Information processing method and apparatus, and electronic device, storage medium and program product

Abstract

The present disclosure relates to the technical field of computers, and relates to an information processing method and apparatus, and an electronic device, a storage medium and a program product. The information processing method in the present disclosure comprises: on the basis of information posted by a first user, determining whether there is factual error information in the posted information; in response to there being factual error information in the posted information, generating error correction information, wherein the error correction information comprises correct information corresponding to the factual error information; and in a comment area corresponding to the posted information, displaying the error correction information.

Description

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

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

[0002] The emergence of Internet technology has greatly changed the way information is disseminated. With the emergence of various social media, there are more and more ways for users to publish information.

[0003] In the vast amount of Internet information, there are a large number of factual error information, which can mislead users who see these factual error information and have a wide range of influence.

[0004] SUMMARY

[0005] 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 intended to be used in limiting the scope of the claimed subject matter.

[0006] According to some embodiments of the present disclosure, an information processing method is provided, comprising: determining whether there is factual error information in the published information according to the information published by a first user; in response to the presence of factual error information in the published information, generating correction information, wherein the correction information includes correct information corresponding to the factual error information; and displaying the correction information in a comment area corresponding to the published information.

[0007] According to some other embodiments of the present disclosure, an information processing device is provided, comprising: a determination module configured to determine whether there is factual error information in the published information according to the information published by a first user; a generation module configured to generate correction information in response to the presence of factual error information in the published information, wherein the correction information includes correct information corresponding to the factual error information; and a display module configured to display the correction information in a comment area corresponding to the published information.

[0008] According to still some other embodiments of the present disclosure, an electronic device is provided, comprising: a processor; and a memory coupled to the processor for storing instructions, the instructions being executed by the processor to cause the processor to perform the information processing method of any one of the embodiments of the present disclosure.

[0009] According to still some other embodiments of the present disclosure, a computer-readable storage medium is provided, having stored thereon a computer program, the program being executed by a processor to perform the information processing method of any one of the embodiments of the present disclosure.

[0010] According to yet some embodiments of the present disclosure, there is provided a computer program product comprising instructions which, when executed by a processor, implement the information processing method of any of the embodiments of the present disclosure.

[0011] According to still some embodiments of the present disclosure, there is provided a computer program comprising instructions which, when executed by a processor, implement the information processing method of any of the embodiments of the present disclosure.

[0012] Other features, aspects, and advantages of the present disclosure will become apparent from the following detailed description of the exemplary embodiments of the present disclosure with reference made to the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0013] The preferred embodiments of the present disclosure will be described herein below with reference to the accompanying drawings. The accompanying drawings are used in the providing of further understanding of the present disclosure, and together with the specific description below form a part of the specification, and are used to explain the present disclosure. It should be understood that the accompanying drawings are only some embodiments of the present disclosure, and do not constitute a limitation on the present disclosure. In the drawings:

[0014] FIG. 1 shows a flowchart of an information processing method according to some embodiments of the present disclosure;

[0015] FIGS. 2A-2E show schematic diagrams of interfaces according to some embodiments of the present disclosure;

[0016] FIGS. 3A-3C show schematic diagrams of interfaces according to some other embodiments of the present disclosure;

[0017] FIG. 4 shows a flowchart of an information processing method according to some other embodiments of the present disclosure;

[0018] FIG. 5 shows a structural schematic diagram of an information processing apparatus according to some embodiments of the present disclosure;

[0019] FIG. 6 shows a structural schematic diagram of an electronic device according to some embodiments of the present disclosure;

[0020] FIG. 7 shows a structural schematic diagram of a computer system according to some embodiments of the present disclosure.

[0021] It should be understood that the sizes of the various portions shown in the drawings are not necessarily drawn to scale. Identical or similar reference numerals are used to represent identical or similar components throughout the various figures. Thus, once a component is defined in one figure, it can not be discussed further in subsequent figures. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present disclosure will be clearly and completely described in combination with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, and 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.

[0023] It should be understood that each of the steps recited in the method embodiments of the present disclosure can be performed in different orders 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 set forth in these embodiments, numerical expressions, and numerical values should be interpreted as merely illustrative, not limiting the scope of the present disclosure.

[0024] The term "comprise" and variations of the term, such as "comprising," "comprises," and "comprised of" as used in the present disclosure are open-ended, meaning that "comprising" includes the elements listed thereafter, but not excluding others. In addition, the term "contain" and variations of the term, such as "containing," "contains," and "contained of" as used in the present disclosure are open-ended, meaning that "containing" includes the elements listed thereafter, but not excluding others. Thus, comprising and containing are synonymous. The term "based on" means "based, at least in part, on."

[0025] Reference throughout this specification to "an embodiment," "some embodiments," or "embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the application. The appearance of the phrases "in one embodiment," "in some embodiments," or "in embodiments" in various places in the specification are not necessarily all referring to the same embodiment, although they can. Furthermore, the terms "a" or "an," as used in this specification do not denote a limitation of quantity or an intent that more than one of the referenced item is present.

[0026] It should be noted that the terms "first", "second", and the like in the present disclosure are merely used to distinguish different devices, modules, or units, and are not intended to limit the functions of the devices, modules, or units, or the sequence or interdependence of the functions. Unless otherwise specified, the terms "first", "second", and the like are not intended to imply a given order or any other manner of given order.

[0027] It should be noted that the modification of "one" and "multiple" mentioned in the present disclosure is illustrative rather than restrictive, and those skilled in the art should understand that "one or more" should be understood unless otherwise explicitly indicated in the context.

[0028] 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 intended to limit the scope of the messages or information.

[0029] 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 that is clear to those skilled in the art.

[0030] The factual error information can also be referred to as a factual error, that is, information inconsistent with information that is recognized as factually correct. For example, one day has 24 hours is factually correct information, and one day has 23 hours is factually incorrect information. There is no effective identification and correction mechanism for the factual error information published by the user, and the spread of the factual error information can cause incorrect guidance to other users, and the influence range can be wide.

[0031] To solve the above problems, the present disclosure provides an information processing method, which can improve the timeliness and accuracy of identifying and correcting factual error information, and reduce the incorrect guidance of factual error information to other users and the influence range.

[0032] Some embodiments of the information processing method of the present disclosure will be described below with reference to FIGS. 1-4.

[0033] FIG. 1 is a flowchart of some embodiments of the information processing method of the present disclosure. As shown in FIG. 1, the method of this embodiment includes steps S102-S106. The method of this embodiment can be executed by a client, or can be completed by cooperation of a client and a server. The client can be implemented by software and / or hardware.

[0034] In step S102, according to the information published by the first user, it is determined whether there is factual error information in the published information.

[0035] The first user can publish information in multiple ways on the network platform. The published information can include one or more media types. For example, in response to the first user inputting or uploading information to be published, and triggering a publishing control, the information to be published is published to obtain published information. For another example, in response to the first user publishing comment information in a comment area corresponding to information published by another user, the comment information is taken as published information. As long as the information published by the first user on the network platform is publicly published, the method of the present disclosure can be used to process the published information, and the manner of publishing information and the type of published information are not limited herein. For example, the published information can include information of at least one media type such as text, image, and video.

[0036] For example, a machine learning model can be used to determine whether there is factually incorrect information in the published information according to the information published by the first user. The machine learning model is, for example, a large model. In the case where the published information only includes text, the machine learning model can be a large language model (LLM). In the case where the published information only includes an image, the machine learning model can be a large graph model. In the case where the published information includes information of multiple media types, the machine learning model can be a multi-modal large model. The type of machine learning model is not limited to the examples shown.

[0037] In step S104, in response to the presence of factually incorrect information in the published information, error correction information is generated.

[0038] The error correction information includes correct information corresponding to the factually incorrect information. The machine learning model can be used to generate the correct information corresponding to the factually incorrect information to obtain the error correction information. The correct information corresponding to the factually incorrect information can be generated based on the factually correct information already stored in the resource library. The error correction information can include information of at least one media type, for example, the error correction information can include information of at least one media type such as text, image, and video. In the case where the error correction information includes information of multiple media types, the correct information can be displayed in a more vivid and rich form, so that the user who sees the error correction information can more easily understand and obtain correct knowledge information, thereby avoiding being misled by the factually incorrect information.

[0039] In step S106, the error correction information is displayed in a comment area corresponding to the published information.

[0040] A comment control can be displayed in the display interface of the published information. In response to a triggering operation on the comment control, a comment area is displayed, and the error correction information is displayed in the comment area. The display of the error correction information can also be triggered in other ways, which are not limited to the examples shown.

[0041] The comment area is an area closely associated with the published information, in which various users can comment on the published information, expand discussions, and users viewing the published information are likely to check the comments of other users in the comment area if they are interested in, have doubts about, or are affected by the published information. Therefore, displaying the correction information in the comment area corresponding to the published information can on the one hand make the correction information clearly associated with and corresponding to the published information, so that users viewing the published information can clearly know that the correction information is for correcting the published information; on the other hand, users who are more likely to be affected by the published information can see the correction information, thereby reducing the erroneous guidance of factual error information to these users. If the correction information is displayed in an area that is not closely associated with the published information, the above effects cannot be achieved.

[0042] The method of the above embodiment automatically determines whether there is factual error information in the published information in response to the information published by the first user, generates correction information if there is, and the correction information includes the correct information corresponding to the factual error information. The method of the above embodiment can improve the timeliness and effectiveness of identifying factual error information, display the correction information in the comment area corresponding to the published information, so that users who are more likely to be affected by the published information can clearly and accurately obtain correct information, reduce the erroneous guidance of factual error information to these users, reduce the influence range of factual error information, and improve the effectiveness of correction.

[0043] How to determine whether there is factual error information in the published information will be described below in conjunction with some embodiments.

[0044] The prompt information can be set to indicate whether the machine learning model identifies the published information as having factual error information. The prompt information and the published information are input into the machine learning model, and an identification result of whether the published information has factual error information is output. For example, the prompt information includes task information and output information. For example, the task information is used to describe that the task of the machine learning model is to identify whether the input information has factual error information based on the resource library, and the output information is used to describe that the output of the machine learning model is an identification result of whether the input information has factual error information.

[0045] In some embodiments, a machine learning model is used to understand the published information to obtain first semantic information of the published information, determine one or more target resources related to the first semantic information from the resource library, and determine whether there is factual error information in the published information according to the one or more target resources.

[0046] For example, one or more resources are stored in the resource library, each resource can include information of one or more media types, and the content of each resource is factually correct, i.e., each resource belongs to factually correct information. Through the machine learning model, the published information can be understood to obtain first semantic information, and one or more target resources related to the first semantic information can be determined from the resource library through semantic matching.

[0047] Further, in some embodiments, a machine learning model is employed to understand one or more resources in the resource library to obtain second semantic information of each resource in the one or more resources; the first semantic information is compared with the second semantic information of each resource to determine one or more target resources related to the first semantic information.

[0048] By matching the first semantic information with the second semantic information of each resource, one or more target resources related to the published information can be determined. Since the published information can include information of one or more media types, each resource can also include information of one or more media types, therefore, the machine learning model can perform semantic understanding on information of multiple media types, i.e., the machine learning model can perform multi-modal semantic understanding.

[0049] After determining the one or more target resources, since the content of the one or more target resources is factually correct, by comparing the first semantic information with the semantic information of the one or more target resources, it can be determined whether there is factually incorrect information in the published information. For example, the similarity between the first semantic information and the semantic information of the one or more target resources is determined, and in the case where the similarity between the first semantic information and the semantic information of each target resource is lower than a threshold value, it is determined that there is factually incorrect information in the published information, without being limited to the examples shown.

[0050] In some embodiments, a machine learning model is employed to identify a first keyword in the published information, match the first keyword with a second keyword of one or more resources in the resource library, determine one or more target resources related to the published information, and determine whether there is factually incorrect information in the published information according to the one or more target resources.

[0051] One or more target resources related to the published information can be determined through keyword matching, and then whether there is factually incorrect information in the published information can be determined according to the one or more target resources. For example, the first semantic information of the published information is compared with the semantic information of the one or more target resources to determine whether there is factually incorrect information in the published information.

[0052] In some embodiments, a first keyword in the published information is identified, the first keyword is matched with a second keyword of one or more resources in the resource library, one or more candidate resources related to the published information are determined, the published information is understood to obtain first semantic information of the published information, one or more target resources related to the first semantic information are determined from the one or more candidate resources, and it is determined whether there is factually incorrect information in the published information according to the one or more target resources.

[0053] The keyword matching and the semantic matching can be combined, some candidate resources are screened through the keyword matching, and then one or more target resources related to the published information are selected through the semantic matching, and it is determined whether there is factually incorrect information in the published information according to the one or more target resources.

[0054] Since the published information and the content of the one or more resources in the resource library can be relatively long, the semantic information can be relatively rich, and only a fragment in the published information can be factually incorrect information. The method of combining the keyword matching and the semantic matching can improve the efficiency and the accuracy.

[0055] In the above embodiments, whether there is factually incorrect information in the published information is identified based on the resources in the resource library by the machine learning model, which is more timely and accurate than manually identifying the factually incorrect information, reduces the incorrect guidance of the factually incorrect information to the viewing user, and reduces the spread range.

[0056] In response to the fact that there is no factually incorrect information in the published information, the published information can no longer be processed, and in response to the fact that there is factually incorrect information in the published information, error correction information needs to be generated. How to generate the error correction information is described below in combination with some embodiments.

[0057] In some embodiments, a target content related to the first semantic information is determined from the one or more target resources by using the machine learning model, and the target content is summarized to generate correct information corresponding to the factually incorrect information.

[0058] Since each target resource can include information of one or more media types, and only part of the content of each target resource can be related to the published information, a machine learning model can be employed to determine target content related to the first semantic information from understanding of each target resource. For example, a piece of text, an image, and / or a video in the target resource is target content related to the first semantic information. The machine learning model is employed to summarize the extracted target content to generate correct information corresponding to the factual error information, and further generate the correction information. The target content can be content in the plurality of target resources, and the correct information corresponding to the factual error information can be obtained by summarizing the content in the plurality of target resources.

[0059] The correct information corresponding to the factual error information can include information of one or more media types, for example, the correct information can be text, or can be presented by using other media types such as images, videos, and the like. The content of the correction information relative to the correct information can be more abundant and more consistent with the expression of natural language, and can include response information to the published information. For example, the published information is “one day has 23 hours”, the correct information is “one day has 24 hours”, and the correction information can be “no, one day has 24 hours”.

[0060] Since the target resource is factually correct, by extracting and summarizing the target content related to the first semantic information in the target resource, the correct information corresponding to the factual error information is generated, which can improve the effectiveness and accuracy of the correction.

[0061] In some embodiments, the correction information further includes basis information corresponding to the correct information, and the machine learning model is employed to extract the basis information corresponding to the correct information from the target content. The basis information includes information of at least one media type.

[0062] The basis information can enhance the persuasiveness and credibility of the correction information, thereby improving the correction effect. For example, the basis information can be text, images, and / or videos and the like further extracted from the target content. By displaying multiple media types or multi-modal information in the correction information, the user can be more attracted to view the correction information, the display effect and persuasiveness of the correction information can be improved, thereby improving the correction effect and reducing the incorrect guidance and propagation range of the factual error information to the user.

[0063] In some embodiments, the correction information further includes a link corresponding to the basis information, or a link corresponding to the correct information, or a link corresponding to the target content, or a link corresponding to one or more target resources.

[0064] Adding the link in the correction information can enhance the persuasiveness and credibility of the correction information, and the viewing user of the correction information can further view the complete content of the target resource through the link, reducing the operation of the viewing user searching for related knowledge by himself, facilitating the viewing user to acquire the knowledge of the target resource, and further improving the correction effect.

[0065] After generating the correction information, the correction information can be displayed in the comment area corresponding to the published information, that is, the correct information corresponding to the factual error information can be displayed, the basis information can be displayed, and the link can be displayed, so that the viewing user of the correction information can more accurately and conveniently and comprehensively understand the related correct knowledge of the factual error information in a more diversified form.

[0066] The way of triggering the identification of whether the published information has factual error information and displaying the correction information can be various, and first how to trigger the identification of the published information will be described in combination with some embodiments.

[0067] The identification of whether the published information has factual error information can be triggered by the correction intelligent agent or through the interaction with the correction intelligent agent, and the correction information can be published by the correction intelligent agent. The identification of the published information can be triggered by the correction intelligent agent, so as to more timely and accurately identify whether the published information has factual error information, and the correction intelligent agent has more persuasiveness in publishing the correction information than ordinary users, thereby improving the correction effect.

[0068] In some embodiments, in response to a publishing operation of a first user on published information, the published information is acquired, and whether the published information has factual error information is determined according to the published information.

[0069] For example, the published information is a work published by the first user, which can be a text, an image, a video and the like created by the first user, or a work generated by the first user through various ways such as re-posting or adaptation, and is not limited to the examples. For example, in response to the first user generating the published information through one or more ways such as inputting, uploading and the like, and triggering a publishing control (i.e. a publishing operation), the published information is acquired. The operation of the first user inputting and uploading the published information can be various, which will not be described herein.

[0070] For another example, the published information is comment information published by the first user, which can be comment information on the work published by other users, or comment information on the work of the first user. For example, in response to the first user triggering a comment information publishing control (i.e. a publishing operation), the published information is acquired.

[0071] The published information can be public information published by the first user through various channels, not limited to the examples described above. For example, the published information can be a viewpoint published by the first user in a network platform such as a forum. By automatically triggering the identification of whether there is factual false information in the published information through the publishing operation, and the subsequent generation of correction information and the display of the correction information, the correction can be more timely and accurate for each item of published information, and the adverse effects of the factual false information in the entire network platform can be reduced.

[0072] The determination of whether there is factual false information in the published information can be made directly according to the to-be-published information before the publishing operation, for example, after the first user inputs or uploads the to-be-published information.

[0073] In some embodiments, in response to the first user mentioning the correction intelligent agent in the published information, the published information is obtained, and it is determined whether there is factual false information in the published information according to the published information.

[0074] For example, the first user can mention the correction intelligent agent by mentioning an identifier. The mentioning identifier is, for example, “@”. The correction intelligent agent can also be mentioned in other ways, not limited to the examples described above. For example, the work published by the first user can include the work itself and brief description information, and the correction intelligent agent can be mentioned in the work or the brief description information.

[0075] As shown in FIG. 2A, the display interface includes a display area 201 in which the published information is displayed. The display area 201 can display the work published by the first user. The display interface can also include a display area 202 in which the brief description information is displayed. The display area 202 can be displayed in various forms such as a floating layer, a window, and the like, not limited to the examples described above. The display area 202 can display a general description of the work or other related content. The correction intelligent agent can be mentioned in the brief description information to trigger the identification of whether there is factual false information in the published information. For example, the brief description information is “In fact, a day of an earthling has 23 hours @ correction intelligent agent”.

[0076] For another example, the first user mentions the intelligent agent in the comment information. As shown in FIG. 2B, the display area 201 can display the published information, and the display area 203 can display the comment information of each user in response to the triggering of the comment control. For example, the first user has the nickname ABC, and the comment information is “In fact, a day of an earthling has 23 hours @ correction intelligent agent”. The comment information can be summary information of the published information or key information in the published information, and can also include information consistent with the brief description information described above, or other information related to the published information.

[0077] The first user can mention the correction intelligent agent in the published information, and actively trigger identification of whether there is factual error information in the published information. If the first user is not sure about the accuracy of the published information, the first user can actively trigger identification and subsequent correction of the published information, and then the first user can modify the published information to make the published information more accurate. The user who publishes the information is provided with a self-checking approach, which is simple and convenient. Compared with the user searching for relevant knowledge to determine whether the published information is accurate, the efficiency and accuracy of self-checking are improved, and the adverse effects of the factual error information generated in the entire network platform are reduced.

[0078] In some embodiments, in response to a second user watching the published information publishing question information to the correction intelligent agent in the comment area corresponding to the published information, the published information is obtained, wherein the question information is used to ask the correction intelligent agent whether the published information has errors; and whether there is factual error information in the published information is determined according to the published information.

[0079] The second user refers to one or more users watching the published information, and can also include the first user. The second user can ask the correction intelligent agent in the comment area corresponding to the published information, and the question information can mention the correction intelligent agent to trigger identification of whether there is factual error information in the published information.

[0080] As shown in FIG. 2C, in the comment area 203, the nickname of the second user is DEF. If the second user is doubtful about the video published by the first user, the second user can ask the correction intelligent agent “Is the content of this video correct? @Correction Intelligent Agent”.

[0081] If the user watching the published information is doubtful about the published information, inconsistent with his own cognition, etc., the user can ask the correction intelligent agent, trigger identification and subsequent correction of the published information. For the user watching the published information, more accurate information can be obtained through simple and convenient operation, without the need for searching and judging, etc., improving the efficiency and accuracy of correction, and reducing the adverse effects of the factual error information generated in the entire network platform.

[0082] The comment area can be displayed in various forms such as a half-screen panel, a pop-up window, a floating layer, and the comment information in the comment area can be displayed statically or dynamically. For example, the comment area is displayed in the form of a transparent layer above the published information, and the comment information (which can be called a scroll) is displayed by scrolling. The display mode of the comment area is not limited to the examples shown in the figures.

[0083] The above-mentioned various methods of triggering identification of whether there is factual error information in the published information can be combined arbitrarily, and are not limited to the examples shown.

[0084] Next, how to display the correction information is described in combination with some embodiments.

[0085] In some embodiments, in response to the published information being a published work, the correction information is displayed as the comment information of the work by the correction intelligent agent in the comment area corresponding to the work.

[0086] As shown in FIG. 2D, if there is factual error information in the published information, the correction intelligent agent can publish the correction information in the form of comment information in the comment area 203. For example, the correction information can be displayed as the first comment information, i.e., displayed on top. The correction information can be displayed as a first-level comment. Generally, the correction information is the information responding to the published information the fastest, but in order to make the correction information be seen by more users and improve the correction effect, the correction information can be displayed as the first comment information in any case, and in the case of dynamic display of each comment information, the correction information can be fixedly displayed at a preset position so as to be seen by more users and improve the correction effect.

[0087] In some embodiments, in response to the published information being published comment information, the correction information is displayed as the reply information of the comment information by the correction intelligent agent in the comment area where the published comment information is located.

[0088] As shown in FIG. 2B or 2E, the correction intelligent agent can directly reply to the comment information published by the first user, and the reply content is the correction information. For example, the comment information published by the first user can be displayed as the first comment information, and the correction information can be displayed as the first reply information to the comment information, so that the correction information can be seen by more users and improve the correction effect. The correction information can be displayed as a second-level comment.

[0089] In some embodiments, in response to the second user watching the published information publishing the question information to the correction intelligent agent in the comment area corresponding to the published information, the correction information is displayed as the reply information of the question information by the correction intelligent agent in the comment area corresponding to the published information.

[0090] As shown in FIG. 2C, the correction intelligent agent replies to the question information of the second user, and the reply content is the correction information. For example, the question information of the second user can be displayed as the first comment information or the first comment information other than the comment information of the first user, and the correction information can be displayed as the first reply information to the question information, so that the correction information can be seen by more users and improve the correction effect. The correction information can be displayed as a second-level comment.

[0091] The correction information can not be subject to the folding rule, that is, it is kept displayed in the comment area, not hidden or folded, so that the correction information can be seen by more users, improving the correction effect and effectiveness, and reducing the error guidance and propagation range of factual error information to the viewing users.

[0092] In the above embodiments, for the case of triggering the existence of factual error information in the published information by different ways, the correction information can be displayed in different forms, so that the users who see the correction information can more clearly understand the relationship between the correction information and the published information, comment information or question information, improve the correction effect and effectiveness, and reduce the error guidance and propagation range of factual error information to the viewing users.

[0093] In some embodiments, the correction information is highlighted with a preset effect. For example, the correction information is displayed in a specific font, color, or highlighted in a way such as highlighting. So that users pay more attention to the correction information, improve the correction effect and effectiveness.

[0094] The foregoing embodiments mentioned that the correction information can also include correct information corresponding to the basis information, and the basis information can include at least one of text, image, audio, and video. In some embodiments, in response to a viewing operation of the third user on the image in the basis information, the image is displayed in an enlarged manner. In some embodiments, in response to a viewing operation of the third user on the video in the basis information, the video is played.

[0095] As shown in FIG. 3A, the correction information can include correct information displayed in text, and can also include basis information 301, which can be at least one of an image, a video, and audio. In response to a viewing operation of the third user on the image by clicking or the like, the enlarged image can be displayed in a pop-up window, a floating layer, or the like. In response to a viewing operation of the third user on the video by clicking or the like, the video can be played in a pop-up window, a floating layer, or the like. In response to a playing operation of the third user on the audio by clicking or the like, the audio can be played. The specific manner of the viewing operation is not limited herein. The image and the video can be displayed and played in a full screen or the like by the viewing operation of the third user, and in response to an exit operation (for example, an operation of clicking an area other than the display area of the image and the video, or the like) of the third user, the enlarged image is no longer displayed or the video is no longer played.

[0096] The display of a variety of media types or multi-modal information in the correction information can attract users to view the correction information more, improve the display effect, credibility and persuasiveness of the correction information, thereby improving the correction effect and reducing the error guidance and propagation range of factual error information to users.

[0097] The correction information can further include a link corresponding to the information. In some embodiments, in response to a third user viewing the correction information triggering the link, the third user is jumped to a page corresponding to the link.

[0098] As shown in FIG. 3B, a link corresponding to the information (corresponding to the information) is displayed. The link can be displayed in the form of text, etc., but is not limited to the examples shown. If the third user triggers the link by clicking or the like, the corresponding page can be jumped to. The display of the link can be triggered by the third user, for example, in response to the third user's preset operation (clicking the correction information or the like), the link corresponding to the information is displayed. The link corresponding to the information can be displayed in various forms of display areas such as new pages, windows, or floating layers, and the correction information can also be displayed at the same time.

[0099] Displaying the link corresponding to the information can enhance the persuasiveness and credibility of the correction information. The user viewing the correction information can further view the complete content of the target resource through the link, reducing the user's operation of searching for related knowledge by himself / herself, facilitating the user's acquisition of knowledge of the target resource, and further improving the correction effect.

[0100] The correction information can also be displayed together with the related information of the correction agent, for example, the identification information of the correction agent, one or more feedback controls corresponding to the correction information, and one or more feedback information corresponding to the feedback controls. In some embodiments, the identification information of the correction agent, the correction information published by the correction agent, and one or more feedback controls corresponding to the correction information and the feedback information corresponding to the feedback controls are displayed, wherein the one or more feedback controls include at least one of a positive feedback control and a negative feedback control; in response to a third user viewing the correction information triggering a target feedback control in the one or more feedback controls, the feedback information corresponding to the target feedback control is displayed.

[0101] For example, the identification information of the correction agent includes at least one of the image and the name of the correction agent, which can be modified. As shown in FIGS. 2B to 3B, the one or more feedback controls are, for example, "like" and "dislike" controls, which are used to feed back positive opinions or negative opinions. The feedback information corresponding to the one or more feedback controls is, for example, the number of triggers of the feedback controls. For example, in response to the third user clicking the feedback control of "like", the number of "likes" is increased by one, and the trigger of the feedback control can be displayed by changing the color of the feedback control. In addition, the publication time and location of the correction information and the like can also be displayed.

[0102] By setting the feedback controls and the feedback information corresponding thereto, the feedback of the user to the correction information can be obtained. According to these feedbacks, the content and expression manner of the correction information can be further adjusted, so that more users can pay attention to the correction information and the correction effect is improved.

[0103] The error correction intelligent agent can interact with the user in addition to publishing the error correction information. In some embodiments, in response to a third user viewing the error correction information, the third user interacts with the error correction intelligent agent based on the error correction information, and display interaction information of the error correction intelligent agent and the third user.

[0104] For example, as shown in FIGS. 2B to 3B, a reply control corresponding to the error correction information can be displayed. As shown in FIG. 3C, in response to the third user triggering the reply control, an input area 303 is displayed, and the third user can input reply information to the error correction information through a virtual keyboard, voice, or the like, and then interact with the error correction intelligent agent based on the error correction information. The interaction with the error correction intelligent agent can also be triggered in other ways, and the content of the interaction can also not be limited to the error correction information or the published information itself. The error correction intelligent agent can interact with the third user as a knowledge-based tool. The interaction information can be displayed in a comment area, or a new interface can be displayed as an interaction interface of the third user and the error correction intelligent agent, and the interaction information is displayed in the interaction interface.

[0105] Any user can interact with the error correction intelligent agent, which can or can not be related to the published information or the error correction information. For example, in response to any user inputting interaction information to the error correction intelligent agent, reply information issued by the error correction intelligent agent is displayed. The interaction information of the user and the error correction intelligent agent can be displayed in a comment area or a new interface, which is not limited herein.

[0106] In the network platform, a user can configure a corresponding personal page. In order to make the error correction intelligent agent closer to the real user, a corresponding personal page can be configured for the error correction intelligent agent. In some embodiments, in response to a viewing operation of the third user viewing the error correction information to the error correction intelligent agent, a personal page of the error correction intelligent agent is displayed, and one or more pieces of knowledge information are displayed in the personal page, wherein the knowledge information is generated according to the error correction information.

[0107] For example, the third user can trigger the display of the personal page of the error correction intelligent agent by clicking the identification information of the error correction intelligent agent or the like. The personal page of the error correction intelligent agent can be consistent with the type and style of the information displayed in the personal page of the ordinary user, so that the user can better view the personal page of the error correction intelligent agent. The personal page of the error correction intelligent agent can display identification information of the error correction intelligent agent, such as an image, a name, or the like, and can also display one or more pieces of knowledge information, which is generated according to the error correction information. For example, the knowledge information can be a science popularization video generated according to the error correction information, which can be generated based on one or more target resources used to generate the error correction information.

[0108] More factual and correct knowledge can be spread to the user through the personal page of the correction agent, and the influence of the factual incorrect information on the user can be reduced.

[0109] The foregoing embodiments mention that the information processing method of the present disclosure can be executed by the client, and can also be completed by the cooperation of the client and the server. How the information processing method is completed by the cooperation of the client and the server will be described below in combination with some embodiments.

[0110] The client can be implemented by software or a combination of software and hardware, and can include the correction agent and the user interface. The server can include the correction system and can also include the audit system.

[0111] In some embodiments, the published information is matched with preset information in a database to determine whether the preset information is contained in the published information; and in response to the fact that the preset information is not contained in the published information, it is determined whether the factual incorrect information is contained in the published information.

[0112] It can be determined by the audit system whether the preset information is contained in the published information. The preset information can be information related to safety, sensitive words, etc. Through the audit of the audit system, the safety and legality of the published information can be improved.

[0113] FIG. 4 is a flowchart of another embodiment of the information processing method of the present disclosure. As shown in FIG. 4, the method of this embodiment includes steps S401-S408.

[0114] In step S401, the client receives the published information input by the user, the questioning information of the correction agent, or the mention of the correction agent in the published information through the user interface.

[0115] In step S402, the client sends the published information or the questioning information to the audit system of the server.

[0116] The published information can be information that has been published after the publishing operation, or information that is to be published before the publishing operation.

[0117] In step S403, the audit system determines whether the preset information is contained in the published information or the questioning information.

[0118] In step S404, in response to the fact that the preset information is not contained in the published information or the questioning information, the audit system sends the published information or the questioning information to the correction system.

[0119] In step S405, the correction system of the server determines whether the factual incorrect information is contained in the published information or whether the questioning information is factual questioning information.

[0120] The factual questioning information is information that asks questions about facts.

[0121] In step S406, in response to the existence of the factual error information in the published information, the error correction system generates the error correction information, or in response to the question information being the factual question information, the error correction system generates the reply information.

[0122] The process of generating the reply information is similar to that of generating the error correction information, which can be referred to the foregoing embodiments and will not be described here.

[0123] In step S407, the error correction system sends the error correction information or the reply information to the error correction intelligent agent.

[0124] In step S408, the error correction intelligent agent publishes the error correction information or the reply information.

[0125] The method of the embodiments of the present disclosure can automatically identify whether there is factual error information in the published information, and in the case of the existence of factual error information, can automatically generate and display the error correction information, improving the timeliness and accuracy of the identification under the factual error, and avoiding the incorrect guidance of the factual error information to more users. Compared with the indication of the factual error information by the ordinary user, the error correction information published by the error correction intelligent agent is more credible, and the error correction effect is better. Through the display of the correct information, the multimedia type of the basis information and the link, the display effect and the credibility are improved, and the way for the user to obtain knowledge is increased. The error correction intelligent agent can also reply to the user's question, so that the user can quickly obtain the knowledge he wants to know, and expand the propagation range of the correct knowledge.

[0126] The present disclosure also provides an information processing apparatus, which will be described below in conjunction with FIG. 5.

[0127] FIG. 5 is a structural diagram of some embodiments of the information processing apparatus of the present disclosure. As shown in FIG. 5, the information processing apparatus 50 of the embodiment includes a determination module 510, a generation module 520 and a display module 530.

[0128] The determination module 510 is configured to determine, according to the information published by the first user, whether there is factual error information in the published information.

[0129] The generation module 520 is configured to generate error correction information in response to the existence of the factual error information in the published information, wherein the error correction information includes correct information corresponding to the factual error information.

[0130] The display module 530 is configured to display the error correction information in a comment area corresponding to the published information.

[0131] In some embodiments, the determining module 510 is configured to determine, according to the information published by the first user, whether there is factual incorrect information in the published information; in response to the presence of the factual incorrect information in the published information, generate correction information, wherein the correction information comprises correct information corresponding to the factual incorrect information; and display the correction information in a comment area corresponding to the published information.

[0132] In some embodiments, the determining module 510 is configured to use a machine learning model to understand one or more resources in a resource library to obtain second semantic information of each resource in the one or more resources; and compare the first semantic information with the second semantic information of each resource to determine one or more target resources related to the first semantic information.

[0133] In some embodiments, the generating module 520 is configured to use a machine learning model to determine, from the one or more target resources, target content related to the first semantic information; and summarize the target content to generate the correct information corresponding to the factual incorrect information.

[0134] In some embodiments, the correction information further comprises basis information corresponding to the correct information, and the generating module 520 is configured to use a machine learning model to extract, from the target content, the basis information corresponding to the correct information, wherein the basis information comprises information of at least one media type.

[0135] In some embodiments, the determining module 510 is configured to obtain the published information in response to a publishing operation of the first user on the published information, and / or in response to the first user mentioning a correction intelligent agent in the published information, wherein the correction intelligent agent is used to publish correction information; and determine, according to the published information, whether there is factual incorrect information in the published information.

[0136] In some embodiments, the display module 530 is configured to display, in response to the published information being published work, the correction information as comment information of the correction intelligent agent on the work in a comment area corresponding to the work; or in response to the published information being published comment information, display the correction information as reply information of the correction intelligent agent on the comment information in a comment area where the comment information is located.

[0137] In some embodiments, the determining module 510 is configured to obtain the published information in response to a second user who views the published information publishing question information to the correction intelligent agent in a comment area corresponding to the published information, wherein the question information is used to ask the correction intelligent agent whether the published information has errors; and determine, according to the published information, whether there is factual incorrect information in the published information.

[0138] In some embodiments, the display module 530 is configured to display the correction information as a reply to the question information of the correction intelligent agent in a comment area corresponding to the published information.

[0139] In some embodiments, the correction information further comprises basis information corresponding to the correct information, the basis information comprising at least one of text, image, audio, and video, and the display module 530 is configured to perform at least one of the following: in response to a viewing operation of the image in the basis information by a third user viewing the correction information, display the image in an enlarged manner; and in response to a viewing operation of the video in the basis information by the third user, play the video.

[0140] In some embodiments, the correction information further comprises a link corresponding to the basis information, and the display module 530 is further configured to, in response to a triggering of the link by the third user viewing the correction information, jump to a page corresponding to the link.

[0141] In some embodiments, the correction information is published by the correction intelligent agent, and the display module 530 is further configured to, in response to the third user viewing the correction information, enable the third user to interact with the correction intelligent agent based on the correction information, and display interaction information between the correction intelligent agent and the third user.

[0142] In some embodiments, the display module 530 is further configured to, in response to a viewing operation of the correction intelligent agent by the third user viewing the correction information, display a personal page of the correction intelligent agent, and display one or more pieces of knowledge information in the personal page, wherein the knowledge information is generated according to the correction information.

[0143] In some embodiments, the display module 530 is configured to display identification information of the correction intelligent agent, display the correction information published by the correction intelligent agent, and display one or more feedback controls corresponding to the correction information and feedback information corresponding to the one or more feedback controls, wherein the one or more feedback controls comprise at least one of a positive feedback control and a negative feedback control; and in response to a triggering of a target feedback control in the one or more feedback controls by the third user viewing the correction information, display feedback information corresponding to the target feedback control.

[0144] In some embodiments, the determination module 510 is further configured to match the published information with preset information in a database, determine whether the preset information is contained in the published information, and in response to the preset information not being contained in the published information, determine whether there is factual error information in the published information.

[0145] It should be noted that each unit (module) described above is a logical division according to the specific function implemented by it, and is not intended to limit the specific implementation manner, for example, it can be implemented in software, hardware or a combination of software and hardware. In actual implementation, each unit described above can be implemented as an independent physical entity, or can also be implemented by a single entity (for example, a processor (CPU or DSP, etc.), an integrated circuit, etc.). In addition, each unit described above is indicated by a dashed line in the drawing, indicating that these units can not actually exist, and the operations / functions implemented by them can be implemented by the processing circuit itself.

[0146] In addition, although not shown, the device can also include a memory, which can store various information generated by the device, each unit included in the device in operation, programs and data for operation, data to be transmitted by the communication unit, etc. The memory can be a volatile memory and / or a non-volatile memory. For example, the memory can include, but is not limited to, a random access memory (RAM), a dynamic random access memory (DRAM), a static random access memory (SRAM), a read-only memory (ROM), a flash memory. Of course, the memory can also be located outside the device. Alternatively, although not shown, the device can also include a communication unit, which can be used for communication with other devices. In one example, the communication unit can be implemented in a suitable manner known in the art, for example, including communication components such as an antenna array and / or a radio frequency link, various types of interfaces, communication units, etc. Here will not be described in detail. In addition, the device can also include other components not shown, such as a radio frequency link, a baseband processing unit, a network interface, a processor, a controller, etc. Here will not be described in detail.

[0147] Some embodiments of the present disclosure also provide an electronic device. FIG. 6 shows a block diagram of some embodiments of the electronic device of the present disclosure. For example, in some embodiments, the electronic device 60 can be various types of devices, for example, can include but not limited to mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablets), PMPs (portable multimedia players), vehicle terminals (such as vehicle navigation terminals), etc. and fixed terminals such as digital TVs, desktop computers, etc. For example, the electronic device 60 can include a display panel for displaying data and / or execution results utilized in the scheme according to the present disclosure. For example, the display panel can be various shapes, such as a rectangular panel, an oval panel or a polygonal panel, etc. In addition, the display panel can not only be a flat panel, but also a curved panel, or even a spherical panel.

[0148] As shown in FIG. 6, the electronic device 60 of this embodiment includes a memory 61 and a processor 62 coupled to the memory 61. It should be noted that the components of the electronic device 60 shown in FIG. 6 are merely exemplary and non-limiting, and the electronic device 60 can also have other components according to actual application needs. The processor 62 can control other components in the electronic device 60 to perform desired functions.

[0149] In some embodiments, the memory 61 is configured to store one or more computer readable instructions. When the processor 62 executes the computer readable instructions, the computer readable instructions are implemented by the processor 62 to implement the method according to any of the above embodiments. For specific implementation of each step of the method and related explanations, please refer to the above embodiments, and the repeated parts will not be described here.

[0150] For example, the processor 62 and the memory 61 can directly or indirectly communicate with each other. For example, the processor 62 and the memory 61 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 62 and the memory 61 can also communicate with each other through a system bus, and the present disclosure does not limit the processor 62 and the memory 61.

[0151] For example, the processor 62 can be embodied as various appropriate processors, processing devices, etc., such as a central processing unit (CPU), a graphics processing unit (GPU), a network processing unit (NP), etc.; and can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic component, a discrete hardware component. The central processing unit (CPU) can be X86 or ARM architecture, etc. For example, the memory 61 can include any combination of various forms of computer readable storage media, such as volatile memory and / or non-volatile memory. The memory 61 may, for example, include a system memory, which stores, for example, an operating system, application programs, a boot loader, a database, and other programs, etc. Various application programs and various data, etc. can also be stored in the storage medium.

[0152] In addition, according to some embodiments of the present disclosure, various operations / processes according to the present disclosure, when implemented by software and / or firmware, can install programs constituting the software from a storage medium or a network to a computer system with a dedicated hardware structure, such as the computer system (or electronic device) 70 shown in FIG. 7, which is capable of performing various functions when various programs are installed. FIG. 7 is a block diagram showing an example structure of a computer system that can be employed according to embodiments of the present disclosure.

[0153] In FIG. 7, a central processing unit (CPU) 701 executes various processes in accordance with a program stored in a read only memory (ROM) 702 or a program loaded from a storage section 708 to a random access memory (RAM) 703. In the RAM 703, data required when the CPU 701 executes various processes and the like is also stored as necessary. The central processing unit is merely exemplary, and can be other types of processors, such as the various processors described above. The ROM 702, the RAM 703, and the storage section 708 can be various forms of computer readable storage media, as described below. Note that, although the ROM 702, the RAM 703, and the storage section 708 are shown separately in FIG. 7, one or more of them can be combined or located in the same or different memory or storage modules.

[0154] The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output interface 705 is also connected to the bus 704.

[0155] The following components are connected to the input / output interface 705: an input section 706 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 707 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 708 including a hard disk, a magnetic tape, and the like; and a communication section 709 including a network interface card such as a LAN card, a modem, and the like. The communication section 709 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 computer system 70 are shown in FIG. 7 as communicating through the bus 704, 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.

[0156] A drive 710 is also connected to the input / output interface 705 as necessary. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is attached to the drive 710 as necessary, so that a computer program read therefrom is installed in the storage section 708 as necessary.

[0157] In the case where the above-described 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 711.

[0158] According to embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program code for executing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network by the communication device 709, or installed from the storage device 708, or installed from the ROM 702. When the computer program is executed by the CPU 701, the above-described functions defined in the methods of the embodiments of the present disclosure are executed.

[0159] It should be noted that, in the context of the present disclosure, a computer readable medium can be a tangible medium which can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable medium can be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable storage medium can be, for example, but 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 disc 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 for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, the computer readable signal medium can include a data signal carried in a baseband or as part of a carrier wave, in which the computer readable program code is carried. Such a propagated data signal can take any of a variety of forms, including but not limited to electro-magnetic, optical, or any suitable combination thereof. The computer readable signal medium can also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer readable medium can be transmitted by any suitable medium, including but not limited to wire, cable, RF (radio frequency), or any suitable combination thereof.

[0160] The above computer readable medium can be included in the above electronic device; or can exist separately, without being assembled into the electronic device.

[0161] In some embodiments, a computer program including instructions which, when executed by a processor, causes the processor to carry out the method according to any of the embodiments described above is also provided. For example, the instructions can be embodied in a computer program code.

[0162] In an embodiment of the disclosure, computer program code to carry out operations of the disclosure described above can be written in one or more programming languages, or combinations thereof, including object oriented programming languages, such as Java, Smalltalk, C++, 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).

[0163] The flow diagrams and the block diagrams in the drawings are illustrations of possible architectures, functions, and operations for systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flow diagrams or block diagrams can represent a module, a segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may

[0164] The modules, components or units described in the embodiments of the present disclosure can be implemented by software or by hardware. In some cases, the name of the module, component or unit does not constitute a limitation on the module, component or unit itself.

[0165] The functionality described herein above can be performed, at least in 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), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip systems (SOCs), complex programmable logic devices (CPLDs), etc.

[0166] According to some embodiments of the present disclosure, an information processing method is provided, including: determining whether there is factual incorrect information in published information according to the published information of a first user; in response to the presence of factual incorrect information in the published information, generating correction information, wherein the correction information includes correct information corresponding to the factual incorrect information; and displaying the correction information in a comment area corresponding to the published information.

[0167] In some embodiments, determining whether there is factual incorrect information in the published information according to the published information of the first user includes: using a machine learning model to understand the published information to obtain first semantic information of the published information; determining one or more target resources related to the first semantic information from a resource library; and determining whether there is factual incorrect information in the published information according to the one or more target resources.

[0168] In some embodiments, determining one or more target resources related to the first semantic information from the resource library includes: using a machine learning model to understand one or more resources in the resource library to obtain second semantic information of each resource in the one or more resources; and comparing the first semantic information with the second semantic information of each resource to determine the one or more target resources related to the first semantic information.

[0169] In some embodiments, generating the correction information includes: using a machine learning model to determine target content related to the first semantic information from the one or more target resources; and summarizing the target content to generate the correct information corresponding to the factual incorrect information.

[0170] In some embodiments, the correction information further includes basis information corresponding to the correct information, and generating the correction information further includes: using a machine learning model to extract the basis information corresponding to the correct information from the target content, wherein the basis information includes information of at least one media type.

[0171] In some embodiments, determining whether the published information contains factual incorrect information according to the published information of the first user includes: in response to a publishing operation of the first user on the published information, and / or in response to the first user mentioning a correction intelligent agent in the published information, obtaining the published information, wherein the correction intelligent agent is used to publish correction information; and determining whether the published information contains factual incorrect information according to the published information.

[0172] In some embodiments, displaying the correction information in the comment area corresponding to the published information includes: in response to the published information being published work, displaying the correction information as comment information of the work by the correction intelligent agent in the comment area corresponding to the work; or in response to the published information being published comment information, displaying the correction information as reply information of the comment information by the correction intelligent agent in the comment area where the comment information is located.

[0173] In some embodiments, determining whether the published information contains factual incorrect information according to the published information of the first user includes: in response to a publishing operation of the first user on the published information, and / or in response to the first user mentioning a correction intelligent agent in the published information, obtaining the published information, wherein the correction intelligent agent is used to publish correction information; and determining whether the published information contains factual incorrect information according to the published information.

[0174] In some embodiments, displaying the correction information in the comment area corresponding to the published information includes: displaying the correction information as reply information of the question information by the correction intelligent agent in the comment area corresponding to the published information.

[0175] In some embodiments, the correction information further includes basis information corresponding to the correct information, the basis information including at least one of text, image, audio, and video, and the information processing method further includes at least one of the following: in response to a viewing operation of a third user viewing the image in the basis information while viewing the correction information, zooming in on the image; and in response to a viewing operation of the third user viewing the video in the basis information while viewing the correction information, playing the video.

[0176] In some embodiments, the correction information further includes a link corresponding to the basis information, and the information processing method further includes: in response to a trigger of the link by a third user viewing the correction information, jumping to a page corresponding to the link.

[0177] In some embodiments, the correction information is published by the correction intelligent agent, and the information processing method further includes: in response to a third user viewing the correction information, enabling the third user to interact with the correction intelligent agent based on the correction information, and displaying interaction information between the correction intelligent agent and the third user.

[0178] In some embodiments, the information processing method further includes: in response to a viewing operation of the third user on the correction intelligent agent, displaying a personal page of the correction intelligent agent, and displaying one or more pieces of knowledge information in the personal page, wherein the knowledge information is generated according to the correction information.

[0179] In some embodiments, displaying the correction information includes: displaying identification information of the correction intelligent agent, displaying the correction information published by the correction intelligent agent, displaying one or more feedback controls corresponding to the correction information and feedback information corresponding to the one or more feedback controls, wherein the one or more feedback controls include at least one of a positive feedback control and a negative feedback control; the information processing method further includes: in response to a trigger of a target feedback control in the one or more feedback controls by the third user, displaying feedback information corresponding to the target feedback control.

[0180] In some embodiments, determining whether there is factual error information in the published information according to the information published by the first user includes: matching the published information with preset information in a database to determine whether the published information contains the preset information; and in response to the published information not containing the preset information, determining whether there is factual error information in the published information.

[0181] According to another embodiment of the present disclosure, an information processing device is provided, including: a determination module configured to determine whether there is factual error information in the published information according to the information published by the first user; a generation module configured to generate correction information in response to the published information containing factual error information, wherein the correction information includes correct information corresponding to the factual error information; and a display module configured to display the correction information in a comment area corresponding to the published information.

[0182] According to still another embodiment of the present disclosure, an electronic device is provided, including: a processor; and a memory coupled to the processor, configured to store instructions, the instructions being executed by the processor to cause the processor to perform the information processing method of any one of the embodiments of the present disclosure.

[0183] According to still another embodiment of the present disclosure, a computer readable storage medium is provided, having a computer program stored thereon, the program being executed by a processor to perform the information processing method of any one of the embodiments of the present disclosure.

[0184] According to still another embodiment of the present disclosure, a computer program product is provided, including: instructions, the instructions being executed by a processor to implement the information processing method of any one of the embodiments of the present disclosure.

[0185] According to still another embodiment of the present disclosure, a computer program is provided, including: instructions, the instructions being executed by a processor to implement the information processing method of any one of the embodiments of the present disclosure.

[0186] The above description is only some embodiments of the present disclosure and an explanation of the principles of the technology used. Those skilled in the art should understand that the disclosed range of the present disclosure is not limited to the technical solutions formed by the specific combinations of the technical features described above, and should also cover other technical solutions formed by any combination of the above technical features or equivalent features without departing from the above disclosed concept. For example, the technical solutions formed by replacing the above features with the technical features disclosed in the present disclosure (but not limited to) having similar functions.

[0187] In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the application can be practiced without these specific details. In other instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

[0188] In addition, although each operation is described in a particular order, this should not be understood as requiring the operations to be performed in the particular order shown or in sequential order. In certain circumstances, multitasking and parallel processing can be advantageous. Likewise, although several implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the disclosure. Certain features described in the context of separate embodiments can also be combined in a single embodiment. Conversely, various features described in the context of a single embodiment can also be implemented in separate embodiments or in any suitable sub-combination.

[0189] Although some specific embodiments of the present disclosure have been described in detail by way of example, those skilled in the art should understand that the above examples are only for illustration, not for limiting the scope of the present disclosure. Those skilled in the art should understand that the above embodiments can be modified without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.

Claims

1. An information processing method, comprising: Based on the information posted by the first user, determine whether there are any factual errors in the posted information; In response to the existence of the factual error in the published information, error correction information is generated, wherein the error correction information includes the correct information corresponding to the factual error; The correction information is displayed in the comment area corresponding to the published information.

2. The information processing method according to claim 1, wherein, The step of determining whether there is factual error in the information posted by the first user includes: A machine learning model is used to understand the published information to obtain the first semantic information of the published information; Identify one or more target resources related to the first semantic information from the resource repository; Based on the one or more target resources, determine whether the published information contains the factual error.

3. The information processing method according to claim 2, wherein, The step of determining one or more target resources related to the first semantic information from the resource repository includes: Using the machine learning model, one or more resources in the resource library are understood to obtain the second semantic information of each of the one or more resources; The first semantic information is compared with the second semantic information of each resource to determine one or more target resources related to the first semantic information.

4. The information processing method according to claim 2 or 3, wherein, The generated error correction information includes: Using the machine learning model, target content related to the first semantic information is determined from the one or more target resources; The target content is summarized to generate the correct information corresponding to the factual error information.

5. The information processing method according to claim 4, wherein, The error correction information also includes the basis information corresponding to the correct information, and the generation of error correction information also includes: Using the machine learning model, the basis information corresponding to the correct information is extracted from the target content, wherein the basis information includes information of at least one media type.

6. The information processing method according to any one of claims 1-5, wherein, The step of determining whether there is factual error in the information posted by the first user includes: In response to the first user's publishing operation of the published information, and / or in response to the first user mentioning the error correction agent in the published information, the published information is obtained, wherein the error correction agent is used to publish the error correction information; Based on the published information, determine whether there are any factual errors in the published information.

7. The information processing method according to claim 6, wherein, The display of the correction information in the comment area corresponding to the published information includes: In response to the published information being a published work, the error correction information is displayed as the error correction agent in the comment area corresponding to the work, providing the error correction information for the comment information of the work; or In response to the published information being a published comment, the error correction information is displayed as a reply from the error correction agent to the comment in the comment area where the published comment is located.

8. The information processing method according to any one of claims 1-7, wherein, The step of determining whether there is factual error in the information posted by the first user includes: In response to a second user viewing the published information, a question is posted to the error-correcting agent in the comment area corresponding to the published information, and the published information is obtained. The question is used to ask the error-correcting agent whether there is an error in the published information. Based on the published information, determine whether the published information contains any factual errors.

9. The information processing method according to claim 8, wherein, The display of the correction information in the comment area corresponding to the published information includes: In the comment area corresponding to the published information, the error correction information is displayed as the response information of the error correction agent to the question.

10. The information processing method according to any one of claims 1-9, wherein, The error correction information also includes supporting information corresponding to the correct information, wherein the supporting information includes at least one of text, image, audio, and video, and the information processing method further includes at least one of the following: In response to a third user viewing the error correction information and viewing an image in the information, the image is enlarged and displayed. In response to the third user's viewing operation of the video in the information provided, the video is played.

11. The information processing method according to claim 10, wherein, The error correction information also includes the link corresponding to the information, and the information processing method further includes: In response to a third user viewing the error correction information triggering the link, the user is redirected to the link corresponding to the error correction information. page.

12. The information processing method according to any one of claims 1-11, wherein, The error correction information is published by the error correction agent, and the information processing method further includes: In response to a third user viewing the error correction information, the error correction agent interacts with the error correction information, and the interaction information between the error correction agent and the third user is displayed.

13. The information processing method according to any one of claims 1-12, further comprising: In response to a third user viewing the error correction information, the error correction agent's personal page is displayed, and one or more pieces of knowledge information are displayed on the personal page, wherein the knowledge information is generated based on the error correction information.

14. The information processing method according to any one of claims 1-13, wherein, The display of the error correction information includes: Display the identification information of the error correction agent, display the error correction information published by the error correction agent, and display one or more feedback controls corresponding to the error correction information and their corresponding feedback information, wherein the one or more feedback controls include at least one of positive feedback controls and negative feedback controls; The information processing method further includes: In response to a third user viewing the error correction information triggering a target feedback control among the one or more feedback controls, the feedback information corresponding to the target feedback control is displayed.

15. The information processing method according to any one of claims 1-14, wherein, The step of determining whether there is factual error in the information posted by the first user includes: The published information is matched with preset information in the database to determine whether the published information contains the preset information. In response to the fact that the published information does not contain the preset information, it is determined whether the published information contains the factual error.

16. An information processing apparatus, comprising: The determination module is configured to determine whether there is any factual error in the information published by the first user. The generation module is configured to generate correction information in response to the existence of the factual error information in the published information, wherein the correction information includes the correct information corresponding to the factual error information; The display module is configured to display the error correction information in the comment area corresponding to the published information.

17. An electronic device comprising: processor; as well as A memory coupled to the processor is used to store instructions that, when executed by the processor, cause the processor to perform the information processing method as described in any one of claims 1-15.

18. A computer-readable storage medium having a computer program stored thereon, wherein, When executed by a processor, the program implements the information processing method according to any one of claims 1-15.

19. A computer program product comprising: Instructions which, when executed by a processor, implement the information processing method according to any one of claims 1-15.

20. A computer program comprising: Instructions which, when executed by a processor, implement the information processing method according to any one of claims 1-15.

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