicitly indicated in the context.

[0053] The names of the messages or information exchanged between the plurality of devices in the embodiments of the present disclosure are only for illustrative purposes, and are not used to limit the scope of the messages or information.

[0054] The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings, but the present disclosure is not limited to these specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes can not be described in some embodiments. In addition, in one or more embodiments, specific features, structures or characteristics can be combined by any suitable means from the present disclosure which is clear to those skilled in the art.

[0055] In the related art, the machine learning model directly processes the uniform resource locator, and the same uniform resource locator is usually a long text, which will cause the machine learning model to be slow in processing the uniform resource locator to generate output information, and further cause the client to easily occur in the process of showing the output information to the user. Stutter, poor user experience.

[0056] The present disclosure provides a technical solution that can improve the smoothness of the client showing the output information to the user and improve the user experience.

[0057] FIG. 1 is a flow diagram illustrating an information processing method according to some embodiments of the present disclosure. The information processing method of this embodiment can be executed on a server.

[0058] As shown in FIG. 1, the information processing method includes: step S110, in response to a user's input operation on a client, obtaining link information corresponding to the input operation, the link information including at least one uniform resource locator; step S120, determining a mark corresponding to each uniform resource locator, wherein the length of the mark corresponding to each uniform resource locator is less than the length of each uniform resource locator; step S130, using a machine learning model to process at least one mark corresponding to the at least one uniform resource locator to obtain intermediate information corresponding to the input operation, wherein the intermediate information includes the at least one mark; and step S140, sending the intermediate information to the client so that the client displays output information corresponding to the input operation to the user according to the intermediate information. The mark corresponding to each uniform resource locator can also be referred to as a short mark.

[0059] In the above embodiments, since the processing procedure of the machine learning model is usually complex, mapping the uniform resource locator to the token with a length less than that of the uniform resource locator can reduce the complexity of the processing of the machine learning model, improve the processing efficiency of the machine learning model, and further improve the fluency of the client in presenting the output information to the user and the user experience.

[0060] The information processing method in other embodiments of the present disclosure will be described in detail below in combination with FIGS. 2A-5.

[0061] FIG. 2A is a flow diagram illustrating an information processing method according to some embodiments of the present disclosure. FIG. 2A differs from FIG. 1 in that steps S131A-S132A in FIG. 2A are an implementation of step S130 in FIG. 1. Only the differences between FIG. 2A and FIG. 1 will be described below, and the same parts will not be described again.

[0062] As shown in FIG. 2A, in step S131A, the at least one token is sent to the machine learning model.

[0063] In step S132A, the intermediate information obtained by processing the at least one token by the machine learning model is received.

[0064] The machine learning model is, for example, a large language model (LLM) or other natural language processing (NLP) model.

[0065] FIG. 2B is a flow diagram illustrating an information processing method according to some other embodiments of the present disclosure. FIG. 2B differs from FIG. 1 in that step S131B in FIG. 2B is an implementation of step S130 in FIG. 1. Only the differences between FIG. 2B and FIG. 1 will be described below, and the same parts will not be described again.

[0066] The link information further includes link text corresponding to each uniform resource locator. As shown in FIG. 2B, in step S131B, the at least one token and the link text corresponding to each uniform resource locator are processed by the machine learning model to obtain the intermediate information, wherein the intermediate information further includes the link text corresponding to each uniform resource locator, the link text is the text presented to the user by the client, and is used by the user to link to the uniform resource locator corresponding to the link text.

[0067] The link text corresponding to each uniform resource locator is the text shown to the user for the user to click, and in response to the user clicking the text, the user can access the uniform resource locator corresponding to the text. Generally, the link text can reflect the content of the target page corresponding to the uniform resource locator linked by the link text. Showing the link text to the user can further improve the user experience.

[0068] FIG. 2C is a flow diagram illustrating an information processing method according to yet some embodiments of the present disclosure. FIG. 2C differs from FIG. 1 in that steps S131C-S134C of FIG. 2C are an implementation of step S130 in FIG. 1. Only the differences between FIG. 2C and FIG. 1 will be described below, and the same parts will not be described again.

[0069] As shown in FIG. 2C, in step S131C, in response to the machine learning model requesting to access the uniform resource locator corresponding to any one of the tags, the any one of the tags is replaced by the uniform resource locator corresponding to the any one of the tags. In step S132C, the uniform resource locator corresponding to the any one of the tags is accessed. In step S133C, the relevant content in the accessed uniform resource locator is sent to the machine learning model for the machine learning model to obtain the intermediate information. In step S134C, the intermediate information obtained by the machine learning model processing the at least one tag and the relevant content in the accessed uniform resource locator is received.

[0070] In the above embodiments, the machine learning model can access the relevant content in the uniform resource locator as needed, further enriching the intermediate information generated by the machine learning model, so that the user of the client can more easily distinguish the differences between the contents of the target pages linked by different uniform resource locators, further improving the user experience.

[0071] FIG. 3 is a flow diagram illustrating an information processing method according to yet some embodiments of the present disclosure. FIG. 3 differs from FIG. 1 in that FIG. 3 shows other steps S150 of the information processing method according to yet some embodiments. Only the differences between FIG. 3 and FIG. 1 will be described below, and the same parts will not be described again.

[0072] As shown in FIG. 3, in step S150, the correspondence information between the at least one uniform resource locator and the at least one tag is sent to the client, where the correspondence information is used by the client to replace each tag in the intermediate information with the uniform resource locator corresponding to the each tag to obtain the output information. The correspondence information between the at least one uniform resource locator and the at least one tag can be represented in any reasonable form, for example, including but not limited to forms such as tables, icons, or mappings.

[0073] Step S150 in FIG. 3 is performed after step S120. The step S150 of the present disclosure is not limited to a strict execution sequence between step S130 and step S140, that is, step S150 can be performed before step S130, between step S130 and step S140, after step S140, or simultaneously with step S130 and / or step S140.

[0074] The information processing method in some embodiments of the present disclosure will be described from another perspective based on FIG. 4.

[0075] FIG. 4 is a flow diagram illustrating an information processing method according to yet some embodiments of the present disclosure. The information processing method of this embodiment can be performed on a client.

[0076] As shown in FIG. 4, the information processing method includes: step S240, receiving intermediate information corresponding to an input operation of a user on a client from a server in response to the input operation of the user on the client, wherein the intermediate information is obtained by processing at least one label corresponding to at least one uniform resource locator corresponding to the input operation of the user on the client by a machine learning model of the server, and the intermediate information includes the at least one label, and the length of the label corresponding to each uniform resource locator is less than the length of the uniform resource locator; step S250, receiving correspondence information between the at least one uniform resource locator and the at least one label from the server; step S260, replacing each label in the intermediate information with a uniform resource locator corresponding to the label according to the correspondence information to obtain output information; and step S270, displaying the output information to the user so that the user links to the uniform resource locator corresponding to each label through the output information.

[0077] FIG. 5 is a flow diagram illustrating an information processing method according to yet some embodiments of the present disclosure. FIG. 5 is different from FIG. 4 in that step S271 of FIG. 5 is an implementation of step S270 of FIG. 4. Only the differences between FIG. 5 and FIG. 4 will be described below, and the same parts will not be described again.

[0078] The intermediate information includes link text corresponding to each uniform resource locator. As shown in FIG. 5, in step S271, the link text corresponding to the at least one uniform resource locator is displayed to the user, wherein the link text is used by the user to link to the uniform resource locator corresponding to the link text.

[0079] The link text corresponding to each uniform resource locator is the text shown to the user for the user to click, and in response to the user clicking the text, the user can access the uniform resource locator corresponding to the text. Generally, the link text can reflect the content of the target page corresponding to the uniform resource locator linked by the link text. Showing the link text to the user can further improve the user experience.

[0080] In some embodiments, the information processing method of the present disclosure can further include, in response to the user clicking any link text, displaying the content in the uniform resource locator corresponding to the any link text to the user.

[0081] In some embodiments, the mark in any of the preceding embodiments is a short mark and has a length less than a length threshold, and the length threshold is less than the length of the uniform resource locator corresponding to the mark.

[0082] In some embodiments, the machine learning model in any of the preceding embodiments can be deployed on the server side or on other devices or equipment other than the server.

[0083] In some embodiments, the link information corresponding to the input operation of the user can be obtained by calling a search plugin. The link text in the preceding link information is, for example, a Markdown link text.

[0084] The interaction process between the client, the server and the machine learning model will be described more intuitively below with reference to FIG. 6.

[0085] FIG. 6 is a flow diagram illustrating an information processing method according to yet another embodiment of the present disclosure.

[0086] As shown in FIG. 6, the information processing method includes steps S300-S370.

[0087] In step S300, the client sends the input information of the user to the server. The input information instructs the server to obtain the uniform resource locator. The input information can be information parsed by the client from the input operation of the user on the client, or can be information directly input by the user. The input operation of the user can be, for example, a text input operation or a gesture input operation, which is not limited by the present disclosure.

[0088] Taking a model question and answer scenario as an example, the user opens the application program of the client, enters the dialogue page with the intelligent agent, and inputs the text information "Please provide a website link for learning English" indicating the demand or question in the dialogue page. The information input by the user in the dialogue page is used to instruct the server to obtain the uniform resource locator for learning English.

[0089] In step S310, the server invokes the search plug-in to obtain link information corresponding to the input information through searching, the link information including at least one uniform resource locator. In some embodiments, the link information can also include link text corresponding to each uniform resource locator. The link text can be, for example, Markdown link text.

[0090] Taking the model question and answer scenario as an example, the server invokes the pre-deployed search plug-in to obtain link information corresponding to the input information “Please provide a website link for learning English” input by the user on the dialogue page. The link information includes at least one uniform resource locator of a website for learning English. For example, the link information can also include link text corresponding to the uniform resource locator of each website for learning English. The link text can be, for example, a title named for the website, including but not limited to “word learning website”, “grammar learning website”, etc.

[0091] In step S320, the server maps each uniform resource locator into a token. The length of the token is less than the length of the uniform resource locator corresponding to the token. For example, the token is a short token and its length is less than a length threshold, and the length threshold is less than the length of the uniform resource locator corresponding to the token.

[0092] Taking the model question and answer scenario as an example, the server maps the uniform resource locator of a website for learning English into a token u1, and maps the uniform resource locator of another website for learning English into a token u2. Here, numbers are used to distinguish the uniform resource locators of different websites, which is only an example and does not constitute a specific limitation to the present disclosure.

[0093] In step S331, the server sends at least one token mapped from at least one uniform resource locator to the machine learning model. The machine learning model is deployed on the server in FIG. 6, which is only an example. In some embodiments, the machine learning model can also be deployed on other devices or apparatuses other than the server, and the present disclosure does not specifically limit the deployment location of the machine learning model. In some embodiments, in the case where the link information includes link text, the server also sends the link text corresponding to each uniform resource locator to the machine learning model. The link text can be, for example, Markdown link text.

[0094] Taking the model question and answer scenario as an example, the server sends the tokens u1 and u2 mapped from the uniform resource locators of the websites for learning English and their corresponding link texts “word learning website” and “grammar learning website” to the machine learning model. The token u1 corresponds to the link text “word learning website”, and the token u2 corresponds to the link text “grammar learning website”.

[0095] In step S332', the machine learning model processes the at least one mark to obtain intermediate information corresponding to the input information, and the intermediate information includes the at least one mark. In some embodiments, when the link information includes link text, the machine learning model processes the at least one mark and the at least one link text corresponding to the at least one uniform resource locator to obtain the intermediate information, and the intermediate information includes the at least one mark and the at least one link text.

[0096] Taking the model question and answer scenario as an example, the machine learning model learns the marks $u1$, $u2$ and the link texts "word learning website" and "grammar learning website" corresponding thereto respectively, and obtains intermediate information corresponding to the input information "Please provide the website link for learning English." For example, the intermediate information is a link in Markdown syntax, that is: "[word learning website] ($u1$) provides a special word learning method, which can help users learn more words in a short time. \n[grammar learning website] ($u2$) is a website that can help users learn many common grammars." "\n" is a line break.

[0097] In step S332, the server receives the intermediate information from the machine learning model. Taking the model question and answer scenario as an example, the server receives the intermediate information from the machine learning model, that is: "[word learning website] ($u1$) provides a special word learning method, which can help users learn more words in a short time. \n[grammar learning website] ($u2$) is a website that can help users learn many common grammars."

[0098] In step S340, the server sends the intermediate information to the client. Taking the model question and answer scenario as an example, the server sends the intermediate information "[word learning website] ($u1$) provides a special word learning method, which can help users learn more words in a short time. \n[grammar learning website] ($u2$) is a website that can help users learn many common grammars." to the client.

[0099] In step S350, the server sends the correspondence between the at least one uniform resource locator and the at least one mark to the client. Taking the model question and answer scenario as an example, the server sends the correspondence between the uniform resource locator and the aforementioned marks $u1$, $u2$ to the client.

[0100] In step S360, the client replaces each mark in the intermediate information with a uniform resource locator corresponding to the mark to obtain output information corresponding to the input information. Taking the model question and answer scenario as an example, the client replaces the mark u1 in the intermediate information “[word learning website] ($u1$) provides a special word learning method, which can help users learn more words in a short period of time.\n[grammar learning website] ($u2$) is a website that can help users learn many common grammars.” with a uniform resource locator corresponding to u1, and replaces the mark u2 with a uniform resource locator corresponding to u2 to obtain the output information “[word learning website] (first uniform resource locator) provides a special word learning method, which can help users learn more words in a short period of time.\n[grammar learning website] (second uniform resource locator) is a website that can help users learn many common grammars.”. Here, the first uniform resource locator and the second uniform resource locator are only used to identify different uniform resource locators, and actually are complete website addresses corresponding to the word learning website and the grammar learning website respectively.

[0101] In step S370, the client shows the output information to the user. In some embodiments, in the case where the link information includes link text, the client shows the user link text corresponding to each uniform resource locator, and links the user to the uniform resource locator corresponding to any link text in response to the user clicking the link text.

[0102] Taking the model question and answer scenario as an example, the client shows the output information to the user, that is, the display content of the user's dialogue page interface is “word learning website provides a special word learning method, which can help users learn more words in a short period of time.\ngrammar learning website is a website that can help users learn many common grammars.”, wherein the word learning website and the grammar learning website are hyperlinks, and the user can access the specific content of the two websites by clicking the “word learning website” and “grammar learning website” in the dialogue page, that is, jump to the corresponding website page to display the content of the website page to the user.

[0103] The above is an information processing method provided by some embodiments of the present disclosure. The information processing apparatus in some embodiments of the present disclosure will be described below with reference to FIGS. 7-8.

[0104] FIG. 7 is a block diagram illustrating an information processing apparatus according to some embodiments of the present disclosure.

[0105] As shown in FIG. 7, the information processing apparatus 71 includes: an obtaining module 711 configured to, in response to an input operation of a user on a client, obtain link information corresponding to the input operation, the link information including at least one uniform resource locator; a determining module 712 configured to determine a mark corresponding to each uniform resource locator, wherein the length of the mark corresponding to each uniform resource locator is less than the length of the uniform resource locator; a processing module 713 configured to, using a machine learning model, process at least one mark corresponding to the at least one uniform resource locator to obtain intermediate information corresponding to the input operation, wherein the intermediate information includes the at least one mark; and a sending module 714 configured to send the intermediate information to the client, so that the client displays output information corresponding to the input operation to the user according to the intermediate information.

[0106] The information processing apparatus 71 can be configured to perform steps S110-S140 of FIG. 1. In some embodiments, the information processing apparatus 71 is further configured to perform any steps of FIGS. 2A, 2B, 2C, and 3. In some embodiments, the information processing apparatus 72 can also be configured to perform any steps performed by the server as shown in FIG. 6.

[0107] FIG. 8 is a block diagram illustrating an information processing apparatus according to some embodiments of the present disclosure.

[0108] As shown in FIG. 8, the information processing apparatus 82 includes: a first receiving module 824 configured to, in response to an input operation of a user on a client, receive intermediate information corresponding to the input operation from a server, wherein the intermediate information is obtained by the server using a machine learning model to process at least one mark corresponding to at least one uniform resource locator corresponding to the input operation, the intermediate information including the at least one mark, and the length of the mark corresponding to each uniform resource locator is less than the length of the uniform resource locator; a second receiving module 825 configured to receive, from the server, correspondence information of the at least one uniform resource locator and the at least one mark; a replacing module 826 configured to replace each mark in the intermediate information with a uniform resource locator corresponding to the mark according to the correspondence information to obtain output information; and a displaying module 827 configured to display the output information to the user, so that the user links to the uniform resource locator corresponding to each mark through the output information.

[0109] The information processing apparatus 82 can be configured to perform steps S240-S270 of FIG. 4. In some embodiments, the information processing apparatus 82 can be configured to perform any steps of FIG. 5. In some embodiments, the information processing apparatus 82 can also be configured to perform any steps performed by the client as shown in FIG. 6.

[0110] It should be noted that the above-described various modules are logical modules according to the specific functions implemented by them, and are not intended to limit the specific implementation manners, for example, they can be implemented in software, hardware, or a combination of software and hardware. In actual implementation, the above-described various modules can be implemented as independent physical entities, or can also be implemented by a single entity (for example, a processor (CPU or DSP, etc.), an integrated circuit, etc.). In addition, the above-described various modules are indicated by dashed lines in the drawings, indicating that these modules can not actually exist, and the operations / functions implemented by them can be implemented by the processing circuit itself.

[0111] The above is an information processing apparatus in some embodiments of the present disclosure. An information processing system in some embodiments of the present disclosure will be described below in conjunction with FIG. 9.

[0112] FIG. 9 is a block diagram illustrating an information processing system according to some embodiments of the present disclosure.

[0113] As shown in FIG. 9, the information processing system 9 includes a server 91 and a client 92. The server 91 is configured to perform steps S110-S140 as shown in FIG. 1. The client 92 is configured to perform steps S240-S270 as shown in FIG. 4.

[0114] In some embodiments, the server 91 is further configured to perform any steps of FIGS. 2A, 2B, 2C, and 3 or any steps performed by the server in FIG. 6.

[0115] In some embodiments, the client 92 is further configured to perform any steps of FIG. 5 or any steps performed by the client in FIG. 6.

[0116] FIG. 10 is a block diagram illustrating an electronic device according to some embodiments of the present disclosure.

[0117] As shown in FIG. 10, the electronic device 10 includes a memory 101 and a processor 102 coupled to the memory 101, the processor 102 being configured to perform the information processing method according to any of the preceding embodiments based on instructions stored in the memory 101.

[0118] The memory 101 is configured to store one or more computer-readable instructions. The memory 101 can include any combination of various types of computer-readable storage media, such as volatile memory and / or non-volatile memory, including but not limited to random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), read-only memory (ROM), flash memory. The memory 101 may, for example, store an operating system, application programs, a boot loader, a database, and other programs, and can also store various application programs and various data.

[0119] The processor 102 is configured to run the computer-readable instructions to implement the information processing method of any of the preceding embodiments. For specific implementation of each step of the information processing method, refer to the embodiments described above, and the repeated parts will not be described here.

[0120] The processor 102 and the memory 101 can communicate with each other directly or indirectly. For example, the processor 102 and the memory 101 can communicate through a network. The network can include a wireless network, a wired network, and / or any combination of a wireless network and a wired network. The processor 102 and the memory 101 can also communicate with each other through a system bus, and the present disclosure does not limit the implementation.

[0121] It should be noted that the components of the electronic device 10 shown in FIG. 10 are only exemplary and not limiting, and the electronic device 10 can also have other components according to actual application needs. The processor 102 can communicate with other components of the electronic device 10 to perform the desired functions.

[0122] The electronic device can be implemented by software, firmware, and / or hardware, and can be integrated into an electronic device installed with a related application program.

[0123] FIG. 11 shows a block diagram of an electronic device according to some other embodiments of the present disclosure.

[0124] The electronic device 11 shown in FIG. 11 can be a computer system with a special hardware structure, which can perform corresponding functions when installed with a related application program.

[0125] The electronic device includes but is not limited to mobile terminals such as smartphones, notebook computers, personal digital assistants (PDAs), tablet computers (Tablet PCs), PMPs (portable multimedia players), vehicle terminals (such as vehicle navigation terminals), wearable devices, and the like, and fixed terminals such as digital televisions, desktop computers, and the like.

[0126] As shown in FIG. 11, a central processing unit (CPU) 111 executes various processes in accordance with a program stored in a read only memory (ROM) 112 or a program loaded from a storage section 118 to a random access memory (RAM) 113. In the RAM 113, data required when the CPU 111 executes various processes and the like is stored as necessary. The CPU is merely exemplary, and can be other types of processors, such as the various processors described above. The ROM 112, the RAM 113, and the storage section 118 can be various forms of computer readable storage media. Note that although the ROM 112, the RAM 113, and the storage section 118 are shown separately in FIG. 11, one or more of them can be combined, or located in the same or different memory or storage modules.

[0127] The CPU 111, the ROM 112, and the RAM 113 are connected to each other via a bus 114. An input / output interface 115 is also connected to the bus 114.

[0128] The following components are connected to the input / output interface 115: an input section 116 including a touch panel, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, and the like; an output section 117 including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), a speaker, a vibrator, and the like; a storage section 118 including a hard disk, a magnetic tape, and the like; and a communication section 119 including a network interface card such as a LAN card, a modem, and the like. The communication section 119 allows communication processing to be performed via a network such as the Internet. It is easily understood that although the various devices or modules in the electronic device 11 are shown in FIG. 11 as communicating via the bus 114, they can also communicate through a network or other means, where the network can include a wireless network, a wired network, and / or any combination of a wireless network and a wired network.

[0129] A drive 1110 is also connected to the input / output interface 115 as necessary. A removable medium 1111 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is attached to the drive 1110 as necessary, so that a computer program read therefrom is installed in the storage section 118 as necessary.

[0130] In the case where the above series of processes are implemented by software, the program constituting the software can be installed from a network such as the Internet or a storage medium such as the removable medium 1111.

[0131] According to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product that, when run on a computer, causes the computer to implement the information processing method described in any of the preceding embodiments. The computer program product includes a computer program carried on a computer-readable medium, which contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network by the communication section 119, or installed from the storage section 118, or installed from the ROM 112. When the computer program is executed by the CPU 111, the information processing method of the embodiment of the present disclosure is executed.

[0132] Note that, in the context of the present disclosure, the computer-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0133] The computer-readable medium can be a computer-readable storage medium, or a computer-readable signal medium, or any combination of the two.

[0134] The computer-readable storage medium includes, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium stores a computer program that, when executed by a processor, implements the information processing method described in any of the preceding embodiments.

[0135] The computer readable signal medium can include a computer readable storage medium that is one of tangible and non-transitory.

[0136] The computer readable medium described above can be included in the electronic device described above; or can exist separately from the electronic device and be not assembled in the electronic device.

[0137] In some embodiments, a computer program product is also provided, which, when running on a computer, enables the computer to implement the information processing method described in any of the above embodiments.

[0138] In some embodiments, a computer program is also provided, which includes instructions, which, when executed by a processor, enable the processor to perform the information processing method of any of the above embodiments. For example, the instructions can be embodied as computer program codes.

[0139] Based on the method, device or equipment in any of the above embodiments, the present disclosure performs a control experiment on the Short URL and Domain-based Short URL. The control group adopts the related technology, and the experimental group corresponding to the Short URL and Domain-based Short URL respectively adopts the method, device or equipment in any of the embodiments of the present disclosure. The experiment proves that the experimental group shows the process of outputting information to the user more smoothly, and is not prone to freezing.

[0140] Computer program code for carrying out operations of the present disclosure can be written in any one or more of a variety of programming languages or combinations of languages including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0141] The computer program instructions can also be loaded onto a computer or other programmable information processing apparatus to cause a series of operations to be performed on the computer or other programmable information processing apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable information processing apparatus implement the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0142] The functions described above can be implemented in at least part by one or more hardware logic components. For example, and without limitation, illustrative hardware logic components that can be used include Field-programmable Gate Arrays (FPGAs), Program-specific Integrated Circuits (ASICs), Program-specific Standard Products (ASSPs), System-on-a-chip systems (SOCs), Complex Programmable Logic Devices (CPLDs), etc.

[0143] While certain aspects of the present disclosure have been described with reference to one or more particular embodiments thereof, those skilled in the art will understand that many alternative embodiments can be made therefrom. In general, embodiments of the present disclosure are applicable to any suitable electronic device, system, or architecture. In addition, unless otherwise indicated, the functions performed by the various components described herein can be implemented using electronic components, software, firmware, or any suitable combination thereof. In addition, it will be understood that various hardware and software components, or modules, of the embodiments described herein can be combined, divided, recombined, or otherwise rearranged, unless otherwise indicated.

Claims

1. An information processing method, comprising: in response to a user's input operation on a client, obtaining link information corresponding to the input operation, the link information comprising at least one uniform resource locator; determining a token corresponding to each uniform resource locator, wherein the length of the token corresponding to each uniform resource locator is less than the length of the uniform resource locator; processing at least one token corresponding to the at least one uniform resource locator by using a machine learning model to obtain intermediate information corresponding to the input operation, wherein the intermediate information comprises the at least one token; sending the intermediate information to the client so that the client displays output information corresponding to the input operation to the user according to the intermediate information.

2. The information processing method according to claim 1, wherein processing at least one token corresponding to the at least one uniform resource locator by using a machine learning model to obtain intermediate information corresponding to the input operation comprises: sending the at least one token to the machine learning model; receiving the intermediate information obtained by the machine learning model processing the at least one token. 3.The information processing method of claim 1 or 2, further comprising: sending correspondence information of the at least one uniform resource locator and the at least one token to the client, wherein the correspondence information is used by the client to replace each token in the intermediate information with a uniform resource locator corresponding to the token to obtain the output information.

4. The information processing method according to claim 1 or 2, wherein The link information further comprises link text corresponding to each uniform resource locator, and processing at least one token corresponding to the at least one uniform resource locator by using a machine learning model to obtain intermediate information corresponding to the input operation comprises: processing the at least one token and the link text corresponding to each uniform resource locator by using a machine learning model to obtain the intermediate information, wherein the intermediate information further comprises the link text corresponding to each uniform resource locator, the link text being text displayed to the user by the client and being used by the user to link to the uniform resource locator corresponding to the link text. Processing at least one token corresponding to the at least one uniform resource locator by using a machine learning model to obtain intermediate information corresponding to the input operation comprises:

5. The information processing method according to claim 2, wherein in response to the machine learning model requesting to access a uniform resource locator corresponding to any token, replacing the any token with the uniform resource locator corresponding to the any token; accessing the uniform resource locator corresponding to the any token; sending relevant content in the accessed uniform resource locator to the machine learning model for the machine learning model to obtain the intermediate information; receiving the intermediate information obtained by the machine learning model processing the at least one token and the relevant content in the accessed uniform resource locator. 6.An information processing method, comprising: ​ In response to an input operation of a user on a client, intermediate information corresponding to the input operation is received from a server, wherein the intermediate information is obtained by processing at least one token corresponding to at least one uniform resource locator corresponding to the input operation by a machine learning model, and the intermediate information includes the at least one token, and a length of the token corresponding to each uniform resource locator is less than a length of the uniform resource locator; Correspondence information between the at least one uniform resource locator and the at least one token is received from the server; According to the correspondence information, each token in the intermediate information is replaced by a uniform resource locator corresponding to the token to obtain output information; The output information is displayed to the user so that the user links to the uniform resource locator corresponding to each token through the output information.

7. The information processing method according to claim 6, wherein The intermediate information includes link text corresponding to each uniform resource locator, and the output information is displayed to the user, including: The link text corresponding to the at least one uniform resource locator is displayed to the user, wherein the link text is used by the user to link to the uniform resource locator corresponding to the link text.

8. The information processing method of claim 7, further comprising: In response to the user clicking any link text, content in the uniform resource locator corresponding to the any link text is displayed to the user.

9. An information processing apparatus, comprising: An acquisition module configured to, in response to an input operation of a user on a client, acquire link information corresponding to the input operation, the link information including at least one uniform resource locator; A determination module configured to determine a token corresponding to each uniform resource locator, wherein a length of the token corresponding to each uniform resource locator is less than a length of the uniform resource locator; A processing module configured to process at least one token corresponding to the at least one uniform resource locator by a machine learning model to obtain intermediate information corresponding to the input operation, wherein the intermediate information includes the at least one token; A sending module configured to send the intermediate information to the client so that the client displays output information corresponding to the input operation to the user according to the intermediate information.

10. An information processing apparatus, comprising: A first receiving module configured to, in response to an input operation of a user on a client, receive intermediate information corresponding to the input operation from a server, wherein the intermediate information is obtained by processing at least one token corresponding to at least one uniform resource locator corresponding to the input operation by a machine learning model by the server, and the intermediate information includes the at least one token, and a length of the token corresponding to each uniform resource locator is less than a length of the uniform resource locator; a second receiving module configured to receive, from the server, the correspondence information of the at least one uniform resource locator and the at least one mark; a replacing module configured to replace each mark in the intermediate information with a uniform resource locator corresponding to the mark according to the correspondence information, to obtain the output information; a displaying module configured to display the output information to the user, so that the user links to the uniform resource locator corresponding to each mark through the output information. 11.An information processing system, comprising: a server configured to perform the information processing method according to any one of claims 1-5; a client configured to perform the information processing method according to any one of claims 6-8. 12.An electronic device, comprising: a memory; and a processor coupled to the memory, the processor configured to perform the information processing method according to any one of claims 1-8 based on instructions stored in the memory. 13.A computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the information processing method according to any one of claims 1-8. 14.A computer program product which, when running on a computer, causes the computer to perform the information processing method according to any one of claims 1-8. ​

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