Consumption public opinion information analysis method, system and equipment and medium

Abstract

The invention provides a consumption public opinion information analysis method, system and device and a medium, and belongs to the technical field of consumption information processing. A consumption information set is obtained, consumption information needing to be analyzed is matched with consumption identifiers in a consumption information library, and whether the consumption identifiers matched with the consumption information needing to be analyzed exist or not is judged; when the consumption identifier matched with the consumption information needing to be analyzed exists, consumption analysis corresponding to the consumption identifier is executed; if the current consumption process is the consumption process of the consumer and the virtual shop assistant, the consumption information needing to be analyzed is input into the consumption information consumption public opinion analysis model; and executing corresponding consumption analysis including information query consumption analysis, consumption process adjustment consumption analysis or guide consumption analysis based on an identification result of the consumption information consumption public opinion analysis model. According to the method, consumption public opinions are fed back in real time, enterprises can be helped to adjust service strategies in time, differentiated processing of virtual and real person scenes gives consideration to service efficiency and personalized requirements, and consumer satisfaction is improved.

Description

Technical Field

[0001] The present invention belongs to the field of consumer information processing technology, and specifically relates to a consumer public opinion information analysis method, system, equipment and medium. Background Art

[0002] With the rapid development of the internet and e-commerce, the dissemination of information in the consumer sector has exploded. Consumers express their evaluations, opinions, and demands for products and services through multiple channels, including e-commerce platforms, social media, and online customer service, generating a massive amount of consumer public opinion information. This information, which contains consumer preferences, pain points, and market trends, is of great value to companies in optimizing products, improving services, and formulating marketing strategies.

[0003] In existing consumer sentiment analysis, raw data often contains a large amount of invalid information. Directly importing this data into analytical models results in wasted computing resources and biased results. Related technologies are unable to effectively utilize real-time feedback on consumer sentiment, hindering companies from effectively adjusting their service strategies. The differentiated handling of virtual and real-life scenarios fails to effectively match service efficiency with personalized needs, resulting in poor consumer satisfaction. Summary of the Invention

[0004] The present invention provides a method for analyzing consumer public opinion information. The method provides real-time feedback on consumer public opinion to help companies adjust their service strategies in a timely manner. The differentiated processing of virtual and real-life scenes takes into account both service efficiency and personalized needs, thereby improving consumer satisfaction.

[0005] Methods include: S101: Obtain a consumption information set, extract recent consumption information from the consumption information set, and use the recent consumption information as the consumption information to be analyzed; S102: Match the consumption information to be analyzed with the consumption identifiers in the consumption information database to determine whether there is a consumption identifier that matches the consumption information to be analyzed; S103: When there is a consumer identifier that matches the consumer information to be analyzed, perform consumption analysis corresponding to the consumer identifier, generate feedback information based on the execution result, and output the feedback information to the public opinion monitoring platform; When there is no consumption identifier that matches the consumption information to be analyzed, determining the current consumption process, which includes the consumption process between the consumer and the virtual store clerk and the consumption process between the consumer and the store clerk; S104: If the current consumption process is a consumption process between a consumer and a virtual store clerk, the consumption information needs to be analyzed and input into the consumption information consumption public opinion analysis model. Based on the recognition results of the consumption information consumption public opinion analysis model, corresponding consumption analysis including information query consumption analysis, consumption process adjustment consumption analysis or guided consumption analysis is performed.

[0006] Preferably, step S101 further includes: Obtain a set of consumer information from the public opinion monitoring platform and attach a consumption timestamp to each piece of consumer information; Remove blank input, noise data or repeated information in consumption information to obtain target consumption information; Extract the valid consumption information with the latest consumption timestamp from the target consumption information; The valid consumption information with the latest consumption timestamp is formatted to generate text data that meets the preset data format requirements, and the text data is stored as the consumption information to be analyzed.

[0007] Preferably, step S102 specifically includes: Load consumption identifiers from the consumption information database and adjust the priority of consumption identifiers based on historical consumption information; The consumption information to be analyzed is input into the precise matching module, and the precise matching module determines whether there is a consumption identifier that matches the consumption information to be analyzed; When there are multiple matching consumer identifiers, the consumer identifier with the highest priority is selected as the final matching result based on the priority; When there is no matching consumption identifier, the consumption information to be analyzed is input into the fuzzy matching module, and matching is performed according to the fuzzy matching conditions to determine whether there is a consumption identifier that is fuzzy matching with the consumption information to be analyzed.

[0008] Preferably, step S103 further includes: When there is no consumption identification that matches the consumption information to be analyzed, the current consumption process is determined, where the consumption process includes the consumption process between the consumer and the virtual store clerk and the consumption process between the consumer and the store clerk.

[0009] Preferably, step S103 further includes: if the current consumption process is a consumption process between a consumer and a store clerk, inputting the consumption information to be analyzed into the consumption public opinion analysis model, and determining the consumption request category based on the recognition result of the consumption public opinion analysis model; When the consumption request category is information query, provide information feedback corresponding to the consumption request category; When the consumption request category is a consumption analysis instruction, corresponding prompt information is generated, and according to the prompt information, the corresponding execution subject is prompted to perform the consumption analysis corresponding to the consumption analysis instruction and record the consumption record.

[0010] Preferably, the method further comprises: after the consumption process between the consumer and the store clerk is completed, transmitting the consumption record to the consumption information database; Based on the consumption information stored in the consumption information database, adjust the parameter weights of the consumer public opinion analysis model to optimize the recognition ability of the consumer public opinion analysis model; The consumption identification in the consumption information database is updated based on the consumption records and the feedback information obtained during the consumption process between the consumer and the store clerk.

[0011] Preferably, step S104 specifically includes: If the current consumption process is a consumption process between a consumer and a virtual store clerk, the consumption information needs to be analyzed and input into the consumption information and consumption public opinion analysis model to determine whether the consumption information and consumption public opinion analysis model has identified the specific consumption; When the consumption information and public opinion analysis model identifies specific consumption, the consumption analysis corresponding to the specific consumption is performed; When the consumption information and public opinion analysis model fails to identify specific consumption, the current consumption process is switched to the consumption process between the consumer and the store clerk; During the consumption process between consumers and store clerks, actual needs are identified based on historical consumption information, and auxiliary consumption analysis corresponding to actual needs is performed.

[0012] This application also provides a consumer public opinion information analysis system, which includes: The consumption acquisition and screening module is used to obtain the consumption information set and extract the recent consumption information from the consumption information set, and use the recent consumption information as the consumption information to be analyzed; The consumption identification matching judgment module is used to match the consumption information to be analyzed with the consumption identification in the consumption information database to determine whether there is a consumption identification that matches the consumption information to be analyzed; The consumption analysis and feedback module is used to perform consumption analysis corresponding to the consumption identifier when there is a consumption identifier that matches the consumption information to be analyzed, generate feedback information based on the execution result, and output the feedback information to the public opinion monitoring platform; When there is no consumption identifier that matches the consumption information to be analyzed, determining the current consumption process, which includes the consumption process between the consumer and the virtual store clerk and the consumption process between the consumer and the store clerk; The virtual clerk scenario consumption public opinion analysis module is used to input the consumption information to be analyzed into the consumption information consumption public opinion analysis model if the current consumption process is a consumption process between a consumer and a virtual clerk. Based on the recognition results of the consumption information consumption public opinion analysis model, corresponding consumption analysis including information query consumption analysis, consumption process adjustment consumption analysis or guided consumption analysis is performed.

[0013] According to another embodiment of the present application, an electronic device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the consumer public opinion information analysis method when executing the program.

[0014] According to another embodiment of the present application, a storage medium is also provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the consumer public opinion information analysis method are implemented.

[0015] It can be seen from the above technical solutions that the present invention has the following advantages: The consumer public opinion information analysis method involved in this application ensures the timeliness and accuracy of consumer information entering the analysis phase by adding timestamps, eliminating invalid data, and extracting the latest valid data, thereby avoiding analysis deviations caused by redundant or obsolete data. By matching consumer identifications in the consumer information database, it is possible to quickly respond to historically recorded consumption scenarios, directly call preset analysis logic to generate feedback, shorten the processing cycle, and improve the real-time performance of the public opinion monitoring platform. Utilize the consumer public opinion analysis model to automatically parse needs, perform information queries, adjust processes, or guide consumption, etc., to reduce manual intervention and improve service standardization.

[0016] Recording the consumption analysis process and results provides data support for subsequent updates to the consumer information database and model optimization. Through the continuous accumulation of consumption records, the consumer information database can continuously update consumption identifiers. Simultaneously, adjusting model parameter weights improves the accuracy of identifying complex demands, increasing system adaptability as data grows. Real-time feedback on consumer sentiment helps companies adjust service strategies promptly. Differentiated processing of virtual and real-life scenarios balances service efficiency and personalized needs, improving consumer satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for the description. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 A flowchart of the consumer public opinion information analysis method; Figure 2 This is a schematic diagram of the consumer public opinion information analysis system; Figure 3 Schematic diagram of an electronic device. DETAILED DESCRIPTION

[0019] The following describes in detail the consumer public opinion information analysis method involved in this application. For the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are provided to facilitate a thorough understanding of the embodiments of this application. However, it should be clear to those skilled in the art that this application can also be implemented in other embodiments without these specific details.

[0020] It should be understood that when used in this specification, the term "comprising" indicates the presence of the described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or their collections. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0021] It should be understood that the "one or more" mentioned in this application refers to one, two or more, and the "multiple" mentioned in this application refers to two or more. In the description of this application, unless otherwise specified, " / " means or, for example, A / B can mean A or B. The "and / or" in this article is only a way to describe the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0022] The phrases "one embodiment" or "some embodiments" described in this application mean that the specific features, structures, or characteristics described in the embodiment are included in one or more embodiments of the application. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in other embodiments," etc. that appear in different places in this application do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized.

[0023] In embodiments of the present invention, computer program code for performing the operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including, but not limited to, object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (exemplarily, via the Internet using an Internet service provider).

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0025] See also Figure 1 FIG2 is a flowchart of a method for analyzing consumer public opinion information in a specific embodiment, the method comprising: S101: Obtain a consumption information set, extract recent consumption information from the consumption information set, and use the recent consumption information as the consumption information to be analyzed.

[0026] In some embodiments, the sources of consumer information sets are wide-ranging, including but not limited to user reviews on e-commerce platforms (such as Taobao and JD.com); discussions and order sharing about products or services on social media platforms (such as Weibo and Douyin); comments and feedback on the company's official website; questionnaires in offline stores; consumer inquiries and complaints recorded by the customer service system, etc.

[0027] Based on your company's needs and business characteristics, define a "recent" timeframe, such as the past week, month, or three months. This timeframe can be adjusted flexibly. For example, for products with rapid updates and high consumption frequency (e.g., electronics and fast-moving consumer goods), a shorter timeframe can be used; for durable consumer goods (e.g., appliances and automobiles), the timeframe can be extended appropriately.

[0028] From the acquired consumer information set, we filter out consumer information that falls within the recent timeframe based on the timestamp field in the data records. This information, including consumers' opinions on products or services, descriptions of their experiences, and feedback on issues, serves as the basis for subsequent in-depth analysis.

[0029] S102: Match the consumption information to be analyzed with the consumption identifiers in the consumption information database to determine whether there is a consumption identifier that matches the consumption information to be analyzed.

[0030] In some embodiments, the consumption identification stored in the consumption information database covers multiple dimensions, including product attribute identification (such as the screen size and processor model of the mobile phone), service type identification (such as after-sales service response time and delivery speed), emotional tendency identification (such as satisfaction, dissatisfaction, and complaints), consumption behavior identification (such as repeat purchase, return, and bad review), etc.

[0031] Through historical data analysis, industry experience, and expert advice, companies predefine various consumer identifiers and store them in a structured database. As business grows and the market changes, the consumer identifier database will be continuously updated and improved.

[0032] This embodiment pre-processes the consumer information to be analyzed, including removing noise data (such as irrelevant special symbols and advertising links), word segmentation (segmenting the text into individual words or phrases), and part-of-speech tagging (marking the part of speech of each word, such as noun, verb, or adjective).

[0033] Using string matching algorithms (such as the BM algorithm and the KMP algorithm) or semantic matching algorithms (such as word vector similarity calculation based on Word2Vec and semantic similarity calculation based on BERT), the processed consumer information is compared with the identifiers in the consumer identifier database. The system determines whether there are semantically similar or exact matching consumer identifiers. If so, the matching identifier information is recorded; if not, the system proceeds to the next step.

[0034] S103: When a consumer identifier that matches the consumption information to be analyzed exists, the corresponding consumption analysis is performed, and feedback information is generated based on the execution results. The feedback information is output to the public opinion monitoring platform. If no consumer identifier that matches the consumption information to be analyzed exists, the current consumption process is determined. The consumption process includes the consumption process between the consumer and the virtual store clerk and the consumption process between the consumer and the store clerk.

[0035] In some embodiments, pre-defined consumer analysis logic is invoked for each matching consumer identifier. For example, if the "poor product quality" identifier is matched, the analysis logic may include statistics on the frequency of product quality issues, the specific product batches involved, and the affected consumer groups. If the "slow logistics delivery" identifier is matched, the analysis logic may include analysis of the average logistics delivery time and the reasons for the delay (e.g., weather or warehouse issues).

[0036] Based on the results of consumer analysis, structured feedback information is generated, including problem description, scope of impact, severity assessment, and relevant suggestions. Feedback information can be formatted as tables, charts, or text reports, making it easier for users of the public opinion monitoring platform to understand the situation intuitively.

[0037] The generated feedback information is pushed to the public opinion monitoring platform, which displays it to relevant company personnel (such as the marketing department, customer service department, and product department) through a visual interface so that they can understand consumer public opinion in a timely manner and take corresponding measures.

[0038] The current consumption process is determined by analyzing consumption information. For example, if the consumption information comes from the intelligent customer service dialogue window on the company's official website, it is considered a consumption process between the consumer and the virtual store clerk; if the information comes from offline store purchase records or telephone customer service communication records, it is considered a consumption process between the consumer and the store clerk. The consumption process type can also be comprehensively determined by combining multiple factors such as user identity information and consumption scenario.

[0039] S104: If the current consumption process is a consumption process between a consumer and a virtual store clerk, the consumption information needs to be analyzed and input into the consumption information consumption public opinion analysis model. Based on the recognition results of the consumption information consumption public opinion analysis model, corresponding consumption analysis including information query consumption analysis, consumption process adjustment consumption analysis or guided consumption analysis is performed.

[0040] In some embodiments, consumer information and public opinion analysis models are trained based on a large amount of historical consumer information data, using machine learning or deep learning algorithms such as recurrent neural networks (RNNs), long short-term memory networks (LSTMs), and transformers. Training data includes various types of consumer records and user reviews, labeled with corresponding categories such as information inquiries, complaints, and purchase inquiries. By continuously adjusting model parameters, the model can accurately identify sentiment within consumer information.

[0041] The consumption information to be analyzed is input into the trained model. The model extracts features and understands the semantics of the input information and outputs the recognition results, that is, it determines whether the consumption information belongs to the categories of information query, consumption process adjustment or consumption guidance.

[0042] If the model identifies an information query, the company analyzes the specific content of the user's query, such as product features, usage instructions, pricing information, etc. The company determines whether the existing knowledge base can accurately answer the user's question. If there are unclear answers or missing content, the company proposes suggestions for improving the knowledge base to better serve users in the future.

[0043] When it is identified as an adjustment to the consumption process, in-depth analysis will be conducted on the problems that occurred during the consumption process, such as inaccurate answers from the virtual clerk and cumbersome interaction processes.

[0044] If it falls into the consumption guidance category, we explore the user's potential needs, combine the user's historical consumption data and current inquiry content, and generate personalized recommendations. For example, we can recommend relevant product accessories, upgraded services, or promotions to encourage user consumption.

[0045] On the basis of the above embodiment, in order to further improve the reliability of the consumer public opinion information analysis method provided by the above embodiment, the following is an implementable method. In this embodiment, the consumer information to be analyzed extracted from the consumer consumption information is compared with the consumer information library in the system to quickly determine whether the content entered by the consumer meets the defined consumer identification. The consumer information library is a database containing multiple preset consumer identifications. Each rule corresponds to a consumer category, which is used to describe the common needs and problem scenarios of consumers. The core of consumer public opinion analysis is to analyze the consumer keywords of the consumer information to be analyzed, compare them with the rules in the consumer information library one by one, and find the most suitable data match.

[0046] After completing the matching consumption analysis, the system needs to determine whether there is a consumer ID that matches the consumption information to be analyzed. If a matching rule exists, the system considers that the consumer's consumption category has been identified and can perform the corresponding consumption analysis based on the matching consumption ID. If no matching rule is found, it needs to further call the consumer public opinion analysis model for deeper identification.

[0047] After matching consumption analysis is complete, the system returns a matching result set. If one or more matches are found in the result set, the system selects the most suitable match based on the priority of the consumption identifier as the final result. If no rules are matched, the system transfers the consumption information to be analyzed to a deep neural network model, which uses more complex algorithms such as large language models to make consumption predictions based on the data. This two-step matching strategy ensures both processing efficiency and the accuracy of consumer sentiment analysis.

[0048] In the corresponding step S103, after matching the consumption information to be analyzed with the rules in the consumption information database, if a rule is identified that matches the consumption information to be analyzed, the system will trigger the consumption analysis instruction associated with the rule. The consumption analysis instruction corresponding to the consumption identifier includes a series of preset functional tasks. After the consumption analysis task is completed, feedback information will be generated based on the execution results of the consumption analysis. The content of the feedback information depends on the specific execution of the consumption analysis task, and usually includes the consumption analysis results, status information, and prompt content. The feedback information can be text information visible to the consumer or an execution log recorded internally by the system for subsequent processing.

[0049] Outputting the generated feedback information to the public opinion monitoring platform means that the system returns the processing results to consumers in a visual form.

[0050] In step S104, after the system matches the consumer information to be analyzed with the consumer identifiers in the consumer information database, if no matching consumer identifier is found, the system proceeds to the next step of the judgment process. At this point, the system deems that the consumer's consumption information cannot be quickly matched according to the preset rules, possibly belonging to a more complex or unexpected scenario, and therefore requires further processing.

[0051] The system analyzes consumption information to determine the current consumption process. When a consumer first enters the consumption platform and interacts with the consumption processing terminal, it will automatically determine that the consumption process is between the consumer and the virtual store clerk. When the consumer's consumption information has been taken over by the store clerk, it will be determined that the consumption process is between the consumer and the store clerk. The consumption process can be determined in the following ways: Determine the consumer's consumption process based on their identity status. Based on the keywords and language style of the consumer information, infer whether the current interaction is with the consumer processing terminal or the store clerk. Record the current consumption process using a system status identifier, automatically updating it when the status changes.

[0052] When determining the consumption process, we mainly distinguish between two scenarios: the consumption process between the consumer and the virtual store clerk and the consumption process between the consumer and the store clerk. By determining the consumption process without matching rules, the system achieves dynamic adjustment capabilities in different scenarios. The system can distinguish between the consumption process between the consumer and the virtual store clerk and the consumption process between the consumer and the clerk, avoiding the situation where the consumption processing end is stuck in an endless loop or provides incorrect answers when unable to answer questions. Furthermore, by providing clerks with the consumer's historical consumption records, the system can help clerks more accurately identify consumers' needs during the consumption process between consumers and clerks.

[0053] As a method of this embodiment, if the current consumption process is a consumption process between a consumer and a virtual store clerk, the consumption information needs to be analyzed and input into the consumption information consumption public opinion analysis model, and the corresponding consumption analysis including information query consumption analysis, consumption process adjustment consumption analysis or guided consumption analysis is performed based on the recognition results of the consumption information consumption public opinion analysis model.

[0054] In this embodiment, when the system determines that the consumer's current consumption process is between the consumer and a virtual store clerk, the system will adopt a method tailored to the interaction between the consumer and the virtual store clerk. During this interaction, the consumer typically interacts with the consumer processing terminal or the intelligent customer service system. Because the consumer processing terminal may encounter incomplete information or questions beyond its knowledge when answering consumer questions, the system needs to use a specific model to analyze consumer public opinion based on the consumer's consumption information to avoid providing incorrect answers from the consumer processing terminal.

[0055] By analyzing the consumer's identity and the content of their purchase information, the system determines whether the current purchase process is between the consumer and the virtual store clerk. If the consumer's input has not yet been taken over by the clerk, the system determines that the current stage is a purchase process between the consumer and the virtual store clerk. The system then marks the consumer's latest input data as requiring analysis.

[0056] After determining that the current purchase process is between a consumer and a virtual store clerk, the system inputs the consumer's consumption information to the consumer information and public opinion analysis model. This model, based on a large language model (LLM) or other machine learning algorithms, is specifically designed to analyze consumer information content and identify actual purchases.

[0057] After obtaining the output of the consumer information and public opinion analysis model, the system performs corresponding consumer analysis based on the identification results. Each identified consumer category corresponds to a consumer analysis task. The system performs consumer mapping on the model's output, mapping the identified consumer category to the pre-set consumer analysis task. During the execution of the consumer analysis task, the system monitors the execution status and results of the consumer analysis task and generates feedback based on the task results, which is then output to the consumer.

[0058] In some specific embodiments, step S104 further involves the following: S401: If the current consumption process is a consumption process between a consumer and a store clerk, the consumption information to be analyzed is input into the consumption public opinion analysis model, and the consumption request category is determined based on the recognition result of the consumption public opinion analysis model.

[0059] In this embodiment, when the current consumption process is determined to be an interaction between a consumer and a store employee, the system inputs the consumer information to be analyzed (such as consumer questions, feedback, or instructions) into the consumer public opinion analysis model. The consumer public opinion analysis model uses natural language processing (NLP) and text classification algorithms (such as machine learning models or deep learning models) to perform semantic analysis on the information content, identifying keywords and sentiment, and ultimately determining the specific category of the consumer request (such as information query, consumer analysis instruction, etc.).

[0060] S402: When the consumption request category is information query, provide information feedback corresponding to the consumption request category.

[0061] In this embodiment, when a consumer request is classified as "information inquiry," the system retrieves and extracts information related to the inquiry (such as product specifications, prices, promotions, etc.) from a pre-defined knowledge base or data interface, and provides feedback to the consumer in structured or natural language form. For example, if a consumer asks about the battery capacity of a certain mobile phone, the system directly accesses the product information database to return the specific parameters.

[0062] S403: When the consumption request type is a consumption analysis instruction, corresponding prompt information is generated, and according to the prompt information, a corresponding execution subject is prompted to execute the consumption analysis corresponding to the consumption analysis instruction.

[0063] In this embodiment, if the consumer request is a "consumer analysis instruction" (e.g., a user requesting an analysis of the positive reviews for a certain product category), the system first generates a prompt (e.g., a pop-up window or notification message) to clearly inform the executing entity (e.g., a store clerk or manager) of the analysis task to be completed (e.g., "Please analyze the user reviews for product XX over the past week"). After receiving the prompt, the executing entity invokes the appropriate data analysis tool or model (e.g., a statistical report or machine learning model) to perform the analysis and output the results (e.g., a trend chart or conclusion report).

[0064] S404: storing the recognition result and information feedback or executed consumption analysis information as a consumption record.

[0065] In this embodiment, the system stores the consumer sentiment analysis model's identification results (e.g., request category), information feedback (e.g., query results), or executed consumer analysis information (e.g., analysis report data) in a structured data format (e.g., database table, JSON file) as consumption records. Records typically include fields such as timestamp, user ID, interaction content, and processing results.

[0066] S405: After the consumer and the store clerk complete the consumption process, the consumption record is transmitted to the consumption information database.

[0067] In this embodiment, after the consumer and store employee complete their purchase (e.g., transaction completion, consultation termination), the system transfers the stored purchase records to a consumer information database. This database centrally stores historical purchase data, identification rules, and analysis model parameters, supporting data addition, deletion, modification, and version management. Purchase records are synchronized to the database in batches or in real time through data interfaces (e.g., APIs and ETL tools), ensuring that the database data is dynamically synchronized with actual purchase scenarios. For example, newly generated user query records can be added to the knowledge base to optimize information retrieval logic.

[0068] S406: Based on the consumption information stored in the consumption information database, adjust the parameter weights of the consumption public opinion analysis model to optimize the recognition ability of the consumption public opinion analysis model.

[0069] In this embodiment, based on historical consumption information stored in the consumer information database (such as labeled user requests and processing results), the system uses algorithms (such as backpropagation and gradient descent) to adjust the parameter weights of the consumer public opinion analysis model. For example, if the model has a low accuracy rate when identifying requests for "promotion consultation," the system automatically increases the weight of features in this category to improve subsequent recognition accuracy.

[0070] Adopting supervised learning or semi-supervised learning mode, historical consumption records are used as training data, performance is measured through model evaluation indicators (such as accuracy and recall rate), and model parameters are iteratively optimized to make it more in line with the needs of actual consumption scenarios.

[0071] S407: Update the consumption identification in the consumption information database according to the consumption record and the feedback information obtained during the consumption process between the consumer and the store clerk.

[0072] In this embodiment, the system updates the consumer identifiers in the consumer information database based on consumption records (such as newly added user request types and analysis instruction patterns) and feedback collected during the consumption process (such as store clerks' comments on model recognition results). Consumption identifiers are predefined rules or labels (such as "product inquiry" and "after-sales complaint") that are used to quickly match and categorize consumer information.

[0073] In this embodiment, after the consumer and the store clerk complete their purchase, the system transmits the recognition results, feedback, or consumption analysis generated during the current interaction as a consumption record to the consumption information database. The main function of the consumption information database is to store consumption information between the consumer and the system for subsequent analysis and model optimization.

[0074] The consumption information in the consumption information database of this embodiment is used for model training and fine-tuning. The specific implementation process is as follows: Consumption records are extracted from the consumer information database, including consumer information, identification results, and feedback. This extracted data is used as training samples and fed into the consumer public opinion analysis model to adjust the model's parameter weights. Based on the model's performance on new data, the model's weight parameters are dynamically adjusted to improve the model's ability to identify different consumer categories.

[0075] The system dynamically updates the consumer identifiers in the consumer information database by analyzing consumption records and consumer feedback. Updating consumer identifiers includes adding new rules, modifying existing rules, and deleting invalid rules to ensure the system can adapt to changes in consumer demand. Based on actual consumer feedback, the system updates consumer identifiers in the following steps: Analyze unmatched consumer purchase information in consumption records and identify new consumer purchases. Generate new consumption identifiers for unmatched consumer purchases and add them to the consumption information database. Adjust existing consumption identifiers. Delete consumption identifiers that have not been triggered or have expired for a long time to ensure that the consumption information database rules remain valid. By analyzing consumer feedback in consumption records, the system identifies outdated or expired consumption identifiers and automatically deletes or updates these rules.

[0076] This embodiment achieves self-optimization by storing consumption records in a consumer information database and dynamically adjusting the parameter weights of the consumer public opinion analysis model based on log data. By analyzing consumption records and consumer feedback, the system can dynamically update the rules of the consumer information database, ensuring that the system's consumer public opinion analysis capabilities always adapt to changes in consumer demand, thereby improving the system's recognition accuracy and response speed.

[0077] As an implementation method of this application, the following steps are also involved: S801, if the current consumption process is a consumption process between a consumer and a virtual store clerk, the consumption information needs to be analyzed and input into the consumption information and consumption public opinion analysis model to determine whether the consumption information and consumption public opinion analysis model has identified the specific consumption; S802, when the consumption information and public opinion analysis model identifies specific consumption, performing consumption analysis corresponding to the specific consumption; S803: When the consumption information and public opinion analysis model fails to identify a specific consumption, or the input consumption information to be analyzed exceeds the processing range, the current consumption process is switched to the consumption process between the consumer and the store clerk; S804, during the consumption process between the consumer and the store clerk, actual needs are identified based on historical consumption information, and auxiliary consumption analysis corresponding to the actual needs is performed.

[0078] In this embodiment, the system processes the consumer's input for analysis during the purchase process between the consumer and the virtual store clerk. The system passes the consumer's input data to the consumer information and public opinion analysis model and determines whether the model can identify the consumer's specific consumption category. The core function of the public opinion analysis model is to determine the consumer's true needs through consumer keyword analysis, thereby providing corresponding consumption analysis guidance.

[0079] After the model identifies a consumer's specific consumption, the system will invoke the corresponding consumption analysis instructions based on the identification results. Each consumption category is pre-associated with one or more consumption analysis tasks, and the system will execute these tasks according to the preset logic to meet the consumer's needs.

[0080] The system extracts consumption analysis instructions corresponding to the identified consumption categories from the consumption analysis instruction library. The system invokes these instructions to execute tasks such as queries, recommendations, redirects, or replies. The system monitors the execution status of consumption analysis tasks and generates feedback based on the results.

[0081] During the consumption process between consumers and store clerks, the system will analyze the consumer's historical consumption information and current consumption information, identify the consumer's specific needs, and perform corresponding auxiliary consumption analysis.

[0082] The system analyzes consumers' historical consumption information to identify their behavioral patterns and potential needs. Based on the analysis results, the system automatically generates auxiliary consumption analysis prompts and recommends corresponding consumption analysis tasks to store staff.

[0083] The following is an embodiment of the consumer public opinion information analysis system provided by the embodiments of the present disclosure. This system and the consumer public opinion information analysis methods of the above-mentioned embodiments belong to the same inventive concept. For details not fully described in the embodiments of the consumer public opinion information analysis system, please refer to the embodiments of the above-mentioned consumer public opinion information analysis method.

[0084] like Figure 2 As shown, the system includes: The consumption acquisition and screening module is used to obtain the consumption information set and extract the recent consumption information from the consumption information set, and use the recent consumption information as the consumption information to be analyzed; The consumption identification matching judgment module is used to match the consumption information to be analyzed with the consumption identification in the consumption information database to determine whether there is a consumption identification that matches the consumption information to be analyzed; The consumption analysis and feedback module is used to perform consumption analysis corresponding to the consumption identifier when there is a consumption identifier that matches the consumption information to be analyzed, generate feedback information based on the execution result, and output the feedback information to the public opinion monitoring platform; When there is no consumption identifier that matches the consumption information to be analyzed, determining the current consumption process, which includes the consumption process between the consumer and the virtual store clerk and the consumption process between the consumer and the store clerk; The virtual clerk scenario consumption public opinion analysis module is used to input the consumption information to be analyzed into the consumption information consumption public opinion analysis model if the current consumption process is a consumption process between a consumer and a virtual clerk. Based on the recognition results of the consumption information consumption public opinion analysis model, corresponding consumption analysis including information query consumption analysis, consumption process adjustment consumption analysis or guided consumption analysis is performed.

[0085] like Figure 3 As shown, the present application also provides an electronic device, including a display module 103, a memory 102, a processor 101, and a computer program stored in the memory and executable on the processor 101. When the processor 101 executes the program, the steps of the power transmission engineering GIM model parsing and loading method are implemented.

[0086] In the embodiments of the present invention, electronic devices include, but are not limited to, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the embodiments of the present application described and / or claimed herein.

[0087] In the embodiment of the present application, the processor 101 can be implemented by using at least one of an application-specific integrated circuit (ASIC), a programmable logic device (PLD), a field programmable gate array (FPGA), a processor, a controller, a microcontroller, a microprocessor, and an electronic unit designed to perform the functions described herein. In some cases, such an embodiment can be implemented in a controller. For software implementation, an embodiment such as a process or function can be implemented with a separate software module that allows the execution of at least one function or operation. The software code can be implemented by a software application (or program) written in any appropriate programming language, and the software code can be stored in a memory and executed by a controller.

[0088] The display module 103 is used to display information input by the user or information provided to the user. The display module 103 may include a display panel, which may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), etc.

[0089] The memory 102 can be used to store software programs and various data. The memory 102 can include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0090] The present application also provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the consumer public opinion information analysis method are implemented.

[0091] The storage medium can be any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0092] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for analyzing consumer public opinion information, characterized in that: Methods include: S101: Obtain a consumption information set, extract recent consumption information from the consumption information set, and use the recent consumption information as the consumption information to be analyzed; S102: Match the consumption information to be analyzed with the consumption identifiers in the consumption information database to determine whether there is a consumption identifier that matches the consumption information to be analyzed; S103: When there is a consumer identifier that matches the consumer information to be analyzed, perform consumption analysis corresponding to the consumer identifier, generate feedback information based on the execution result, and output the feedback information to the public opinion monitoring platform; When there is no consumption identifier that matches the consumption information to be analyzed, determining the current consumption process, which includes the consumption process between the consumer and the virtual store clerk and the consumption process between the consumer and the store clerk; S104: If the current consumption process is a consumption process between a consumer and a virtual store clerk, the consumption information needs to be analyzed and input into the consumption information consumption public opinion analysis model. Based on the recognition results of the consumption information consumption public opinion analysis model, corresponding consumption analysis including information query consumption analysis, consumption process adjustment consumption analysis or guided consumption analysis is performed.

2. The method for analyzing consumer public opinion information according to claim 1, characterized in that: Step S101 also includes: Obtain a set of consumer information from the public opinion monitoring platform and attach a consumption timestamp to each piece of consumer information; Remove blank input, noise data or repeated information in consumption information to obtain target consumption information; Extract the valid consumption information with the latest consumption timestamp from the target consumption information; The valid consumption information with the latest consumption timestamp is formatted to generate text data that meets the preset data format requirements, and the text data is stored as the consumption information to be analyzed.

3. The method for analyzing consumer public opinion information according to claim 1, characterized in that: Step S102 specifically includes: Load consumption identifiers from the consumption information database and adjust the priority of consumption identifiers based on historical consumption information; The consumption information to be analyzed is input into the precise matching module, and the precise matching module determines whether there is a consumption identifier that matches the consumption information to be analyzed; When there are multiple matching consumer identifiers, the consumer identifier with the highest priority is selected as the final matching result based on the priority; When there is no matching consumption identifier, the consumption information to be analyzed is input into the fuzzy matching module, and matching is performed according to the fuzzy matching conditions to determine whether there is a consumption identifier that is fuzzy matching with the consumption information to be analyzed.

4. The method for analyzing consumer public opinion information according to claim 1, characterized in that: Step S103 further includes: When there is no consumption identification that matches the consumption information to be analyzed, the current consumption process is determined, where the consumption process includes the consumption process between the consumer and the virtual store clerk and the consumption process between the consumer and the store clerk.

5. The method for analyzing consumer public opinion information according to claim 1, characterized in that: Step S103 further includes: if the current consumption process is a consumption process between a consumer and a store clerk, inputting the consumption information to be analyzed into the consumption public opinion analysis model, and determining the consumption request category based on the recognition result of the consumption public opinion analysis model; When the consumption request category is information query, provide information feedback corresponding to the consumption request category; When the consumption request category is a consumption analysis instruction, corresponding prompt information is generated, and according to the prompt information, the corresponding execution subject is prompted to perform the consumption analysis corresponding to the consumption analysis instruction and record the consumption record.

6. The method for analyzing consumer public opinion information according to claim 5, characterized in that: It also includes: after the consumption process between the consumer and the store clerk is completed, the consumption record is transmitted to the consumption information database; Based on the consumption information stored in the consumption information database, adjust the parameter weights of the consumer public opinion analysis model to optimize the recognition ability of the consumer public opinion analysis model; The consumption identification in the consumption information database is updated based on the consumption records and the feedback information obtained during the consumption process between the consumer and the store clerk.

7. The method for analyzing consumer public opinion information according to claim 1, characterized in that: Step S104 specifically includes: If the current consumption process is a consumption process between a consumer and a virtual store clerk, the consumption information needs to be analyzed and input into the consumption information and consumption public opinion analysis model to determine whether the consumption information and consumption public opinion analysis model has identified the specific consumption; When the consumption information and public opinion analysis model identifies specific consumption, the consumption analysis corresponding to the specific consumption is performed; When the consumption information and public opinion analysis model fails to identify specific consumption, the current consumption process is switched to the consumption process between the consumer and the store clerk; During the consumption process between consumers and store clerks, actual needs are identified based on historical consumption information, and auxiliary consumption analysis corresponding to actual needs is performed.

8. A consumer public opinion information analysis system, characterized by: The system is used to implement the consumer public opinion information analysis method according to any one of claims 1 to 7; the system includes: The consumption acquisition and screening module is used to obtain the consumption information set and extract the recent consumption information from the consumption information set, and use the recent consumption information as the consumption information to be analyzed; The consumption identification matching judgment module is used to match the consumption information to be analyzed with the consumption identification in the consumption information database to determine whether there is a consumption identification that matches the consumption information to be analyzed; The consumption analysis and feedback module is used to perform consumption analysis corresponding to the consumption identifier when there is a consumption identifier that matches the consumption information to be analyzed, generate feedback information based on the execution result, and output the feedback information to the public opinion monitoring platform; When there is no consumption identifier that matches the consumption information to be analyzed, determining the current consumption process, which includes the consumption process between the consumer and the virtual store clerk and the consumption process between the consumer and the store clerk; The virtual clerk scenario consumption public opinion analysis module is used to input the consumption information to be analyzed into the consumption information consumption public opinion analysis model if the current consumption process is a consumption process between a consumer and a virtual clerk. Based on the recognition results of the consumption information consumption public opinion analysis model, corresponding consumption analysis including information query consumption analysis, consumption process adjustment consumption analysis or guided consumption analysis is performed.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the consumer public opinion information analysis method as described in any one of claims 1 to 7 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the consumer public opinion information analysis method as described in any one of claims 1 to 7 are implemented.

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