Method for classifying information, related device and computer program product

Abstract

This application provides a method, related apparatus, and computer program product for classifying information. The method, in response to receiving a request to publish information to be published, obtains an object identifier of a target object requesting the publication of the information to be published; combines at least a text recognition result of the object identifier with the text content of the information to be published to generate information to be classified; and, in response to the information to be classified not including a preset target content type, classifies the information to be published as information of the target type. This improves the performance and quality of information content classification.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method and device for classifying information, an electronic device, a computer-readable medium, and a computer program product. Background Art

[0002] As society develops, computer technology also advances. The internet provides a platform for users to communicate, allowing them to share content and connect with other users by posting videos and information. For example, users can communicate with other users online by posting information.

[0003] Against this backdrop, platforms have emerged to facilitate user access to content and communication. Consequently, platforms enable users to share and exchange content without establishing connections, such as friendships. Consequently, ensuring safe, friendly, and healthy communication on these platforms, and guaranteeing the quality of shared information, are critical concerns and pressing needs. Summary of the Invention

[0004] Various aspects of the present application provide a method, apparatus, electronic device, computer-readable storage medium, and computer program product for classifying information. These methods can determine the complete content of "information actually requiring classification" based on the information to be published that a combined object expects to publish and the content after object identification, and execute a corresponding publishing strategy based on the classification results of the classified information. This allows for a more complete and accurate determination of the information requiring classification, avoiding issues such as inaccurate information reading and low classification quality caused by publishing and providing information in a combined format. This improves the quality of information processing and classification.

[0005] In one aspect of the present application, a method for classifying information is provided, comprising: in response to receiving a publishing request for publishing information to be published, obtaining an object identifier of a target object for which the information to be published is requested to be published; combining at least a text recognition result of the object identifier and text content of the information to be published to generate information to be classified; and in response to the information to be classified not including a preset type of target content, classifying the information to be published as information of the target type.

[0006] Another aspect of the present application provides an apparatus for classifying information, comprising: an object identification acquisition unit, configured to, in response to receiving a publishing request for publishing information to be published, acquire the object identification of a target object for which the information to be published is requested to be published; a to-be-classified information generation unit, configured to combine at least a text recognition result of the object identification and text content of the information to be published to generate the information to be classified; and a first information classification unit, configured to, in response to the information to be classified not including a preset type of target content, classify the information to be published as information of a target type.

[0007] Another aspect of the present application provides an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method for classifying information provided above.

[0008] In another aspect of the present application, a computer-readable storage medium is provided, on which computer program instructions are stored. The computer program instructions can be executed by a processor to implement the method for classifying information provided above.

[0009] In another aspect of the present application, a computer program product includes a computer program having computer program instructions stored thereon. When the computer program is executed by a processor, the computer program can implement the method for classifying information provided above.

[0010] In the solution provided by the embodiment of the present application, in response to receiving a publishing request to publish information to be published, the object identifier of the target object requesting the publication of the information to be published is obtained; at least the text recognition result of the object identifier and the text content of the information to be published are combined to generate information to be classified; and in response to the information to be classified not including the target content of the preset type, the information to be published is classified as information of the target type. In this way, the information to be published that the object desires to publish and the object identifier can be combined to obtain a complete "information to be classified" for classification, and the corresponding publishing strategy can be determined based on the results of the information to be classified. In this way, the classification performance and quality of the information published by the object can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present application, a brief introduction will be given below to the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0012] Other features, objects and advantages of the present application will become more apparent upon reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0013] Figure 1 A schematic diagram of the information classification process provided in one embodiment of the present application;

[0014] Figure 2 A schematic diagram of a process for obtaining an object identifier provided in one embodiment of the present application;

[0015] Figure 3 A schematic diagram of another process for obtaining an object identifier provided in another embodiment of the present application;

[0016] Figure 4 A schematic diagram of a process for classifying information in an application scenario provided by an embodiment of the present application;

[0017] Figure 5 A schematic diagram of the structure of an apparatus for classifying information provided in one embodiment of the present application;

[0018] Figure 6 The figure is a schematic diagram of the structure of an electronic device suitable for implementing the solution in the embodiment of the present application.

[0019] The same or similar reference numerals in the drawings represent the same or similar components. DETAILED DESCRIPTION

[0020] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0021] In a typical configuration of the present application, the terminal and the equipment of the service network each include one or more processors (CPUs), input / output interfaces, network interfaces and memories.

[0022] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0023] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology for information storage. The information can be computer program instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc-read only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0024] In practical scenarios, the execution subject of this method can be an object device, or a device formed by integrating an object device and a network device through a network, or an application running on such a device. Object devices include but are not limited to various terminal devices such as computers, mobile phones, tablets, smart watches, and wristbands. Network devices include but are not limited to network hosts, single network servers, multiple network servers, or a collection of computers based on cloud computing. Here, the cloud is composed of a large number of hosts or network servers based on cloud computing. Cloud computing is a type of distributed computing, consisting of a group of loosely coupled computers forming a virtual computer.

[0025] When the execution subject is software, it can be installed in the electronic devices listed above. It can be implemented as multiple software or software modules, or as a single software or software module, and is not specifically limited here.

[0026] It should be understood that in the technical solutions involved in this application, the acquisition, storage, use, processing, transportation, provision and disclosure of the personal information of the objects involved (for example, the information to be published by users and objects later involved in this application, object identification, etc.) are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0027] Figure 1 A process 100 for classifying information provided by an embodiment of the present application is shown. The process 100 includes at least the following processing steps:

[0028] (Step) S101: In response to receiving a publishing request for publishing information to be published, obtaining an object identifier of a target object for which publishing of the information to be published is requested.

[0029] In an embodiment of the present application, exemplarily, in the case of an execution entity such as a server used by a service provider of a platform, an object (e.g., a user requesting to publish information) can communicate with the execution entity through the terminal device used by it to publish information (e.g., post comments, dynamics, or upload object content, etc.).

[0030] It should be understood that the selection of the above-mentioned execution subject is only for exemplary purposes. In some scenarios, the execution subject may also be the terminal device used by the object, so that the object can classify the information locally while publishing the information.

[0031] When the executing subject receives a publishing request from an object (for ease of understanding, it can be described as a "target object") requesting to publish information to be published (for example, comments or dynamics to be published), it can respond to this and obtain the object identifier of the target object requesting to publish the information to be published. The object identifier can generally include content that can be associated with the object, presented to other objects to indicate the identity of the object, and allowed to be modified by the object. For example, the object identifier can include the object avatar, object name, etc. of the object. For example, after receiving the publishing request of the target object, the executing subject can obtain the object avatar and object name (in some scenarios, the object name can also be called the "object nickname") currently used by the target object to identify the object itself in the platform.

[0032] S102: at least combining the text recognition result of the object identifier and the text content of the information to be published to generate information to be classified.

[0033] In an embodiment of the present application, after obtaining the object identifier based on step S101 above, the execution entity may "textualize" the object identifier to obtain a text recognition result for the object identifier. For example, for an object identifier in the form of an avatar, the execution entity may detect whether the avatar contains text content. If so, the execution entity may extract the text content as the text recognition result for the "avatar." Correspondingly, for an object name or nickname, the execution entity may directly use it as the "text recognition result."

[0034] Then the execution subject combines at least the text recognition result of the object identifier and the text content of the information to be published to generate the information to be classified. Similarly, for the text content of the information to be published, the execution subject can directly use it as "text content". In some embodiments, if the information to be published includes image content, the execution subject can also include the text recognition result of the image content into the text content of the information to be published, so as to more accurately determine the content in the information to be published and classify it. In this way, it is avoided that when the object provides content in the form of an image, the classification is only based on the "original text content", which may potentially cause "omissions".

[0035] Next, the execution entity may combine the text recognition result and the text content to obtain the information to be classified, for example, by concatenating the text content of the information to be published after the text recognition result, or before the text recognition result.

[0036] In some embodiments, the execution subject can also realize the combination of the two through a pre-trained combination model, and the combination model can determine the way to combine the text content and the text recognition result based on the semantic analysis results of the text recognition results and the text content. For example, the combination model can obtain the readability, clarity, and semantics of each combination result from various combination methods, and then use the most "fluent" result (for example, the combination result with the highest readability and clarity) as the information to be classified. For example, the combination model can obtain the first combination result by "splicing the text content of the information to be released after the text recognition result" and the second combination result by "splicing the text content of the information to be released before the text recognition result". Exemplarily, if the semantic clarity and readability of the first combination result are higher than those of the second combination result, the execution subject can choose to use the first combination result as the information to be classified.

[0037] S103: Detect whether the information to be classified includes target content of a preset type.

[0038] In an embodiment of the present application, after obtaining the information to be classified based on the above S102, the execution subject can classify the information to be classified through a pre-configured classification strategy, a pre-trained classification model, etc. to determine whether it meets the publishing requirements. For example, it is detected whether the information to be classified includes target content of a preset type. The preset type can be preset according to the classification requirements (for example, it can be a content type for which the object lacks publishing authority). Accordingly, in the case of including content of such a preset type, the object actually lacks publishing authority for the information to be published. Accordingly, for such information to be published, it may be refused to provide publishing services by the execution subject.

[0039] Furthermore, if the execution subject determines that the information to be classified does not include target content of a preset type, S104 may be continued to be executed.

[0040] S104: Classify the information to be published into target type information.

[0041] In an embodiment of the present application, the executing subject may classify the information to be published as information of the target type when it is determined that the information to be classified does not exist or does not include the target content of the preset type. For example, such a target type may be a "target type" or "target classification" that "has publishing authority" and allows the publishing service provided by the executed subject. For example, for "information to be published" of such a target type, the executing subject may, according to the indication of the target object, move it to the corresponding information browsing area (for example, present the qualified information in the information area). Or in some scenarios, the executing subject may also provide the result to other subjects used to publish information to indicate that other subjects can publish and are allowed to publish the "information of the target type".

[0042] In some embodiments, the above process 100 may further include S105, which may be selected and executed by the executing subject when the executing subject determines that the information to be classified includes target content of a preset type.

[0043] S105: Classify the information to be published as non-target type information.

[0044] Specifically, for information to be classified that contains target content, the executing subject can determine that the object may change the information content by at least combining the information content and the object identifier, thereby interfering with the executing subject's classification process (for example, by splicing at least part of the content in the object identifier and at least part of the content in the information to be published to interfere with the executing subject, expecting the executing subject to mistakenly classify it from "non-target type" to "target type"). Therefore, for information to be classified that contains target content, the executing subject can correspondingly classify the information to be published as non-target type information. In this way, it is avoided that the object "interferes with classification" by combining the information content and the object identifier.

[0045] In some embodiments, after classifying the information to be published as non-target information, the executing entity can also choose to replace the object identifier with a pre-configured target identifier to eliminate "interference." For example, the default object identifier (default object avatar, object name) can be used to replace the target object's object identifier. This eliminates the target object's interference behavior.

[0046] Subsequently, the method for classifying information provided by this application can more completely and accurately determine the information that needs to be classified, avoiding the problems of inaccurate information reading and low classification quality caused by publishing and providing information in a combined form, thereby improving the quality of information processing and classification.

[0047] In some embodiments, to improve classification efficiency, you can also choose to classify "objects" to reduce the number of objects that need to be classified. This allows computing power to more efficiently focus on objects that may interfere with or mislead classification, thereby improving classification efficiency and capabilities.

[0048] For this, please refer to Figure 2 . Figure 2 A process 200 for obtaining an object identifier provided by an embodiment of the present application is shown. For example, process 200 can be used as an alternative or replacement for S102 in the above process 100. Process 200 includes at least the following processing steps:

[0049] S201 : In response to receiving a publishing request for publishing information to be published, detecting whether a target object has updated its object identifier in a historical time period before a current moment.

[0050] Specifically, in this embodiment, in response to receiving a publishing request for information to be published, the execution subject may first detect whether the target object has updated the object identifier (for example, updated the avatar, updated the object name) in a historical time period before the current moment (for the convenience of description, it will be described as the first historical time period). For example, the first historical time period can be obtained based on the results of a pre-analysis of the behavior of "interfering with classification" by publishing information after changing the avatar. For example, for object A, if it publishes information after updating its avatar and "interferes with classification" by combining the avatar and information, the execution subject can use the time from updating its avatar to publishing the information as a reference. Accordingly, the execution subject can construct a behavior model based on the behavior of a large number of objects that "interfere with classification" to determine the scope of the "first historical time period".

[0051] Accordingly, the execution subject can "classify" the object by detecting whether the target object has updated the object identification in the historical time period before the current moment, so as to identify the object that is more likely to send combined information to "interfere with classification" by updating the object identification.

[0052] Next, if the target object updates the object identifier in the first historical time period, the execution subject responds and executes S202.

[0053] S202: Obtain the object identifier of the target object for which publishing of the information to be published is requested.

[0054] It should be understood that in this step, the executing entity may choose to obtain only the updated object identifiers (i.e., the object identifiers that have been updated) to perform targeted detection. In some embodiments, to avoid interference with classification by objects that are updated in batches (for example, updating the avatar first and then updating the name after a period of time), the executing entity may also choose to obtain all available object identifiers simultaneously (i.e., not just the object identifiers that have been updated).

[0055] In some embodiments, the execution entity may also analyze the textual content of the information to be published to determine whether the object may be using combinational forms to interfere with classification. For example, "focusing" on "combinational forms" of "information to be published" that may use the information to be published to "imply" other objects using the combination of "object identifier and information to be published" to obtain a complete meaning.

[0056] For this, please refer to Figure 3 . Figure 3 Another process 300 for obtaining an object identifier provided by another embodiment of the present application is shown. For example, process 300 can be used as an alternative or replacement for S102 in the above process 100. Process 300 includes at least the following processing steps:

[0057] S301 , in response to receiving a publishing request for publishing information to be published, reading text content of the information to be published.

[0058] Specifically, in response to receiving a publishing request for publishing information to be published, the execution subject may first read the text content of the information to be published.

[0059] S302: Detect whether the text content includes key information pointing to the object identifier.

[0060] Specifically, the execution subject detects the text content read out in S301 to determine whether it includes key information pointing to the object identifier. For example, the key information may be "look at the avatar", "look at the name", etc. The type of key information may also be adjusted and determined based on the form and style of the information display area. For example, in a scene where the information display area is designed with the avatar on the left side of the comment content display position, the key information may also be "look left", "←", etc.

[0061] Accordingly, if the executing entity detects that the text content includes key information pointing to the object identifier, the object may "may have the behavior of interfering with classification by using the combination form" and chooses to continue executing S303 to "obtain the object identifier of the target object requested to publish the information to be published."

[0062] S303: Obtain the object identifier of the target object for which the information to be published is requested to be published.

[0063] Accordingly, if the text content does not include key information pointing to the object identifier, the execution entity can choose to directly detect whether the target content is included based on the text content to determine whether the information to be published is information of the target classification. In this way, by "classifying objects" using different classification dimensions, classification efficiency can be improved (that is, in the case of possible interference classification behavior using combination forms, at least the text recognition results of the object identifier and the text content of the information to be published are combined to generate the information to be classified).

[0064] For ease of understanding, illustratively, the process 300 may further include S304 , S305 , and S306 .

[0065] S304: Detect whether the text content includes the target content.

[0066] S305: Classify the information to be published into target type information.

[0067] S306: Classify the information to be published as non-target type information.

[0068] S304 can be executed when the execution subject determines based on the above S302 that the text content does not include key information pointing to the object identifier. Correspondingly, S305 can be executed after the execution subject executes S304 and determines that the text content does not include the target content. S306 can be executed after the execution subject executes S304 and determines that the text content includes the target content.

[0069] The detection method of the above S304 is similar to that discussed in S103 of the above process 100 and will not be repeated here.

[0070] Similarly, in some embodiments, in process 200, the text content of the information to be published can be directly classified to determine whether the information to be published is the target type of information when the target object has not updated the object identifier in the first historical time period, and the explanation will not be repeated.

[0071] Based on any of the above embodiments, in some embodiments, to prevent the target from "interfering with classification" by splitting multiple messages, the execution entity may further, when responding to a request to publish the pending information, simultaneously detect whether the target has published any historical information within a historical time period (for ease of description, referred to as a second historical time period) prior to the current moment. For example, the second historical time period may be determined based on a pre-analysis of historical objects that have "interfered with classification" by such "continuous sending behavior."

[0072] Accordingly, if the executing entity detects the existence of such historical information, the executing entity may, as an alternative or substitute, choose to combine the text content of the historical information, the text recognition result of the object identifier, and the text content of the information to be published during the execution of the above S102 to generate information to be classified for subsequent classification. The method of generating the text content of the historical information is similar to the method of generating the text content of the information to be published, and will not be repeated here. Therefore, in the case of the existence of historical information that meets the requirements, the information to be classified can combine multiple pieces of information and object identifiers of the object to more comprehensively determine whether the object uses a series of information and object identifiers to split the expressed content to "interfere with classification" and improve detection performance.

[0073] To deepen understanding, this application also provides a specific implementation solution in combination with a specific application scenario. Figure 4 , Figure 4 A schematic diagram of a process 400 of classifying information in an application scenario provided by an embodiment of the present application. In the process 400, for example, a server 410 may classify information.

[0074] Specifically, for example, object 420 communicates with server 410 and executes S401 to request server 410 to publish information 425. Accordingly, server 410 may respond to this, obtain information 425, and execute S402 to detect whether object 420 has updated its object identifier in a historical time period before the current moment.

[0075] Exemplarily, if the object 420 has updated both its avatar and name within the historical time period, the server 410 continues to execute S403 to obtain the object identification of the object 420. For example, the object avatar 430 and the object name 435 are obtained.

[0076] Then, the server 410 executes S404 to combine the text content "XX" in the information to be published 425, the text recognition result "YY" of the object avatar 430, and the object name 435 "ZZ" to obtain the information to be classified 440. For example, the format of the information to be classified 440 can be "XXYYZZ".

[0077] Then, server 410 executes S405 to detect whether information to be classified 440 includes target content (of a preset type). For example, the target content may be in the form of "XY." That is, server 410 can determine that information to be classified 440 includes the preset type of target content upon detecting that information to be classified 440 includes "XY," and thus, determine that information to be published 425 is not of the target type.

[0078] Alternatively, in some other examples, if the format of the preset type of target content is exemplified as "ZY", the to-be-published information 425 may be correspondingly determined as information of the target type.

[0079] The embodiment of the present application also provides a device for classifying information. The structure of the device is as follows: Figure 5 The device 500 shown in FIG. The device 500 includes: an object identifier acquisition unit 510 configured to, in response to receiving a publishing request for publishing information to be published, acquire the object identifier of the target object for which the information to be published is requested to be published; a to-be-classified information generation unit 520 configured to combine at least a text recognition result of the object identifier with the text content of the to-be-published information to generate the to-be-classified information; and a first information classification unit 530 configured to, in response to the information to be classified not including a preset type of target content, classify the to-be-published information into information of a target type.

[0080] In some embodiments, the object identification acquisition unit includes: an identification update detection subunit, which is configured to detect whether the target object has updated the object identification in a first historical time period before the current moment in response to receiving a publishing request to publish information to be published; and a first object identification acquisition subunit, which is configured to obtain the object identification of the target object requested to publish information to be published in response to the target object updating the object identification in the first historical time period.

[0081] In some embodiments, the object identification acquisition unit includes: a text content reading sub-unit, configured to read the text content of the information to be published in response to receiving a publishing request to publish the information to be published; a second object identification acquisition sub-unit, configured to obtain the object identification of the target object for which the information to be published is requested to be published in response to the text content including key information pointing to the object identification.

[0082] In some embodiments, the device 500 also includes: a target content detection unit, configured to detect whether the text content includes target content in response to the text content not including key information pointing to the object identifier; a first information classification unit 530, configured to also classify the information to be published as target type information in response to the text content not including the target content.

[0083] In some embodiments, the target object has published historical information within a second historical time period before the current moment, and the information to be classified generating unit 520 is further configured to combine the text content of the historical information, the text recognition result of the object identifier and the text content of the information to be published to generate the information to be classified.

[0084] In some embodiments, the information to be published includes image content, and the text content of the information to be published includes text recognition results of the image content.

[0085] In some embodiments, the apparatus 500 further includes: a second information classification unit configured to classify the information to be published as non-target type information in response to the information to be classified including target content.

[0086] In some embodiments, the apparatus 500 further includes: an object identifier replacement unit configured to replace the object identifier with a pre-configured target identifier.

[0087] Based on the same inventive concept, an electronic device, a readable storage medium, and a computer program product are also provided in an embodiment of the present application. The method corresponding to the electronic device can be the method for classifying information in the aforementioned embodiment, and its principle of solving the problem is similar to that of the method. The electronic device provided in an embodiment of the present application includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the methods and / or technical solutions of the aforementioned multiple embodiments of the present application.

[0088] An electronic device can be a user device, or a device formed by integrating a user device and a network device via a network, or an application running on any of the above devices. User devices include, but are not limited to, computers, mobile phones, tablets, smart watches, wristbands, and other terminal devices. Network devices include, but are not limited to, network hosts, single network servers, multiple network server clusters, or cloud computing-based computer clusters, and can be used to implement some of the processing functions required for setting an alarm. Here, the cloud is composed of a large number of hosts or network servers based on cloud computing. Cloud computing is a type of distributed computing, consisting of a virtual computer composed of a group of loosely coupled computers.

[0089] Figure 6 The structure of an electronic device suitable for implementing the method and / or technical solution in the embodiment of the present application is shown. The electronic device 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 602 or the program loaded from the storage part 608 into the random access memory (RAM) 603. In RAM 603, various programs and data required for system operation are also stored. CPU 601, ROM 602 and RAM 603 are connected to each other through a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0090] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, a touch screen, a microphone, an infrared sensor, etc.; an output section 607 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), an LED display, an OLED display, etc., and a speaker; a storage section 608 including one or more computer-readable media such as a hard disk, an optical disk, a magnetic disk, a semiconductor memory, etc.; and a communication section 609 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet.

[0091] In particular, the methods and / or embodiments in the embodiments of the present application can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes program code for executing the method shown in the flowchart. When the computer program is executed by the central processing unit (CPU) 601, the above-mentioned functions defined in the method of the present application are performed.

[0092] Another embodiment of the present application further provides a computer-readable storage medium and a computer program product, on which computer program instructions are stored. The computer program instructions can be executed by a processor to implement the methods and / or technical solutions of any one or more embodiments of the present application.

[0093] Specifically, the present embodiment can adopt any combination of one or more computer-readable media.Computer-readable media can be computer-readable signal media or computer-readable storage media.Computer-readable storage media can be, for example, systems, devices or components including but not limited to electricity, magnetism, light, electromagnetic, infrared, or semiconductors, or any combination thereof.More specific examples (non-exhaustive list) of computer-readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROMs), optical storage devices, magnetic storage devices, or any suitable combination thereof.In this document, computer-readable storage media can be any tangible medium containing or storing a program that can be used by an instruction execution system, device or device or used in combination with it.

[0094] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0095] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0096] The computer program code for performing the operations of the present application can be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, 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 can be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0097] The flow chart or block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the equipment, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code include one or more executable instructions for realizing the logical function of the specification. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated system for hardware that performs the function or operation of the specification, or can be implemented with a combination of dedicated hardware and computer instructions.

[0098] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0099] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of modules and units is only a logical function division. There may be other division methods in actual implementation. For example, with units as an example, for example, multiple units or page components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0100] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0101] In addition, the functional modules and units in the various embodiments of the present application may be integrated into a single processing module or unit, or each module or unit may exist physically separately, or two or more units may be integrated into a single module or unit. The aforementioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional modules or units.

[0102] The above-mentioned integrated modules and units implemented in the form of software functional modules and units can be stored in a computer-readable storage medium. The above-mentioned software functional modules and units are stored in a storage medium, including a number of instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute some steps of the methods of each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program code.

[0103] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

[0104] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices recited in a device claim may also be implemented by a single unit or device through software or hardware. Terms such as "first" and "second" are used to indicate names and do not imply any particular order.

Claims

1. A method for classifying information, comprising: In response to receiving a publishing request for publishing information to be published, obtaining an object identifier of a target object for which publishing of the information to be published is requested, including: in response to receiving the publishing request for publishing the information to be published, detecting whether the target object has updated the object identifier in a first historical time period before a current moment; in response to the target object updating the object identifier in the first historical time period, obtaining the object identifier of the target object for which publishing of the information to be published is requested; At least combining the text recognition result of the object identifier and the text content of the information to be published to generate information to be classified; In response to the information to be classified not including target content of a preset type, classifying the information to be published as information of a target type, wherein the preset type is a content type for which the target object lacks publishing authority; In response to the information to be classified including the target content, the information to be published is classified as non-target type information.

2. The method according to claim 1, wherein The step of obtaining the object identifier of the target object for requesting to publish the information to be published in response to receiving the publishing request for publishing the information to be published comprises: In response to receiving a publishing request for publishing information to be published, reading text content of the information to be published; In response to the text content including key information pointing to the object identifier, the object identifier of the target object for which publishing of the information to be published is requested is obtained.

3. The method according to claim 2, further comprising: In response to the text content not including key information pointing to the object identifier, detecting whether the text content includes the target content; In response to the text content not including the target content, the to-be-published information is classified as information of the target type.

4. The method according to claim 1, wherein The target object has published historical information in a second historical time period before the current moment, and the step of combining at least the text recognition result of the object identifier and the text content of the information to be published to generate the information to be classified includes: The text content of the historical information, the text recognition result of the object identifier and the text content of the information to be released are combined to generate information to be classified.

5. The method according to claim 1, wherein The information to be published includes image content, and the text content of the information to be published includes a text recognition result of the image content.

6. A device for classifying information, comprising: The object identification acquisition unit is configured to, in response to receiving a publishing request for publishing information to be published, acquire the object identification of the target object for which the information to be published is requested to be published, including: in response to receiving the publishing request for publishing information to be published, detecting whether the target object has updated the object identification in a first historical time period before a current moment; and in response to the target object updating the object identification in the first historical time period, acquiring the object identification of the target object for which the information to be published is requested to be published; a unit for generating information to be classified, configured to combine at least the text recognition result of the object identifier and the text content of the information to be published to generate the information to be classified; a first information classification unit configured to classify the information to be published into information of a target type in response to the information to be classified not including target content of a preset type; The second information classification unit is configured to classify the information to be published as non-target type information in response to the information to be classified including target content.

7. An electronic device, comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 5.

8. A computer-readable medium having computer program instructions stored thereon, wherein the computer program instructions can be executed by a processor to implement the method according to any one of claims 1 to 5.

9. A computer program product comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 5.

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