Information processing method and system

Abstract

This specification provides an information processing method and system. The information processing method includes: performing information content detection on information to be interacted with to obtain interaction detection information, wherein the information to be interacted with is determined by a detection object targeting a service object; if the information to be interacted with passes content detection, sending the information to be interacted with to the service object, wherein the content detection result of the information to be interacted with is determined based on the interaction detection information; acquiring historical behavior information associated with the detection object and the service object; performing behavior detection on the detection object in at least one detection dimension based on the historical behavior information to obtain behavior detection information, and generating an interaction event based on the behavior detection information, wherein the interaction event is used to provide extended services to the detection object.

Description

Technical Field

[0001] The embodiments in this specification relate to the field of information processing technology, and in particular to information processing methods and systems. Background Technology

[0002] In e-commerce platform operations, merchants frequently violate service standards in areas such as customer service communication, fulfillment, and after-sales service (e.g., delayed responses, shirking responsibility, and failure to fulfill promises), easily leading to user complaints and financial losses, and damaging the overall experience of the e-commerce platform. Traditional quality inspection methods rely on manual sampling or user complaints, which suffer from drawbacks such as low problem coverage, slow response, and delayed intervention, resulting in the recurrence of similar problems and making it difficult to guarantee user experience. Therefore, there is an urgent need for a more effective information processing method to solve the above problems. Summary of the Invention

[0003] In view of the above, embodiments of this specification provide an information processing method. One or more embodiments of this specification also relate to an information processing system, an information processing apparatus, a computing device, a computer-readable storage medium, and a computer program product, to address the technical deficiencies existing in the prior art.

[0004] According to a first aspect of the embodiments of this specification, an information processing method is provided, comprising: Information content detection is performed on the information to be interacted to obtain interaction detection information, wherein the information to be interacted is determined by the target behavior of the detection object towards the service object; If the information to be interacted with passes content detection, the information to be interacted with is sent to the service object, wherein the content detection result of the information to be interacted with is determined based on the interaction detection information; Based on the historical behavior information, the detection object is subjected to behavior detection in at least one detection dimension to obtain behavior detection information, and an interaction event is generated based on the behavior detection information. The interaction event is used to provide extended services for the detection object.

[0005] According to a second aspect of the embodiments of this specification, an information processing system is provided, including a client and a server, comprising: The client is used to submit an object detection request to the server; The server is configured to respond to the object detection request by performing information content detection on the information to be interacted with, and obtaining interaction detection information, wherein the information to be interacted with is determined by the target behavior of the detection object towards the service object; if the information to be interacted with passes the content detection, the server sends the information to be interacted with to the service object, wherein the content detection result of the information to be interacted with is determined based on the interaction detection information; acquire historical behavior information associated with the detection object and the service object; perform behavior detection on the detection object in at least one detection dimension based on the historical behavior information, obtain behavior detection information, and generate an interaction event based on the behavior detection information, wherein the interaction event is used to provide extended services for the detection object, and send the behavior detection information and the interaction event information of the interaction event to the client.

[0006] According to a third aspect of the embodiments of this specification, an information processing apparatus is provided, comprising: The detection module is configured to detect the information content of the information to be interacted with and obtain interaction detection information, wherein the information to be interacted with is determined by the target behavior of the detection object towards the service object; The sending module is configured to send the interactive information to the service object when the interactive information passes the content detection, wherein the content detection result of the interactive information is determined based on the interaction detection information; The acquisition module is configured to acquire historical behavior information associated with the detection object and the service object; The generation module is configured to perform behavior detection on the detection object in at least one detection dimension based on the historical behavior information, obtain behavior detection information, and generate interaction events based on the behavior detection information. The interaction events are used to provide extended services for the detection object.

[0007] According to a fourth aspect of the embodiments of this specification, a computing device is provided, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the above-described information processing method.

[0008] According to a fifth aspect of the embodiments of this specification, a computer-readable storage medium is provided that stores computer-executable instructions, which, when executed by a processor, implement the steps of the information processing method described above.

[0009] According to a sixth aspect of the embodiments of this specification, a computer program product is provided, including a computer program or instructions that, when executed by a processor, implement the steps of the information processing method described above.

[0010] This specification provides an embodiment of an information processing method that performs content detection on information to be interacted with to obtain interaction detection information. The information to be interacted with is determined by the target behavior of the detection object towards the service object. If the information to be interacted with passes content detection, it is sent to the service object to ensure that the information sent to the service object is compliant with content requirements, thus achieving pre-detection before sending the information to the service object. The content detection result of the information to be interacted with is determined based on the interaction detection information. Historical behavior information of the associated detection object and service object is obtained. Based on the historical behavior information, behavior detection is performed on the detection object in at least one detection dimension to obtain behavior detection information. This enables behavior detection of the detection object after sending the information to be interacted with to the service object, ensuring the compliance of the detection object's behavior. An interaction event is generated based on the behavior detection information. The interaction event is used to provide extended services to the detection object. Through pre-detection of information content and post-detection of object behavior, the behavior of the detection object is standardized, ensuring the service experience of the service object and improving the service satisfaction of the service object. Attached Figure Description

[0011] Figure 1 This is a flowchart illustrating an information processing method provided in one embodiment of this specification; Figure 2 This is a flowchart illustrating the processing procedure of an information processing method provided in one embodiment of this specification. Figure 3 This is a flowchart illustrating the detection process of an information processing method provided in one embodiment of this specification; Figure 4 This is a schematic diagram of the structure of an information processing system provided in one embodiment of this specification; Figure 5 This is an architecture diagram of an information processing system provided in one embodiment of this specification; Figure 6 This is a schematic diagram of the structure of an information processing device provided in one embodiment of this specification; Figure 7 This is a structural block diagram of a computing device provided in one embodiment of this specification. Detailed Implementation

[0012] Many specific details are set forth in the following description to provide a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this specification. Therefore, this specification is not limited to the specific implementations disclosed below.

[0013] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of this specification. The singular forms “a,” “described,” and “the” as used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0014] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this specification, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0015] Furthermore, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties. Moreover, the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0016] The technical solutions provided in this application can employ deep learning models with relatively large parameter scales. However, this large model is merely an example; this application does not limit the number of model parameters supported by the deep learning model used, aiming to meet actual needs. The deep learning models involved in this application can be artificial intelligence-based language models (LM) or multimodal models (MM).

[0017] First, the terms and concepts used in one or more embodiments of this specification will be explained.

[0018] Merchant Quality Inspection Service Standards: These are the code of conduct that merchants must follow in customer service communication, contract fulfillment, and after-sales service. They cover core dimensions such as buyer semantic recognition, high-risk scenario identification, negative feedback response, customer service reception quality, and compliance with commitments.

[0019] Multi-stage intelligent intervention: Based on AI models, the interaction process between merchants and users is divided into "pre-event (before the message is sent)" and "post-event (after the message is sent)" stages. Violations are identified in real time, and tiered handling actions such as interception, warning, and compensation are automatically triggered.

[0020] Automatic compensation: After confirming that a merchant has violated service standards (such as customer service failing to respond within a time limit or failing to effectively resolve user issues), the platform will automatically issue platform experience compensation rights as immediate reassurance without requiring the user to file a complaint.

[0021] Invitation to Review: When a user is detected to be experiencing service abnormalities or difficulties, a review alert is sent to the merchant, and a service review invitation is automatically pushed after a preset time window to encourage the merchant to proactively close the loop on problems and improve the user experience.

[0022] Cumulative Mechanism: Repeated violations of service standards by the same merchant within a set period will be counted cumulatively. When the threshold is reached, upgraded governance measures such as credit score deduction and marketing permission restriction will be automatically triggered.

[0023] Experience Score: A dynamic credit indicator used by the platform to quantify a merchant's comprehensive service capabilities. It is built based on actual user feedback and behavioral data during the service process and directly affects its traffic allocation, activity access, and platform resource support.

[0024] To address the aforementioned technical problems, this specification provides an information processing method. This specification also relates to an information processing system, an information processing apparatus, a computing device, a computer-readable storage medium, and a computer program product, which will be described in detail in the following embodiments.

[0025] See Figure 1 , Figure 1 A flowchart of an information processing method according to an embodiment of this specification is shown, which specifically includes the following steps.

[0026] Step 102: Perform information content detection on the information to be interacted with to obtain interaction detection information, wherein the information to be interacted with is determined by the target behavior of the detection object towards the service object.

[0027] Specifically, the detection target can be the service provider, and the service recipient can be the party receiving the service. In the case of the detection target being a store's customer service providing online services, the service recipient can be the buyer, i.e., the consumer. The information to be interacted with refers to the information that the detection target will send to the service recipient. This information can be dialogue information, service cards (such as service cards with information collection functions used to collect information from the service recipient), or resource-providing service cards used to provide or send resources to the service recipient. The purpose of detecting the content of the information to be interacted with is to detect whether it contains information that affects the service recipient's service experience, such as information that maliciously attacks the service recipient. Interaction detection information can be keywords expressing intent or semantics detected in the information to be interacted with, or it can be a summary of the information to be interacted with.

[0028] Based on this, before the detection object interacts with the service object, the interaction information to be sent by the detection object to the service object is determined. That is, the interaction information to be sent by the detection object to the target behavior of the service object is obtained. Before the detection object sends the interaction information to the service object, the information content of the interaction information is detected to obtain the interaction detection information representing the interaction intent, interaction semantics and other information of the interaction information.

[0029] Furthermore, considering that the information to be interacted with is information that the detection object will send to the service object, in order not to affect the interaction experience of the service object, the information to be interacted with can be detected in at least one detection dimension before being sent to the service object to obtain interaction detection information. The specific implementation is as follows: The information processing model is used to detect the information content of the information to be interacted with in the dimensions of preset keywords and / or preset information types, so as to obtain the interaction detection information.

[0030] Specifically, the information processing model can be a large language model used for content detection of the information to be interacted with. This involves extracting keywords from the information or detecting the information type to obtain interaction detection information. Preset keywords can be pre-defined non-compliant keywords, such as words containing abusive connotations; preset information types can be pre-defined information content types, such as promises, shirking responsibility, and sharp-tongued statements. Interaction detection information can include keywords extracted from the information to be interacted with, as well as information types such as promises, shirking responsibility, and sharp-tongued statements obtained from summarizing the interaction information.

[0031] Based on this, an information processing model is used to detect the content of the information to be interacted with using preset keywords and / or preset information types, thereby obtaining interaction detection information. This interaction detection information may include target keywords obtained from keyword detection of the information to be interacted with, and may also include the information type of the information to be interacted with, determined by matching the information to be interacted with based on preset information types. The information to be interacted with can be dialogue text or images containing semantic meaning, such as images or emoticons representing greetings.

[0032] For example, in an e-commerce scenario, the detection target could be the merchant's customer service or the e-commerce platform's customer service. The interaction target is the service recipient of the e-commerce platform or merchant, i.e., the consumer corresponding to the e-commerce platform or merchant. The information to be interacted with is the information that customer service is about to send to the consumer. During the online interaction between customer service and the consumer, before the customer service sends the information to be interacted with, the e-commerce platform's server can obtain the information to be interacted with and detect its content. Keywords such as "hello" and "question" can be extracted from the information "Hello, how can I help you?". Alternatively, the information type of the information to be interacted with can be detected based on a preset information type. If the type of the information to be interacted with matches the preset information type "greeting," then "greeting," "hello," and "question" are used as the interaction detection information.

[0033] In summary, by using an information processing model to detect the content of the interactive information in terms of preset keywords and / or preset information types, the model performs preliminary keyword extraction and information type matching on the interactive information, and extracts key information from the interactive information to facilitate subsequent compliance testing of the interactive information.

[0034] Step 104: If the information to be interacted passes the content detection, the information to be interacted is sent to the service object, wherein the content detection result of the information to be interacted is determined based on the interaction detection information.

[0035] Step 106: Obtain historical behavior information associated with the detection object and the service object.

[0036] Specifically, after performing information content detection on the information to be interacted and obtaining interaction detection information, i.e., if the information to be interacted passes the content detection, the information to be interacted is sent to the service object. The content detection result of the information to be interacted is determined based on the interaction detection information. Historical behavior information associated with the detection object and the service object is obtained. Content detection is used to detect whether the information to be interacted conforms to the information interaction specifications. Its purpose is to detect whether the information to be interacted contains words that affect the service experience of the service object, and whether the intent and semantics corresponding to the information to be interacted will affect the service experience of the service object. The content detection result of the information to be interacted is the identification result of whether the interaction detection information contains words that affect the service experience of the service object. The content detection result of the information to be interacted can also be the judgment result of whether the interaction detection information involves semantics or intent that affect the service object. The interaction detection information is detected in terms of keywords, interaction intent, and interaction semantics. If it is determined that the interaction detection information does not contain keywords that affect the service experience of the service object, and the interaction intent and interaction semantics in the interaction detection information conform to the interaction specifications, the information to be interacted is determined to have passed the content detection. Historical behavioral information refers to the interaction behaviors corresponding to the detection object and the service object respectively, such as the interval between the detection object's response to the service object's questions, the service object's continuous follow-up questions, the service object's repeated inquiries, and the detection object's failure to provide closing remarks or opening remarks.

[0037] Based on this, after performing information content detection on the information to be interacted and obtaining interaction detection information, if it is determined that the information to be interacted has passed the content detection based on the interaction detection information, it means that there is no information in the information to be interacted that affects the service experience of the service object. The information to be interacted can then be sent to the service object, and the historical behavior information of the associated detection object and the service object can be obtained. The interaction methods corresponding to the historical behavior information include, but are not limited to, text dialogue interaction and voice dialogue interaction (audio data).

[0038] Furthermore, considering the possibility that the interactive information may fail content detection based on the interaction detection information, and since the interactive information fails content detection, indicating that the interactive information corresponds to at least one non-compliance issue, a compliance prompt can be generated based on the identified at least one non-compliance issue to indicate that the content of the interactive information is non-compliant. The specific implementation is as follows: If, based on the interaction detection information, it is determined that the information to be interacted with has failed content detection, a compliance prompt is generated based on the information to be interacted with and the interaction detection information; the compliance prompt is displayed on the interaction information page corresponding to the detection object, and the compliance information is used to prompt the detection object to perform compliance processing on the information to be interacted with.

[0039] Specifically, if the information to be interacted fails content detection, it means that the information contains content that does not comply with the interaction content specifications, or that the information or intent expressed in a way that does not conform to the interaction content specifications. Failure to pass content detection indicates that the information will have a negative impact on the service recipient, reducing their user experience. The compliance notification informs the testing recipient that the compliance detection result for the information to be interacted is non-compliant or has failed the compliance detection, explains the reason for the non-compliance, and prompts the testing recipient to handle the information to ensure compliance. The interaction information page corresponding to the testing recipient is the visual page for the interaction between the testing recipient and the service recipient.

[0040] Therefore, if the interaction information fails content detection based on the interaction detection information, it indicates that the interaction information is non-compliant. Sending the interaction information to the service recipient would reduce the service experience and increase the risk of the service recipient filing a complaint. A compliance prompt message is generated based on the interaction information and the interaction detection information, including the compliance detection result, the reason for non-compliance, and rectification suggestions. This compliance prompt message is displayed on the interaction information page corresponding to the tested object, prompting the tested object to handle the interaction information in compliance. The compliance prompt message can be displayed as a pop-up window on the interaction information page. The display of the compliance prompt message on the interaction information page corresponding to the tested object indicates that the server has intercepted the interaction information and will not send it to the service recipient.

[0041] Continuing with the previous example, if the interaction detection information contains "abusive keywords," it means the interaction information failed content detection, and the server will block it, preventing it from being sent to the user. Based on the interaction detection information and the interaction information to be sent, a compliance warning message is generated: "The interaction information contains sensitive words and has been blocked. It is recommended to modify the sensitive words before sending it." This compliance warning message is displayed on the customer service representative's (the user being detected) chat page, i.e., the interaction information page. The compliance warning message is used to prompt customer service to modify the interaction information as soon as possible before sending it to the consumer (the user being detected).

[0042] In summary, displaying compliance prompts on the interactive information page corresponding to the tested object serves to remind the tested object to process the interactive information in compliance with regulations, thus avoiding sending interactive information that has not passed compliance testing to the service object and preventing negative impacts on the service object.

[0043] Furthermore, the historical behavioral information associated with the detection object and the service object includes not only the interaction information generated by the interaction between the detection object and the service object, but also the dialogue information between the service object and the detection object, as specifically implemented as follows: Obtain the dialogue information and interaction behavior information associated with the detection object and the service object; use the dialogue information and interaction behavior information as the historical behavior information.

[0044] Specifically, dialogue information refers to the dialogue information between the detection object and the interaction object before the detection object sends the information to be interacted with to the service object. Dialogue information can be timestamped dialogue information collected from the detection object and the service object within a preset time period. The preset time period can be set according to information acquisition needs, such as 24 hours prior to the generation time of the information to be interacted with. Interaction behavior information is descriptive information about the interaction behavior between the detection object and the service object. Interaction behavior includes, but is not limited to, work order push, call transfer, coupon distribution, silence duration, interrupting / interrupting the dialogue, etc.

[0045] Based on this, the dialogue information and interaction behavior information of the associated detection object and service object are obtained. The dialogue information includes at least two historical dialogues with timestamps. The interaction behavior information consists of the service operations provided by the detection object to the service object. The dialogue information and interaction behavior information are treated as historical behavior information.

[0046] Continuing with the previous example, the dialogue information between the detection object and the service object refers to the content of voice or text communication between them. Dialogue information includes, but is not limited to, chat logs, email exchanges, voice content, speech-to-text transcription, and dialogue semantics and intent between online customer service and consumers. Interaction behavior information refers to the process characteristics and metadata of communication between customer service and consumers, i.e., "how customer service and customers interact." It describes the background, method, and rhythm of the dialogue, including but not limited to time indicators, communication rhythm and pattern, semantics and status signals, and operational and procedural actions. Time indicators include, but are not limited to, response time (the interval between customer service replies to customer messages); silence time (the blank time during a call or online conversation where neither party speaks); and total processing time (the total time spent resolving a single problem or session). Communication rhythm and pattern include, but are not limited to, interruptions / interruptions, and continuous follow-up questions. Semantic and status signals include, but are not limited to, semantic tendencies and voice characteristics, such as speech rate, volume, and tone changes during a call, which reflect the speaker's semantics and attitude. Operational and procedural actions include, but are not limited to, transfer records and work order operations. Dialogue information and interaction behavior information are treated as historical behavior information.

[0047] In summary, by treating dialogue information and interaction behavior information as historical behavior information, subsequent behavior detection of the detected object can be performed on the dialogue interaction dimension and the interaction operation dimension, thereby improving the comprehensiveness of behavior detection of the detected object.

[0048] Step 108: Based on the historical behavior information, perform behavior detection on the detection object in at least one detection dimension to obtain behavior detection information, and generate an interaction event based on the behavior detection information. The interaction event is used to provide extended services for the detection object.

[0049] Specifically, after obtaining the historical behavior information of the associated detection objects and service objects, behavior detection can be performed on the detection objects in at least one detection dimension based on the historical behavior information to obtain behavior detection information. Interaction events are then generated based on this behavior detection information. These interaction events provide extended services to the detection objects. Here, "at least one detection dimension" refers to at least one behavior detection dimension used to perform behavior detection on the detection objects based on historical behavior information. That is, the service behavior of the detection objects towards the service objects can be determined based on the historical behavior information. Behavior detection is a compliance check of the service behavior of the detection objects. The behavior detection information is the compliance of the behavior of the detection objects determined based on the historical behavior information. If the historical behavior information determines that the service behavior of the detection objects towards the service objects is "no response to the service objects for a long time," the behavior detection information is "response timeout." Interaction events are generated for non-compliant behaviors corresponding to the behavior detection information and are service compensation events initiated by the service objects, such as issuing coupons to provide service compensation.

[0050] Based on this, after obtaining the historical behavior information of the associated detection objects and service objects, the detection objects are subjected to behavior detection in at least one detection dimension based on the historical behavior information to obtain behavior detection information. If the behavior detection information indicates that the detection object has non-compliant behavior, an interaction event is generated based on the behavior detection information. The interaction event is used to provide extended services to the detection object, which may be compensation for the non-compliant behavior of the detection object. If the behavior detection information indicates that the detection object does not have non-compliant behavior, the interaction event can be used to provide a service evaluation portal for service objects, so that service objects can provide service quality feedback through the service evaluation portal.

[0051] Furthermore, after determining the historical behavior information, behavior detection can be performed on this information. Behavior detection is conducted on the historical behavior information in at least one detection dimension to ensure comprehensive detection of the behavior of the detection object towards the service object. The specific implementation is as follows: The at least one detection dimension is determined to include an object semantic dimension, an interaction scenario dimension, an object feedback dimension, and / or a detected object behavior dimension; the behavior detection model is used to perform behavior detection on the detected object in the object semantic dimension, the interaction scenario dimension, the object feedback dimension, and / or the detected object behavior dimension, respectively, based on the historical behavior information, to obtain the behavior detection information.

[0052] Specifically, the object semantic dimension is used to detect the semantics of the service object and the detection object, and to detect historical behavior information in the object semantic dimension, such as detecting whether the historical behavior information contains keywords that affect service quality. The interaction scenario dimension is used to detect the interaction scenarios between the service object and the detection object, such as service object security scenarios. The object feedback dimension is used to detect the service object's product experience feedback, complaints, reports, etc. The detection object behavior dimension can be the detection object's commitment behavior, such as: commitment to resend, commitment to change address, commitment to change contact information, etc. The behavior detection model can be a large language model, used to detect the quality of the service provided by the detection object to the service object. The behavior detection model can be a set of behavior detection models, including but not limited to the upgrade large model (buyer semantics, high-risk scenarios, buyer feedback), the commitment large model (customer service commitment), the service attitude large model (customer service reception - service attitude), and the long-term no-response large model (customer service reception - violation and negligence).

[0053] Based on this, at least one detection dimension is defined, encompassing the object semantic dimension, interaction scenario dimension, object feedback dimension, and / or the detected object behavior dimension. Behavior detection models are used to perform behavior detection on the detected object across these dimensions using historical behavior information, obtaining behavior detection information. The set of behavior detection models includes, but is not limited to, a large-scale upgrade model, a large-scale commitment model, a large-scale service attitude model, and a large-scale model for long-term non-response, used for accurate behavior detection across each dimension.

[0054] In practical applications, in addition to the object semantic dimension, interaction scenario dimension, object feedback dimension and / or the detected object behavior dimension, at least one detection dimension can be customized according to the needs of the detected object. For example, adding or deleting detection dimensions can provide the detected object with the function of editing and managing detection dimensions, so that the detected object can customize the detection dimensions according to its needs and realize personalized adjustment of the detection dimensions.

[0055] Continuing with the previous example, at least one detection dimension includes, but is not limited to, buyer semantics, high-risk scenarios, buyer feedback, customer service reception, and customer service commitments. Buyer semantics (object semantic dimension) primarily uses algorithms to detect semantic anomalies in buyer conversations. High-risk scenarios (interaction scenario dimension) primarily uses algorithms to detect whether buyer statements contain excessive behavior or indicate potential personal injury, such as a buyer expressing a desire to harm themselves or a safety incident occurring after purchasing the product. Buyer feedback (object feedback dimension) primarily uses algorithms to detect whether buyer statements contain complaints, reports, or product experience issues. Customer service reception (detection object behavior dimension) primarily uses algorithms to detect whether customer service statements contain issues related to service attitude, sales ability, basic compliance, or violations / misconduct. Customer service commitments (detection object behavior dimension) primarily uses algorithms to detect whether customer service statements contain promises to resend items, change addresses, or modify contact information. The behavioral detection model set includes, but is not limited to, the upgraded large model (buyer semantics, high-risk scenarios, buyer feedback), the commitment large model (customer service commitment), the service attitude large model (customer service reception - service attitude), and the long-term no-response large model (customer service reception - violations and mistakes). These models are used to conduct targeted detection of historical behavioral information.

[0056] In summary, by using a behavior detection model to perform behavior detection on the detected object in the dimensions of object semantics, interaction scenario, object feedback, and / or detected object behavior, behavior detection information can be obtained, ensuring comprehensive detection of historical behavior information and ensuring the accuracy of behavior detection information.

[0057] Furthermore, when behavioral detection information determines that a monitored object has non-compliant behavior, an early warning event can be generated in a timely manner to issue a warning about the monitored object's behavior. At the same time, evaluation information is collected from service recipients to promptly gather their service feedback. The specific implementation is as follows: Based on the behavior detection information, an early warning event is generated for the detected object, and behavioral early warning information is generated based on the early warning event; the behavioral early warning information is displayed on the interactive page corresponding to the detected object, and evaluation collection information is sent to the service object.

[0058] Specifically, early warning information refers to the alert information generated for a monitored object when its behavior is determined to be non-compliant based on behavioral detection information. This alert serves to the monitored object regarding non-compliant behavior and to indicate that service feedback information will be collected from the service recipient. Evaluation collection information can be evaluation cards, used to collect feedback from service recipients regarding the services provided by the monitored object. Evaluation collection information also represents an invitation to the service recipient to evaluate the services provided by the monitored object, providing an entry point for the service recipient to evaluate the services offered by the monitored object. The interactive page corresponding to the monitored object can be the page the monitored object is currently on, or it can be the monitored object's message notification page.

[0059] Based on this, early warning events are generated for the monitored objects using behavior detection information, used to warn of non-compliant interactive behaviors of the monitored objects. Behavioral early warning information is generated based on these early warning events and displayed on the corresponding interactive page of the monitored object in a visual manner. Furthermore, evaluation information for the interactive services provided by the monitored object is sent to the service recipients. This evaluation information can be an evaluation invitation card, providing the service recipients with an evaluation entry point to assess the services provided by the monitored object.

[0060] Continuing with the previous example, if non-compliant behavior is identified by the behavior detection information, the non-compliant behavior of "response timeout" can be determined based on the behavior detection information. A warning event can be generated for the merchant's "response timeout" behavior; that is, a warning message "Timeout warning, consumer invited to provide service evaluation" is generated and sent to the merchant, displayed as a pop-up on the merchant's interaction page. Simultaneously, an invitation card is sent to the consumer to provide evaluation, collecting the consumer's genuine feedback on the service provided or the merchant's behavior. Alternatively, after issuing the warning to the merchant, a delay of N minutes (N can be set to any value according to actual needs) can be triggered to send the consumer evaluation card, guiding customer service to resolve the consumer's problem (related to customer service satisfaction).

[0061] In summary, behavioral warning information is generated based on warning events and displayed on the interactive page corresponding to the monitored object. The warning information is presented to the monitored object in a visual way, and the evaluation information of the interactive services provided to the monitored object is sent to the service object. The evaluation entry point is provided to the service object in real time, ensuring that high-quality services are provided to the service object.

[0062] Furthermore, the behavior detection information includes the detection results of the behavior of the detected object, as well as the detection results of the behavior of the service object. Based on the behavior detection information, at least one type of interaction event can be generated for the service object to provide extended services. The specific implementation is as follows: Based on the behavior detection information, evaluation events, compensation events, and / or prompt events are generated, and the evaluation events, compensation events, and / or prompt events are used as the interaction events.

[0063] Based on this, evaluation events, compensation events, and / or prompt events are generated using behavior detection information. Evaluation events can be generated for the service recipient, used to collect evaluation information about the services provided by the detected object. Compensation events can be generated for the service recipient, used to compensate for service deficiencies, such as issuing coupons or providing resource compensation. Prompt events can be generated for the service recipient, used to prompt them to retain evidence of service non-compliance. Evaluation events, compensation events, and / or prompt events are treated as interactive events.

[0064] In summary, by treating evaluation events, compensation events, and / or notification events as interaction events, we can ensure the rights and interests of service users as much as possible, provide them with a better service experience, and improve their retention rate.

[0065] Furthermore, considering that the interaction behavior of the monitored object with the service object is related to the service object's service satisfaction, in order to avoid the monitored object continuously providing low-quality service to the service object, the service of the monitored object can be scored and accumulated based on the behavior monitoring information. This score can be used to constrain the service behavior of the monitored object and encourage the monitored object to provide high-quality service to the service object. The specific implementation is as follows: Based on the behavior detection information, a rating record information for the detected object is generated, and a rating information is generated based on historical rating information and the rating record information; if it is determined based on the rating information that the detected object does not meet the operating conditions, operating restriction information is generated for the detected object, and the operating restriction information is sent to the detected object.

[0066] Specifically, the rating record information is the service rating obtained by the tested entity for the services provided to the service recipient. The rating record information can be positive or negative. If the tested entity fails the behavior detection based on the behavior detection information, the rating record information can be negative (e.g., -2 points), meaning that the tested entity's credit score or service score is deducted from its existing rating (historical rating information). If the tested entity passes the behavior detection based on the behavior detection information, the rating record information can be positive (e.g., +2 points), meaning that the tested entity's credit score or service score is added to its existing rating (historical rating information). Operating conditions can correspond to a rating threshold. If the rating information is below the threshold, it indicates that the tested entity does not meet the operating conditions; if the rating information is above the threshold, it indicates that the tested entity meets the operating conditions. Operating restriction information can restrict the operating rights of the merchant corresponding to the tested entity. Operating rights include, but are not limited to, the right to add new products, add new services, and operating duration.

[0067] Based on this, a rating record is generated for the monitored object using behavioral detection information. This record records the service rating the monitored object provides to the service recipient in this instance. A final rating is generated based on historical rating information and the rating record, accumulating the service rating based on historical data—that is, increasing or decreasing the service rating. If the rating record shows a negative score, the score is subtracted from the historical score; if the rating record shows a positive score, the score is added to the historical score. If the rating information determines that the monitored object does not meet the operating conditions (meaning the rating is below the threshold corresponding to the operating conditions), then operating restriction information is generated for the monitored object and sent to it, thereby imposing operating restrictions on the monitored object or its corresponding business entity.

[0068] In practical applications, historical rating information can represent the deducted points. When the rating record shows negative scores, the rating information becomes the accumulation of negative points, and the operating condition becomes the negative score threshold. When the rating information is greater than or equal to the negative score threshold, it indicates that the detected entity has reached a trigger point, and the corresponding merchant will be restricted from continuing operations, such as by limiting product postings and account permissions. For example, a deduction of 12 points will directly restrict the merchant from posting products and participating in marketing activities, thus ensuring the operational order of the platform.

[0069] Continuing with the previous example, during a merchant's operation, a score is accumulated based on their performance. A merchant's score must meet certain operating conditions to continue operating normally. After generating the score record information for the monitored object based on behavioral detection information, it is accumulated based on the merchant's historical score information. If the behavioral detection information determines that the monitored object has engaged in non-compliant interactive behavior, the score record information will be negative, such as -2 points. If the historical score information is 10 points, subtracting 2 points from 10 points will result in a score of 8 points. If the operating condition requires a score threshold of 9 points, since the score information is below the threshold, the merchant no longer meets the operating conditions, and operating restrictions will be imposed.

[0070] In summary, when it is determined from the scoring information that the tested entity does not meet the operating conditions, operating restriction information is generated for the tested entity and sent to the tested entity. This informs the tested entity that its operating rights are restricted, urges the tested entity to make rectifications, and ensures that the tested entity can provide high-quality services to the service recipients.

[0071] This specification provides an embodiment of an information processing method that acquires the interaction information to be determined by a detection object in response to a target behavior of a service object, and performs information content detection on the interaction information to obtain interaction detection information. If the interaction information determines that the interaction information passes content detection, the interaction information is sent to the service object to ensure that the information sent to the service object is content-compliant, thus achieving pre-detection before sending the interaction information to the service object. Historical behavior information of the associated detection object and service object is acquired, and behavior detection is performed on the detection object in at least one detection dimension based on the historical behavior information to obtain behavior detection information, enabling behavior detection of the detection object after sending the interaction information to the service object to ensure the compliance of the detection object's behavior. An interaction event is generated based on the behavior detection information. The interaction event is used to provide extended services to the detection object. Through pre-detection information content detection and post-detection object behavior detection, the behavior of the detection object is standardized, ensuring the service experience of the service object and improving the service satisfaction of the service object.

[0072] The following is in conjunction with the appendix Figure 2 Taking the application of the information processing method provided in this specification in merchant service quality inspection as an example, the information processing method will be further explained. Figure 2 A flowchart illustrating the processing steps of an information processing method provided in one embodiment of this specification is shown, specifically including the following steps.

[0073] Step 202: Obtain the interaction information determined by the detection object for the target behavior of the service object, and perform information content detection on the interaction information to obtain interaction detection information.

[0074] In practical applications, the detection target is the merchant or their customer service, used to assess the service quality of the merchant or customer service. The service recipient is the user of the e-commerce platform, i.e., the consumer. The target behavior of the service recipient can be initiating after-sales or inquiry events. The information to be interacted with refers to the information that the merchant or customer service will respond to in response to the after-sales or inquiry events initiated by the consumer, such as: greetings, inquiries about the purpose of the inquiry, or order inquiries. The purpose of content detection of the information to be interacted with is to detect the interaction intent and to perform keyword detection. The interaction detection information can be the results of compliance detection of the information to be interacted with, such as: determination of whether it contains sensitive words, determination of customer service semantics, etc.

[0075] In specific implementation, such as Figure 3 As shown, when a user initiates an after-sales or inquiry event with the merchant (customer service), the merchant responds to the user's inquiry or after-sales issue. Before sending the merchant's response to the user, real-time content quality checks are performed to determine whether to intercept the merchant's response.

[0076] Step 204: If it is determined from the interaction detection information that the information to be interacted with has failed the content detection, generate a compliance prompt message based on the information to be interacted with and the interaction detection information.

[0077] Step 206: Display the compliance prompt information on the interactive information page corresponding to the object being tested. The compliance information is used to prompt the object being tested to process the interactive information in compliance.

[0078] In practical applications, if the content to be interacted fails content detection, it means that the merchant's reply contains sensitive words, such as insults, malicious attacks, or other offensive language. The compliance notification is a reminder to the merchant that their reply to the user is non-compliant and has been blocked; the merchant needs to adjust it before resubmitting. The interaction page being checked can be the dialogue page between the merchant and the user.

[0079] Step 208: If the interaction information determines that the information to be interacted has passed the content detection, the interaction information is sent to the service object, and the historical behavior information of the associated detection object and the service object is obtained.

[0080] In practice, if the information to be interacted with passes content detection, it means that the merchant's response does not contain sensitive words and is considered compliant information, which can be directly sent to the user. Historical behavioral information of the associated detection object and service object includes, but is not limited to, timestamped conversations and link sharing between the merchant (customer service) and the user.

[0081] Step 210: Based on historical behavior information, perform behavior detection on the detection object and service object in at least one detection dimension to obtain behavior detection information.

[0082] In practical applications, at least one detection dimension corresponds to a service specification quality inspection point, including but not limited to buyer semantics, high-risk scenario, buyer feedback, customer service reception, and customer service commitment detection dimensions. Specifically, buyer semantics primarily uses algorithms to detect semantic anomalies in buyer conversations. High-risk scenario detection primarily uses algorithms to detect whether buyer statements involve excessive behavior or personal injury, such as safety incidents after product purchase. Buyer feedback detection primarily uses algorithms to detect whether buyer statements involve complaints, reports, or product experience issues. Customer service reception detection primarily uses algorithms to detect whether customer service statements involve issues with service attitude, sales skills, basic standards, or violations / misconduct. Customer service commitment detection primarily uses algorithms to detect whether customer service statements include promises to resend items, change addresses, or modify contact information. The behavioral detection information represents the quality inspection results corresponding to the buyer semantics, high-risk scenario, buyer feedback, customer service reception, and customer service commitment detection dimensions, respectively.

[0083] Step 212: Generate interaction events corresponding to the service object based on the behavior detection information. Service extension events are used to provide extended services to the service object.

[0084] Based on the quality inspection results, interactive events can be generated for users in real time. These interactive events can include inviting users to comment or automatic compensation.

[0085] Step 214: Generate early warning events for the detected objects based on the behavior detection information, and generate behavior early warning information based on the early warning events.

[0086] In practical applications, the warning events for monitored objects are used to alert merchants to non-compliant behaviors. Warning events can be to-do orders, card reminders, etc. Behavioral warning information can be a notification sent to the merchant indicating non-compliant behavior.

[0087] Step 216: Display the behavior warning information on the interactive page corresponding to the detected object, and send the evaluation collection information to the service object.

[0088] Behavioral alerts can be displayed as pop-ups on the merchant's currently viewed page or in the chat window between the merchant and the user. After issuing an alert to the merchant, a feedback card can be sent to the user after a delay of N minutes, inviting the customer service representative to resolve the consumer's issue (user satisfaction with customer service directly impacts the representative's performance score).

[0089] Step 218: Generate rating record information for the detected object based on the behavior detection information, and generate rating information based on historical rating information and rating record information.

[0090] In practical applications, rating records can be scores based on a merchant's interactive behavior, such as adding or deducting experience points. Historical rating information can be the experience points that a merchant has already deducted. Generating rating information based on historical and rating record information means that when non-compliant behavior is determined to exist in a merchant, experience points will continue to be deducted from the merchant's already deducted experience points. The rating information represents the accumulated score after deducting experience points.

[0091] Step 220: If it is determined from the scoring information that the test object does not meet the operating conditions, generate operating restriction information for the test object and send the operating restriction information to the test object.

[0092] Operating conditions could include a threshold for deducting experience points. If a merchant's accumulated experience points exceed the threshold (e.g., 12 points), restrictions could be placed on the merchant's operations, such as limiting product listings or account permissions.

[0093] In addition, it provides merchants with an intelligent quality inspection backend, which allows them to manage quality inspection points and view real-time quality inspection detection information, accuracy information, quality inspection intervention information, and cumulative penalty information.

[0094] The information processing method provided in this embodiment combines pre-emptive interception with post-event quality inspection. Through multi-stage intelligent intervention, it achieves quality inspection of both merchants and users, ensuring service quality and user experience. For merchants, high-risk content is identified and blocked in real time before messages are sent, and full compliance judgment is completed within milliseconds after sending, breaking through the traditional "post-event sampling inspection" model and achieving proactive prevention and control of service risks. An automated closed-loop handling mechanism of "identification—compensation—invitation for comments—governance" is constructed, which can automatically trigger user experience compensation, delayed invitation for comments, and violation records without user complaints, transforming single service issues into traceable, manageable, and sustainable governance events. A dynamic hierarchical penalty accumulation mechanism based on cumulative counting is designed to periodically accumulate repeated violations by merchants and link them with credit scores and business permissions, achieving a governance upgrade from "one-time warning" to "long-term constraint".

[0095] In summary, the information processing method provided in this embodiment upgrades the traditional manual sampling inspection (coverage <5%) to AI-powered real-time full-volume quality inspection, achieving 100% coverage and reducing the latency of violation identification from hours to seconds. This improves the coverage and real-time performance of violation identification. By proactively blocking high-risk language and automatically compensating afterward, it reduces the dispute rate and compensation costs caused by service issues, with actual tests showing a reduction of over 30% in related customer complaints, significantly reducing platform financial losses. Users receive immediate compensation and feedback guidance without actively filing complaints after an issue occurs, enhancing the consumer experience. The "early warning + invited review + cumulative deduction" mechanism encourages merchants to proactively optimize their services during conversations, reducing the repeat violation rate by over 40% and improving merchants' self-motivation for compliance. The quality inspection and handling process requires no manual intervention, allowing for the processing of a large number of conversations per day, reducing labor costs by 70%, and enabling the governance strategy to be quickly replicated across multiple task scenarios. This achieves automation and scalability of platform governance. By dynamically linking merchants' service behavior data with their experience scores, credit scores can more accurately reflect the quality of merchants' services, improve the accuracy of traffic allocation and resource support, and strengthen the closed loop of the platform's credit system.

[0096] This specification provides an embodiment of an information processing method that performs content detection on information to be interacted with to obtain interaction detection information. The information to be interacted with is determined by the target behavior of the detection object towards the service object. If the information to be interacted with passes content detection, it is sent to the service object to ensure that the information sent to the service object is compliant, thus achieving pre-detection before sending the information to the service object. The content detection result of the information to be interacted with is determined based on the interaction detection information. Historical behavior information of the associated detection object and service object is obtained, and behavior detection is performed on the detection object in at least one detection dimension based on the historical behavior information to obtain behavior detection information. This achieves behavior detection of the detection object after sending the information to be interacted with to the service object, ensuring the compliance of the detection object's behavior. An interaction event is generated based on the behavior detection information. The interaction event is used to provide extended services to the detection object. Through pre-detection of information content and post-detection of object behavior, the behavior of the detection object is standardized, ensuring the service experience of the service object and improving the service satisfaction of the service object.

[0097] Corresponding to the above method embodiments, this specification also provides information processing system embodiments. Figure 4 A schematic diagram of the structure of an information processing system according to one embodiment of this specification is shown. Figure 4As shown, the information processing system 400 includes a client 410 and a server 420. The client 410 is used to submit an object detection request to the server 420. The server 420 is used to respond to the object detection request by performing information content detection on the information to be interacted with, and obtaining interaction detection information, wherein the information to be interacted with is determined by the target behavior of the detection object towards the service object. If the information to be interacted with passes the content detection, the information to be interacted with is sent to the service object, wherein the content detection result of the information to be interacted with is determined according to the interaction detection information. The system also obtains historical behavior information associated with the detection object and the service object; performs behavior detection on the detection object in at least one detection dimension based on the historical behavior information, obtains behavior detection information, and generates an interaction event based on the behavior detection information. The interaction event is used to provide extended services to the detection object, and the behavior detection information and the interaction event information are sent to the client 410.

[0098] In practical applications, such as Figure 5 As shown, the information processing system includes user terminals, a platform governance hub, an intelligent quality inspection engine, and merchant service data sources. Merchant service data sources include, but are not limited to, customer service chat logs and behavior logs. Customer service chat logs can be text records or text-to-text conversions of voice chat content. Behavior logs include customer service response times to consumer inquiries, problem resolution rates, and consumer feedback. The intelligent quality inspection engine includes a pre-interception subsystem and a post-interception subsystem. The pre-interception subsystem detects and intercepts incoming interactive information from customer service representatives to consumers. Specifically, it uses a large-scale model in real-time to analyze the information to be sent, identify high-risk phrases, and block the transmission of the information if it contains such phrases or keywords, issuing a warning to the customer service representative. After the interaction between customer service and the consumer, post-interception quality inspection can be performed. This involves using a large-scale model in real-time to analyze historical behavioral information between customer service and consumers, identifying any violations, determining the level of violation, and making compliance judgments based on merchant quality inspection service standards.

[0099] The platform's governance hub is used to address non-compliant behaviors by customer service representatives and consumers. For example, it can invoke the automatic compensation module to compensate consumers, and the review invitation module to send review cards to consumers, inviting them to rate the customer service. An accumulation counter is used to accumulate credit scores, experience scores, or service scores for non-compliant behaviors by customer service representatives or merchants. An experience score linkage module monitors the experience score and displays the merchant's operational status if the experience score does not meet operational requirements. The user terminal, i.e., the consumer's terminal, receives platform compensation information, review invitation cards, and access to service reviews.

[0100] This specification provides an embodiment of an information processing system, including a client and a server. The client submits an object detection request to the server. The server responds to the object detection request by performing content detection on the information to be interacted with, obtaining interaction detection information. The information to be interacted with is determined by the target behavior of the detection object towards the service object. If the information to be interacted with passes content detection, it is sent to the service object, ensuring that the information sent to the service object is compliant, thus achieving pre-detection before sending the information to the service object. The content detection result of the information to be interacted with is determined based on the interaction detection information. Historical behavior information of the associated detection object and service object is obtained. Based on the historical behavior information, behavior detection is performed on the detection object in at least one detection dimension to obtain behavior detection information. This enables behavior detection of the detection object after sending the information to the service object, ensuring the compliance of the detection object's behavior. Interaction events are generated based on the behavior detection information. These interaction events provide extended services to the detection object. Through pre-detection of information content and post-detection of object behavior, the behavior of the detection object is standardized, ensuring the service experience of the service object and improving service satisfaction.

[0101] Corresponding to the above method embodiments, this specification also provides embodiments of an information processing apparatus. Figure 6 A schematic diagram of the structure of an information processing apparatus according to one embodiment of this specification is shown. Figure 6 As shown, the device includes: The detection module 602 is configured to perform information content detection on the information to be interacted with and obtain interaction detection information, wherein the information to be interacted with is determined by the target behavior of the detection object towards the service object; The sending module 604 is configured to send the interactive information to the service object when the interactive information passes the content detection, wherein the content detection result of the interactive information is determined based on the interaction detection information; The acquisition module 606 is configured to acquire historical behavior information associated with the detection object and the service object; The generation module 608 is configured to perform behavior detection on the detection object in at least one detection dimension based on the historical behavior information, obtain behavior detection information, and generate an interaction event based on the behavior detection information. The interaction event is used to provide extended services for the detection object. In an optional embodiment, after performing information content detection on the information to be interacted and obtaining interaction detection information, the module further includes: If it is determined from the interaction detection information that the information to be interacted has failed the content detection, a compliance prompt message is generated based on the information to be interacted and the interaction detection information. The compliance prompt information is displayed on the interactive information page corresponding to the object being tested. The compliance information is used to prompt the object being tested to perform compliance processing on the information to be interacted with.

[0102] In an optional embodiment, the step of performing information content detection on the information to be interacted with to obtain interaction detection information includes: The information processing model is used to detect the information content of the information to be interacted with in the dimensions of preset keywords and / or preset information types, so as to obtain the interaction detection information.

[0103] In an optional embodiment, obtaining the historical behavior information associated with the detected object and the service object includes: Obtain the dialogue information and interaction behavior information associated with the detection object and the service object; The dialogue information and the interaction behavior information are used as the historical behavior information.

[0104] In an optional embodiment, the step of performing behavior detection on the detection object based on the historical behavior information in at least one detection dimension to obtain behavior detection information includes: The at least one detection dimension includes the object semantic dimension, the interaction scenario dimension, the object feedback dimension, and / or the detected object behavior dimension. The behavior detection model is used to perform behavior detection on the detected object in the semantic dimension of the object, the interaction scenario dimension, the object feedback dimension, and / or the behavior dimension of the detected object, respectively, to obtain the behavior detection information.

[0105] In an optional embodiment, after performing behavior detection on the detection object based on the historical behavior information in at least one detection dimension to obtain behavior detection information, the method further includes: Based on the behavior detection information, an early warning event for the detected object is generated, and based on the early warning event, behavior early warning information is generated; The behavioral warning information is displayed on the interactive page corresponding to the detected object, and evaluation collection information is sent to the service object.

[0106] In an optional embodiment, generating an interaction event based on the behavior detection information includes: Based on the behavior detection information, evaluation events, compensation events, and / or prompt events are generated, and the evaluation events, compensation events, and / or prompt events are used as the interaction events.

[0107] In an optional embodiment, after generating the interaction event based on the behavior detection information, the method further includes: Based on the behavior detection information, a rating record information for the detected object is generated, and a rating information is generated based on historical rating information and the rating record information; If, based on the scoring information, it is determined that the tested object does not meet the operating conditions, operating restriction information is generated for the tested object, and the operating restriction information is sent to the tested object.

[0108] An embodiment of this specification provides an information processing apparatus that performs information content detection on information to be interacted with, obtaining interaction detection information. The information to be interacted with is determined by the target behavior of the detection object towards the service object. If the information to be interacted with passes content detection, it is sent to the service object, ensuring that the information sent to the service object is content-compliant, thus achieving pre-detection before sending the information to the service object. The content detection result of the information to be interacted with is determined based on the interaction detection information. Historical behavior information of the associated detection object and service object is obtained, and behavior detection is performed on the detection object in at least one detection dimension based on the historical behavior information to obtain behavior detection information. This enables behavior detection of the detection object after sending the information to be interacted with to the service object, ensuring the compliance of the detection object's behavior. An interaction event is generated based on the behavior detection information. The interaction event is used to provide extended services to the detection object. Through pre-detection of information content and post-detection of the detection object's behavior, the behavior of the detection object is standardized, ensuring the service experience of the service object and improving the service satisfaction of the service object.

[0109] The above is an illustrative scheme of an information processing device according to this embodiment. It should be noted that the technical solution of this information processing device and the technical solution of the information processing method described above belong to the same concept. For details not described in detail in the technical solution of the information processing device, please refer to the description of the technical solution of the information processing method described above.

[0110] Figure 7 A structural block diagram of a computing device 700 according to one embodiment of this specification is shown. The components of the computing device 700 include, but are not limited to, a memory 710 and a processor 720. The processor 720 is connected to the memory 710 via a bus 730, and a database 750 is used to store data.

[0111] The computing device 700 also includes an access device 740, which enables the computing device 700 to communicate via one or more networks 760. Examples of these networks include Public Switched Telephone Network (PSTN), Local Area Network (LAN), Wide Area Network (WAN), Personal Area Network (PAN), or combinations of communication networks such as the Internet. The access device 740 may include one or more of any type of wired or wireless network interface (e.g., a network interface card (NIC)), such as an IEEE 802.11 Wireless Local Area Network (WLAN) wireless interface, a Wi-MAX (Worldwide Interoperability for Microwave Access) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, or a Near Field Communication (NFC) interface.

[0112] In one embodiment of this specification, the above-described components of the computing device 700 and Figure 7 Other components, not shown, can also be connected to each other, for example, via a bus. It should be understood that... Figure 7 The block diagram of the computing device shown is for illustrative purposes only and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0113] The computing device 700 can be any type of stationary or mobile computing device, including mobile computers or mobile computing devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable computing devices (e.g., smartwatches, smart glasses, etc.) or other types of mobile devices, or stationary computing devices such as desktop computers or personal computers (PCs). The computing device 700 can also be a mobile or stationary server.

[0114] The processor 720 is configured to execute the following computer-executable instructions, which, when executed by the processor, implement the steps of the above-described information processing method.

[0115] The above is an illustrative scheme of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the information processing method described above belong to the same concept. For details not described in detail in the technical solution of the computing device, please refer to the description of the technical solution of the information processing method described above.

[0116] An embodiment of this specification also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the above-described information processing method.

[0117] The above is an illustrative scheme of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium and the technical solution of the information processing method described above belong to the same concept. For details not described in detail in the technical solution of the storage medium, please refer to the description of the technical solution of the information processing method described above.

[0118] An embodiment of this specification also provides a computer program product, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described information processing method.

[0119] The above is an illustrative scheme of a computer program product according to this embodiment. It should be noted that the technical solution of this computer program product and the technical solution of the information processing method described above belong to the same concept. For details not described in detail in the technical solution of the computer program product, please refer to the description of the technical solution of the information processing method described above.

[0120] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0121] The computer program / instructions include computer program code, which may be in the form of source code, object code, executable file, or certain intermediate forms. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium may be appropriately added or removed according to the requirements of patent practice. For example, in some regions, according to patent practice, computer-readable media may not include electrical carrier signals and telecommunication signals.

[0122] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments in this specification are not limited to the described order of actions, because according to the embodiments in this specification, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments in this specification.

[0123] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0124] The preferred embodiments disclosed above are merely illustrative of this specification. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the embodiments described herein. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the embodiments, thereby enabling those skilled in the art to better understand and utilize this specification. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. An information processing method, comprising: Information content detection is performed on the information to be interacted to obtain interaction detection information, wherein the information to be interacted is determined by the target behavior of the detection object towards the service object; If the information to be interacted with passes content detection, the information to be interacted with is sent to the service object, wherein the content detection result of the information to be interacted with is determined based on the interaction detection information; Obtain historical behavior information associated with the detected object and the service object; Based on the historical behavior information, the detection object is subjected to behavior detection in at least one detection dimension to obtain behavior detection information, and an interaction event is generated based on the behavior detection information. The interaction event is used to provide extended services for the detection object.

2. The information processing method according to claim 1, after performing information content detection on the information to be interacted and obtaining interaction detection information, further includes: If it is determined from the interaction detection information that the information to be interacted has failed the content detection, a compliance prompt message is generated based on the information to be interacted and the interaction detection information. The compliance prompt information is displayed on the interactive information page corresponding to the object being tested. The compliance information is used to prompt the object being tested to perform compliance processing on the information to be interacted with.

3. The information processing method according to claim 1, wherein the step of detecting the information content of the information to be interacted with to obtain interaction detection information includes: The information processing model is used to detect the information content of the information to be interacted with in the dimensions of preset keywords and / or preset information types, so as to obtain the interaction detection information.

4. The information processing method according to claim 1, wherein obtaining historical behavior information associated with the detection object and the service object includes: Obtain the dialogue information and interaction behavior information associated with the detection object and the service object; The dialogue information and the interaction behavior information are used as the historical behavior information.

5. The information processing method according to claim 1, wherein the step of performing behavior detection on the detection object based on the historical behavior information in at least one detection dimension to obtain behavior detection information includes: The at least one detection dimension includes the object semantic dimension, the interaction scenario dimension, the object feedback dimension, and / or the detected object behavior dimension. The behavior detection model is used to perform behavior detection on the detected object in the semantic dimension, the interaction scenario dimension, the object feedback dimension, and / or the behavior dimension of the detected object, respectively, to obtain the behavior detection information.

6. The information processing method according to claim 1, after performing behavior detection on the detection object based on the historical behavior information in at least one detection dimension to obtain behavior detection information, further includes: Based on the behavior detection information, an early warning event for the detected object is generated, and based on the early warning event, behavior early warning information is generated; The behavioral warning information is displayed on the interactive page corresponding to the detected object, and evaluation collection information is sent to the service object.

7. The information processing method according to claim 1, wherein generating an interactive event based on the behavior detection information comprises: Based on the behavior detection information, evaluation events, compensation events, and / or prompt events are generated, and the evaluation events, compensation events, and / or prompt events are used as the interaction events.

8. The information processing method according to claim 1, further comprising, after generating the interaction event based on the behavior detection information: Based on the behavior detection information, a rating record information for the detected object is generated, and a rating information is generated based on historical rating information and the rating record information; If, based on the scoring information, it is determined that the tested object does not meet the operating conditions, operating restriction information is generated for the tested object, and the operating restriction information is sent to the tested object.

9. An information processing system, comprising a client and a server, including: The client is used to submit an object detection request to the server; The server is configured to respond to the object detection request by performing information content detection on the information to be interacted with, and obtaining interaction detection information, wherein the information to be interacted with is determined by the target behavior of the detection object towards the service object; if the information to be interacted with passes the content detection, the server sends the information to be interacted with to the service object, wherein the content detection result of the information to be interacted with is determined based on the interaction detection information; acquire historical behavior information associated with the detection object and the service object; perform behavior detection on the detection object in at least one detection dimension based on the historical behavior information, obtain behavior detection information, and generate an interaction event based on the behavior detection information, wherein the interaction event is used to provide extended services for the detection object, and send the behavior detection information and the interaction event information of the interaction event to the client.

10. A computing device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the method according to any one of claims 1 to 8.

11. A computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1 to 8.

12. A computer program product comprising a computer program or instructions which, when executed by a processor, implement the steps of the method according to any one of claims 1 to 8.

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