Methods and electronic devices for providing product information
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HEMA (CHINA) CO LTD
- Filing Date
- 2025-12-25
- Publication Date
- 2026-05-26
Smart Images
Figure CN122089429A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of Internet application technology, and in particular to methods and electronic devices for providing product information. Background Technology
[0002] With the popularization of Internet applications and the continuous development of e-commerce platforms, more and more users are using e-commerce platforms to purchase the goods they need. For e-commerce platforms, how to help users efficiently connect to the products they need from a large amount of product information, thereby improving user experience and business efficiency, has always been a key research topic for the platforms. One of their solutions is the recommendation system.
[0003] The core of e-commerce platform recommendation systems is product recommendation technology. Its development has evolved from simple rules to complex, systematic engineering. Early rule-based recommendations relied on manually preset rules, such as recommending products with high sales volume or many clicks across the platform. While simple to implement, this couldn't meet the demands of large-scale applications driven by the rapid growth of e-commerce and users' personalized recommendation needs. Subsequently, recommendation systems based on collaborative filtering algorithms emerged. Their basic principle lies in identifying similarities between users or products based on historical user behavior, such as purchases and favorites, and using this similarity for predictive recommendations. Collaborative filtering algorithms mainly include user-based collaborative filtering and product-based collaborative filtering. While collaborative filtering-based recommendation systems have achieved automation and addressed personalized recommendation needs to some extent, they still have drawbacks, such as data sparsity (making it difficult to find similar users or products when behavioral data is sparse) and popularity bias. Another direction in the development of recommender systems is content-based recommendation technology. Its key feature is analyzing the attributes and characteristics of products themselves to recommend items similar to the user's preferences. This technology offers strong interpretability of recommendation results, but also suffers from drawbacks such as reliance on high-quality feature extraction and inability to utilize other information. With the continuous development of recommender systems, the technology has entered the algorithmic era. Recommender systems based on various machine learning algorithms have become mainstream applications. In this approach, user characteristics, item characteristics, and behavioral characteristics can be expressed as feature vectors using machine learning algorithms. Then, specific learning algorithms are used to obtain machine learning models, which are then used to predict user preferences. The benefits of automated algorithms include improved processing power and increased efficiency and accuracy in recommending products. However, traditional automated algorithm-based recommender systems still rely solely on user and product data, such as user browsing history, purchase records, search keywords, and product data like category, price, reviews, and sales volume. When meeting specific recommendation needs, the relevance of the recommendation results to user needs and the interactivity of the recommendation process still require further improvement. Summary of the Invention
[0004] This application provides a method and electronic device for providing product information, as disclosed in the embodiments of this application. This method can improve the interactivity and fun of product recommendations, meet scenario-based needs, and increase the relevance between recommended products and user interests.
[0005] This application provides the following solution: A method for providing product information includes: Receive AI interaction requests and provide a user interaction interface after receiving the AI interaction request; Determine the interaction scenario information corresponding to the current interaction request, and the product category information corresponding to the interaction scenario information; Based on a pre-set AI model, and according to the interactive scenario information, the category information, and the preset brand image, generate first interactive content corresponding to the interactive scenario and the category information, and display the first interactive content in the user interface; Receive interactive information input by the user and determine the user's current emotional state information; Based on the user-inputted interaction information and the scene information, generate second interactive content and recommended product information corresponding to the emotional state information and the scene information, and display the second interactive content and the recommended product information.
[0006] The step of determining the interaction scenario information corresponding to the current interaction request, and the product category information corresponding to the interaction scenario information, includes: The interactive scenario information and the product category information are determined based on the current date.
[0007] The step of determining the interaction scenario information corresponding to the current interaction request, and the product category information corresponding to the interaction scenario information, includes: Based on the page characteristics of the entry page that receives the AI interaction request or the product characteristics of the products within the entry page, the interaction scenario information and the category information are determined.
[0008] The step of determining the interaction scenario information corresponding to the current interaction request, and the product category information corresponding to the interaction scenario information, includes: The interactive scenario information and the product category information are determined based on the current user's identity information.
[0009] Generating the first interactive content corresponding to the interactive scenario and the category information includes generating one or any combination of the following interactive contents: The first text related to the interactive scene information; The preset brand image's facial animation; The preset brand image simulates the output audio; Wearable items representing the pre-defined brand image; The handheld object representing the preset brand image; The scene animation of the preset brand image.
[0010] If the first interactive content or the second interactive content contains text content or audio content, the text content or audio content is generated by the AI model in a human-like style.
[0011] The generation of second interactive content and recommended product information corresponding to the emotional state information and the scene information includes: Generate one or any combination of the following interactive content: Second text related to the interactive scene information; The preset brand image's facial animation; The preset brand image simulates the output audio; The scene animation of the preset brand image; Description information of the products to be recommended.
[0012] The step of receiving interactive information input by the user and determining the user's current emotional state information includes: Receive interactive information input by the user and determine the user's current emotional state in real time; The step of generating second interactive content and recommended product information corresponding to the emotional state information and the scene information based on the user-input interactive information and the scene information includes: Based on the current interactive information input by the user, a second interactive content is generated in real time so that the generated second interactive content can match the emotional state information in real time.
[0013] The step of receiving interactive information input by the user and determining the user's current emotional state information includes: The system receives interactive information input by the user and uses a pre-built lightweight sentiment analysis model to determine the user's current emotional state based on the interactive information input by the user.
[0014] The first interactive content includes image or text content, wherein the image or text content includes operable anchor units, and the method further includes: User operations are received through the anchor point unit; After receiving a user operation through the anchor unit, third interactive content is generated and provided based on the preset AI model.
[0015] The generation and provision of third-party interactive content includes: Based on a pre-set AI model and according to the interactive scenario information and the product category information, interactive scheme information or interactive prompt information related to the interactive scenario information is generated and provided.
[0016] Also includes: Based on the user's actions regarding the displayed recommended product information, determine the content of the next interaction.
[0017] An electronic device, comprising: One or more processors; and A memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform the steps of any of the preceding methods.
[0018] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application utilizes an AI model-based dialogue interaction method to provide product recommendations to users. Leveraging the learning and output capabilities of AI models, it enhances the processing power and efficiency of automated algorithms while improving the interactivity and engagement of recommended products. The interactive content provided by this method is relevant to the defined current interactive scenario, ensuring that the interactive content and recommended products better align with user expectations in the current context, thus fulfilling specific scenario-based needs for interaction and product recommendation. Furthermore, it considers the user's emotional state during the interaction, providing more engaging, personalized, highly interactive, and entertaining product recommendations. This method enhances user participation and emotional resonance during scenario-based shopping, strengthens visual appeal and interactive experience, and effectively increases user attention, click-through rate, and purchase intention. Of course, any product implementing this application does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description
[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0020] Figure 1 This is a flowchart of the method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the first application provided in the embodiments of this application; Figure 3 This is a schematic diagram of the second application provided in the embodiments of this application; Figure 4 This is a schematic diagram of a third application provided in the embodiments of this application; Figure 5 This is a schematic diagram of the device provided in the embodiments of this application; Figure 6 This is a schematic diagram of the electronic device provided in the embodiments of this application. Detailed Implementation
[0021] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.
[0022] With the in-depth application of algorithm technology, the development of recommender systems has also shown new trends. However, existing automated algorithm-based recommender systems are still only based on user and product data. When meeting specific needs, the matching degree between the recommendation results and user needs, as well as the interactivity of the recommendation process, still need further improvement. In some specific scenarios, such as holiday scenarios, the recommendation results generated by existing recommender systems lack contextual consideration and cannot meet users' contextual recommendation needs. In addition, during the interaction process, traditional product recommendation methods mainly rely on keyword search, category browsing, or algorithm recommendation, without paying attention to the user's emotional state and changes, making it difficult to stimulate users' deep purchase motivation. The user experience is relatively tool-like, lacking fun and emotional resonance, and the interactivity of the recommendation process still needs further improvement. The method for providing product information provided in this application embodiment realizes a product recommendation method based on artificial intelligence (AI) algorithm model, which meets the needs of specific scenarios and has the ability to capture the user's emotional state in real time. The product recommendation thus realized has the processing power and efficiency brought by the automated algorithm, while also meeting the specific scenario requirements. Moreover, it pays attention to the user's emotional state during the interaction process, and can provide more interesting, personalized, highly interactive and fun interactive product recommendations.
[0023] The specific technical solutions provided in the embodiments of this application will be described in detail below.
[0024] First, this application provides a method for providing product information, please refer to the embodiments below. Figure 1 The flowchart is for the method provided in the embodiments of this application, such as... Figure 1 As shown, the method may include the following steps: S101: Receive AI interaction request, and provide user interaction interface after receiving the AI interaction request; The method for providing product information provided in this application embodiment first receives an AI interaction request in the client. Upon receiving the AI interaction request, a user interface is provided, such as an operation unit for the AI interaction request within a portable device's app. This operation unit receives user actions, thereby receiving the AI interaction request. The AI interaction request may include a request to interact with the platform's AI model. The operation unit for the AI interaction request can be provided on in-app pages in different application scenarios, such as on specific activity pages (e.g., "New Year's Goods" themed pages, product ranking pages, etc.) or on specific product display pages. It can take the form of an operable button, such as an "AI Assistant" or "AI Help" button. After receiving the AI interaction request, a dedicated user interface can be provided in the client application. This user interface can be a newly created independent interface or a floating page on top of the current page. Figure 2 The diagram shown is a first application illustration of the method for providing product information provided in this application embodiment. Figure 2 The image shows a user interface related to a "New Year" interactive scene, which includes interactive content generated based on a pre-set AI model, such as text related to the interactive scene information 201, and a preset brand image wearing items with interactive scene characteristics 202.
[0025] In one implementation, the provided user interface may further include multiple different themes, each of which may be related to different interactive scenarios, or may include different content designs related to the same interactive scenario. In this implementation, the interactive content display area, for example... Figure 2 The display area containing text 201 and the preset brand image 202 uses a carousel to display interactive content with different themes or different content designs. It should be noted that the examples of user interface content displayed in this step are for illustrative purposes only and do not affect the order of the steps in the method.
[0026] S102: Determine the interaction scenario information corresponding to the current interaction request, and the product category information corresponding to the interaction scenario information; As mentioned above, the method for providing product information provided in this application takes into account product recommendations under specific scenario requirements, in order to meet the specific scenario-based needs of product recommendations. Specific interactive scenarios can be specific social activity scenarios, such as folk festivals (e.g., the Chinese Lunar New Year), or interactive scenarios based on user needs (e.g., "light food for weight loss" scenarios, "nutritional supplement" scenarios, etc.). In this step, the interactive scenario information corresponding to the current interactive request, and the product category information corresponding to the interactive scenario information, can be determined. Specifically, the interactive scenario information and category information can be determined based on the current date. For example, a festival approaching the current date can be identified, and the festival scenario can be identified as the interactive scenario information. The products related to that festival can be identified as the product category information corresponding to the interactive scenario information. Specifically, for example, when the current date is determined to be approaching the Chinese Lunar New Year, the interactive scenario information can be identified as the "New Year" interactive scenario, and "New Year's goods" can be identified as the product category information corresponding to the interactive scenario information.
[0027] In another implementation, the interaction scenario information and category information can be determined based on the page characteristics of the entry page receiving the AI interaction request or the product characteristics of the products within the entry page. For example, when the entry page for the AI interaction request is a theme page for a certain festival, the festival can be identified as the interaction scenario information based on the page's theme, and the category related to that festival can be identified as the corresponding product category information. When the entry page for the AI interaction request is a product page, such as when a user initiates an AI interaction request through a product's details page, the interaction scenario information and category information can be determined based on the corresponding product characteristics of the product page. For example, when the product is a nutritional supplement, the "nutritional supplement" demand scenario can be identified as the interaction scenario information, and the "nutritional supplement" category can be identified as the product category information corresponding to that interaction scenario information.
[0028] In addition, interactive scenario information and category information can be determined based on the current user's identity information. For example, interactive scenario information and category information can be determined based on the current user's nationality information. That is, when the current user is a person of a certain nationality, interactive scenario information and category information can be determined based on the food, festivals and other habits of that country.
[0029] The process of determining the interactive scenario information corresponding to the current interactive request, as well as the product category information corresponding to the interactive scenario information, can also be automatically completed by the pre-built AI system. When a user initiates an AI interactive request, the system automatically collects one or more types of information, such as the current date information, the page features of the entry page or the product features of the products within the entry page, or the current user's identity information, etc., and then the pre-built AI system determines the interactive scenario information and the product category information corresponding to the interactive scenario information.
[0030] S103: Based on a preset AI model, and according to the interactive scenario information, the category information, and a preset brand image, generate first interactive content corresponding to the interactive scenario and the category information, and display the first interactive content in the user interface; The method for providing commodity information provided in the embodiments of the present application can use a preset AI model to implement interactive product recommendations. The preset artificial intelligence (AI) model can be a trained application model and can be implemented based on intelligent algorithms. In practical applications, in order to improve the capabilities of the AI model in scenario recognition and emotion capture in the e-commerce field, when training the preset AI model, focused adjustments or enhancements can be made in the aspects of scenario recognition and emotion capture in the e-commerce field of the model. The preset AI model can be placed in the background. For example, it can be a model placed on the server side or a client model with local generation capabilities. After receiving an AI interaction request, first interactive content corresponding to the interactive scenario and the category information can be generated according to the interactive scenario information, the determined category information, and the preset brand image, and the generated first interactive content can be displayed in the user interface. In this way, the generated first interactive content can have elements reflecting the interactive scenario, and the generated content can echo the interactive scenario, making the generated interactive content more suitable for the current interactive scenario and improving the fit between the interactive content and the interactive scenario.
[0031] In practical applications, the preset AI model can be a model with multimodal generation capabilities. For example, when generating the first interactive content, it can generate one or any combination of the following interactive contents: a first text related to the interactive scenario information; an expression animation of the preset brand image; an audio simulated and output by the preset brand image; wearable items of the preset brand image; a handheld item of the preset brand image (the handheld item can be an image of an item related to the current interactive scenario, or it can also be an image related to the above commodity category information); and a scenario action animation of the preset brand image (such as a scenario action animation of the preset brand image paying New Year greetings in the "New Year" interactive scenario), etc. The generated first interactive content can be an interactive content that embodies and reflects the corresponding interactive scenario. For example, it can have elements reflecting the interactive scenario, making the generated content echo the interactive scenario. For example Figure 2 the lanterns included in the background in, the clothing with a festive atmosphere of the preset brand image, the "handheld" blessing character, the generated text related to the New Year, etc. all echo the "New Year" interactive scenario. The first interactive content can include text content or audio content. The text content or audio content can be generated by the preset AI model in an anthropomorphic style to shorten the psychological distance from the user during the interaction with the preset AI and increase the authenticity and interest of the interaction.
[0032] S104: Receive interactive information input by the user and determine the user's current emotional state information; The method for providing product information provided in this application, when providing recommended product information in an interactive manner, not only considers the interactive scenario of the recommended products but also takes into account the user's current emotional state information. That is, it also generates interactive content that matches the user's current emotional state information. To achieve this, the method first receives interactive information input by the user and determines the user's current emotional state information. The user's current emotional state information reflects the user's current emotional state and can be determined based on the analysis of the user's input content using a specific algorithm model. Existing natural language sentiment analysis models can be used, or a dedicated sentiment analysis model can be developed. The sentiment analysis model in this method can be an independent sentiment analysis model that passes the analysis results to a pre-set AI model, or it can be a component of a pre-set AI model, such as a layer of a pre-set AI model. In this implementation, it can be understood that the process of determining the user's current emotional state information is based on the aforementioned pre-set AI model.
[0033] In another implementation, user-input interactive information can be received. A pre-built lightweight sentiment analysis model is then used to determine the user's current emotional state based on this input, thereby improving the efficiency of sentiment state analysis while ensuring accuracy. User input can be made through input components on the user interface. Depending on the processing capabilities of the pre-built AI model, the user-input interactive information can include different preset types, such as text, voice, images, and videos.
[0034] S105: Based on the user-inputted interaction information and scene information, generate second interactive content and recommended product information corresponding to the emotional state information and scene information, and display the second interactive content and the recommended product information.
[0035] After determining the user's current emotional state, second interactive content and recommended product information corresponding to the user's input interaction information and scene information can be generated. Specifically, depending on the scope of influence of the emotional state information, different implementation methods can be used. In one implementation, the emotional state information may only affect the generation of interactive content, i.e., only reacting to the current emotional state in terms of interactive content. In another implementation, the emotional state information may affect both the generation of interactive content and the determination of recommended products, i.e., reacting to the current emotional state from both the generated interactive content and the recommended product information. The latter implementation method is preferred in this embodiment. Specifically, based on the user's input interaction information and scene information, a pre-built AI model can generate second interactive content and recommended product information corresponding to the emotional state and scene information.
[0036] After determining the second interactive content and the product information to be recommended, these can be displayed. Specifically, they can be shown in the application's user interface. Utilizing the multimodal output capabilities of the pre-built AI model, the second interactive content can include one or any combination of the following: second text related to the interactive scene information (usually a response to user input); animated expressions of a preset brand image; audio output simulating the preset brand image; scene action animations of a preset brand image; and explanatory information about the product information to be recommended, such as operation methods and production techniques. The diversity of interactive content types generated by the pre-built AI demonstrates the effective application of the multimodal output capabilities of the pre-built AI model in the recommendation system, increasing the richness of the interactive content. Similar to the first interactive content mentioned above, the second interactive content can contain text or audio content, which can be generated by the pre-built AI model in a human-like style.
[0037] like Figure 3 The diagram shown is a second application illustration of the method for providing product information provided in this application embodiment. Figure 3 The example shows user-inputted interactive information, as well as second interactive content and product information to be recommended, generated based on a pre-built AI model and corresponding to emotional state and scene information. Figure 3 Interactive information content 311 and interactive information content 341 are user-input interactive information in different examples. The user-input interactive information usually represents the user's current interactive needs. After receiving the user-input interactive information, the pre-built AI model can analyze and determine the user's current emotional state information and generate content. Figure 3The generated content shown includes second interactive content corresponding to the emotional state information and scene information, generated interactive content 312 and interactive content 342. The preset AI model also outputs product information to be recommended, such as product information 313 in Example 3(a) and product information 343 in Example 3(b). Product information 313 includes multiple product display units for displaying multiple generated product information. In addition to displaying multiple generated product information, product information 343 also provides information about the production method of the product generated by the preset AI model, which improves the richness of the interactive content.
[0038] Furthermore, since emotional states are variable, in another implementation, during AI interaction, after receiving user input, the system can analyze the current user interaction information in real time to determine the user's current emotional state. Based on this, a second interactive element can be generated in real time, ensuring that the generated second interactive element matches the emotional state information. The generation strategy and content can be adjusted in real time; for example, the animation style of a preset brand image and the tone of the audio can be adjusted to match the analyzed emotional state information. When emotional state information also affects the determination of recommended products, recommended product information can be generated in real time, ensuring that the recommended product information also matches the analyzed emotional state information. This increases the real-time nature of the interactive content output by the recommendation system in meeting the user's emotional state needs and satisfying the dynamic changes in the user's emotional state.
[0039] In another implementation, the first interactive content may include image or text content, which may include operable anchor units. User actions are received through these anchor units. After receiving user actions through the anchor units, third interactive content can be generated and provided based on a pre-set AI model. For example... Figure 4 The diagram shown is a third application illustration of the method for providing product information provided in this application embodiment. Figure 4 The image illustrates an example of providing operable anchor units within an image of first interactive content, and generating and providing third interactive content after the user interacts with the anchor units. Figure 4In the two examples shown, 4(a) a handheld gift box with a preset brand image is anchored by anchor unit 411 "gift box", and 4(b) a handheld food item with a preset brand image is anchored by anchor unit 421 "preserved meat". After anchor unit 411 is operated, a third interactive content text 412 is generated and provided based on a preset AI model. After anchor unit 421 is operated, a third interactive content text 422 is generated and provided based on a preset AI model. In one implementation, the object anchored by the anchor unit can be an object related to specific product or category information. This object can be generated or determined by a preset AI model based on the category information of the product related to the interactive scene information retrieved in the aforementioned steps.
[0040] In addition, when generating and providing third-party interactive content, it is also possible to generate and provide interactive solution information or interactive prompt information related to the interactive scenario information based on a pre-built AI model and according to the interactive scenario information and category information, such as... Figure 4 The interactive prompt information 413 shown in Figure 4(a) generates and provides interactive solution information or interactive prompt information related to the interactive scenario information. On the one hand, it can facilitate users to select the solution or interactive method in the current interactive scenario, and on the other hand, it can help and guide users to ask interactive questions, which is convenient for users and improves the efficiency of interaction.
[0041] In another implementation, the content of the next interaction can be determined based on the user's actions on the displayed recommended product information. When a user interacts with the displayed recommended product information, such as clicking, it often indicates interest in the product. In this case, the interaction content can be iterated in real-time based on the user's actions, forming a closed-loop mechanism of "input—generation—click—optimization." This improves the alignment between the interaction content and the user's interests, thereby enhancing product recommendation satisfaction and user experience.
[0042] The above provides a detailed description of the method for providing product information provided in the embodiments of this application. This method can provide a user interface after receiving an AI interaction request; determine the interaction scenario information corresponding to the current interaction request, and the product category information corresponding to the interaction scenario information; generate first interactive content corresponding to the interaction scenario and category information based on a preset AI model, and according to the interaction scenario information, category information, and preset brand image; receive interactive information input by the user, and determine the user's current emotional state information; generate second interactive content and recommended product information corresponding to the emotional state information and scenario information based on the user's input interactive information and scenario information, and provide the second interactive content and recommended product information. This method provides product recommendations to users through AI-model-based dialogue interaction. Leveraging the learning and output capabilities of AI models, it ensures the processing power and efficiency of automated algorithms while enhancing the interactivity and engagement of recommended products. The interactive content provided by this method is relevant to the defined current interactive scenario, making the content and recommended products more aligned with user expectations in that context. This satisfies the specific scenario-based needs of interaction and product recommendation, thereby increasing the alignment between recommended products and user interests. Furthermore, it considers the user's emotional state during the interaction, providing more engaging, personalized, and interactive product recommendations. This method enhances user participation and emotional resonance during scenario-based shopping, strengthens visual appeal and interactive experience, and effectively increases user attention, click-through rates, and purchase intentions. By transforming products into "emotional carriers," it strengthens the emotional value of product recommendations in specific scenarios, achieving an upgrade from functional recommendations to emotionally supportive shopping guidance.
[0043] Corresponding to the method for providing product information provided in the embodiments of this application, an apparatus for providing product information is also provided, such as... Figure 5 The diagram shown is a schematic representation of a device for providing product information according to an embodiment of this application. This device may include: The interface providing unit 501 is used to receive AI interaction requests and provide a user interaction interface after receiving the AI interaction request; The scene information determination unit 502 is used to determine the interaction scene information corresponding to the current interaction request, and the product category information corresponding to the interaction scene information; The first content processing unit 503 is used to generate first interactive content corresponding to the interactive scenario and category information based on a preset AI model, interactive scenario information, category information, and preset brand image, and to display the first interactive content in the user interface. The emotion state processing unit 504 is used to receive interactive information input by the user and determine the user's current emotion state information; The second content processing unit 505 is used to generate second interactive content and recommended product information corresponding to the emotional state information and scene information based on the interactive information and scene information input by the user, and to display the second interactive content and recommended product information.
[0044] In one implementation, the scene information determination unit 502 can be used to determine interactive scene information and category information based on the current date.
[0045] In another implementation, the scene information determination unit 502 can be used to determine the interactive scene information and category information based on the page characteristics of the entry page that receives the AI interaction request or the product characteristics of the products within the entry page.
[0046] In another implementation, the scene information determination unit 502 can be used to determine the interactive scene information and category information based on the current user's identity information.
[0047] Generating first interactive content corresponding to the interactive scenario and category information includes generating one or any combination of the following interactive contents: The first text related to the interactive scene information; Pre-set brand image facial animations; The preset brand image is simulated in the audio output. Wearable items that are designed to project a pre-existing brand image; Handheld items that pre-define the brand image; Scene animations that pre-define the brand image.
[0048] In one implementation, if the first or second interactive content contains text or audio content, the text or audio content is generated by an AI model in a human-like style.
[0049] In addition, generating second interactive content corresponding to emotional state information and scene information, as well as product information to be recommended, can be one or any combination of the following interactive content: Secondary text related to interactive scene information; Pre-set brand image facial animations; The preset brand image is simulated in the audio output. Scene animations that pre-define the brand image; Description information of the products to be recommended.
[0050] In another implementation, the emotion state processing unit 504 can be used to receive interactive information input by the user and determine the user's current emotion state information in real time. In this implementation, the second content processing unit 505 can be used to generate second interactive content in real time based on the current interactive information input by the user, so that the generated second interactive content can match the emotional state information in real time.
[0051] In one implementation, the emotion state processing unit 504 can also be used to receive interactive information input by the user and use a pre-built lightweight sentiment analysis model to determine the user's current emotional state information based on the interactive information input by the user.
[0052] In another implementation, the first interactive content includes image or text content, which includes operable anchor units, and the device may further include: The third content processing unit is used to receive user operations through the anchor unit; after receiving user operations through the anchor unit, it generates and provides third interactive content based on a pre-set AI model.
[0053] Among them, generating and providing third-party interactive content can be based on a pre-set AI model and, according to interactive scenario information and category information, generate and provide interactive solution information or interactive prompt information related to the interactive scenario information.
[0054] In one implementation, the second content processing unit 505 can be used to: Based on the user's actions regarding the displayed recommended product information, determine the content of the next interaction.
[0055] This device provides product recommendations to users through AI-model-based dialogue interaction. Leveraging the learning and output capabilities of AI models, it maintains the processing power and efficiency of automated algorithms while enhancing the interactivity and engagement of recommended products. The interactive content provided by this method is relevant to the defined current interactive scenario, ensuring that the content and recommended products better align with user expectations in that context, thus fulfilling specific scenario-based needs for interaction and product recommendation. Furthermore, it considers the user's emotional state during the interaction, providing more engaging, personalized, highly interactive, and entertaining product recommendations. This method increases user participation and emotional resonance during scenario-based shopping, enhances visual appeal and interactive experience, and effectively improves user attention, click-through rates, and purchase intentions.
[0056] It should be noted that the embodiments of this application may involve the use of user data. In practical applications, user-specific personal data may be used in the scheme described herein within the scope permitted by applicable laws and regulations, provided that it complies with the applicable laws and regulations of the country (e.g., with the user's explicit consent, with the user being properly notified, etc.).
[0057] In addition, embodiments of this application also provide a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method described in the foregoing method embodiments.
[0058] And an electronic device, comprising: One or more processors; and A memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform the steps of the method described in the foregoing method embodiments.
[0059] A computer program product includes a computer program / computer executable instructions that, when executed by a processor in an electronic device, implement the steps of the method described in the foregoing method embodiments.
[0060] in, Figure 6 The architecture of an electronic device is illustrated by example. For instance, device 600 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, aircraft, etc.
[0061] Reference Figure 6 The device 600 may include one or more of the following components: processing component 602, memory 604, power supply component 606, multimedia component 608, audio component 610, input / output (I / O) interface 612, sensor component 614, and communication component 616.
[0062] Processing component 602 typically controls the overall operation of device 600, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 602 may include one or more processors 620 to execute instructions to perform all or part of the steps of the methods provided in this disclosure. Furthermore, processing component 602 may include one or more modules to facilitate interaction between processing component 602 and other components. For example, processing component 602 may include a multimedia module to facilitate interaction between multimedia component 608 and processing component 602.
[0063] Memory 604 is configured to store various types of data to support the operation of device 600. Examples of this data include instructions for any application or method operating on device 600, contact data, phonebook data, messages, pictures, videos, etc. Memory 604 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.
[0064] Power supply component 606 provides power to various components of device 600. Power supply component 606 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to device 600.
[0065] Multimedia component 608 includes a screen that provides an output interface between device 600 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of touch or swipe actions but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 608 includes a front-facing camera and / or a rear-facing camera. When device 600 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.
[0066] Audio component 610 is configured to output and / or input audio signals. For example, audio component 610 includes a microphone (MIC) configured to receive external audio signals when device 600 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 604 or transmitted via communication component 616. In some embodiments, audio component 610 also includes a speaker for outputting audio signals.
[0067] I / O interface 612 provides an interface between processing component 602 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.
[0068] Sensor assembly 614 includes one or more sensors for providing status assessments of various aspects of device 600. For example, sensor assembly 614 may detect the on / off state of device 600, the relative positioning of components such as the display and keypad of device 600, changes in the position of device 600 or a component of device 600, the presence or absence of user contact with device 600, the orientation or acceleration / deceleration of device 600, and temperature changes of device 600. Sensor assembly 614 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 614 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 614 may also include an accelerometer, a gyroscope, a magnetometer, a pressure sensor, or a temperature sensor.
[0069] Communication component 616 is configured to facilitate wired or wireless communication between device 600 and other devices. Device 600 can access wireless networks based on communication standards, such as WiFi, or mobile communication networks such as 2G, 3G, 4G / LTE, and 5G. In one exemplary embodiment, communication component 616 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 616 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
[0070] In an exemplary embodiment, device 600 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.
[0071] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 604 including instructions, which can be executed by a processor 620 of device 600 to perform the method provided by the present disclosure. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.
[0072] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.
[0073] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The systems and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.
[0074] The method and electronic device for providing product information provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and its core ideas. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A method for providing product information, characterized in that, include: Receive AI interaction requests and provide a user interaction interface after receiving the AI interaction request; Determine the interaction scenario information corresponding to the current interaction request, and the product category information corresponding to the interaction scenario information; Based on a pre-set AI model, and according to the interactive scenario information, the category information, and the preset brand image, generate first interactive content corresponding to the interactive scenario and the category information, and display the first interactive content in the user interface; Receive interactive information input by the user and determine the user's current emotional state information; Based on the user-inputted interaction information and the scene information, generate second interactive content and recommended product information corresponding to the emotional state information and the scene information, and display the second interactive content and the recommended product information.
2. The method according to claim 1, characterized in that, The step of determining the interaction scenario information corresponding to the current interaction request, and the product category information corresponding to the interaction scenario information, includes: The interactive scenario information and the product category information are determined based on the current date.
3. The method according to claim 1, characterized in that, The step of determining the interaction scenario information corresponding to the current interaction request, and the product category information corresponding to the interaction scenario information, includes: Based on the page characteristics of the entry page that receives the AI interaction request or the product characteristics of the products within the entry page, the interaction scenario information and the category information are determined.
4. The method according to claim 1, characterized in that, The step of determining the interaction scenario information corresponding to the current interaction request, and the product category information corresponding to the interaction scenario information, includes: The interactive scenario information and the product category information are determined based on the current user's identity information.
5. The method according to claim 1, characterized in that, Generating the first interactive content corresponding to the interactive scenario and the category information includes generating one or any combination of the following interactive contents: The first text related to the interactive scene information; The preset brand image's facial animation; The preset brand image simulates the output audio; Wearable items representing the preset brand image; The handheld object representing the preset brand image; The scene animation of the preset brand image.
6. The method according to claim 1, characterized in that, If the first interactive content or the second interactive content contains text content or audio content, the text content or audio content is generated by the AI model in a human-like style.
7. The method according to claim 1, characterized in that, The generation of second interactive content and recommended product information corresponding to the emotional state information and the scene information includes: Generate one or any combination of the following interactive content: Second text related to the interactive scene information; The preset brand image's facial animation; The preset brand image simulates the output audio; The scene animation of the preset brand image; Description information of the products to be recommended.
8. The method according to claim 1, characterized in that, The step of receiving interactive information input by the user and determining the user's current emotional state information includes: Receive interactive information input by the user and determine the user's current emotional state in real time; The step of generating second interactive content and recommended product information corresponding to the emotional state information and the scene information based on the user-input interactive information and the scene information includes: Based on the current interactive information input by the user, a second interactive content is generated in real time so that the generated second interactive content can match the emotional state information in real time.
9. The method according to claim 1, characterized in that, The step of receiving interactive information input by the user and determining the user's current emotional state information includes: The system receives interactive information input by the user and uses a pre-built lightweight sentiment analysis model to determine the user's current emotional state based on the interactive information input by the user.
10. The method according to claim 1, characterized in that, The first interactive content includes image or text content, wherein the image or text content includes operable anchor units, and the method further includes: User operations are received through the anchor point unit; After receiving a user operation through the anchor unit, third interactive content is generated and provided based on the preset AI model.
11. The method according to claim 10, characterized in that, The generation and provision of third-party interactive content includes: Based on a pre-set AI model and according to the interactive scenario information and the product category information, interactive scheme information or interactive prompt information related to the interactive scenario information is generated and provided.
12. The method according to claim 1, characterized in that, Also includes: Based on the user's actions regarding the displayed recommended product information, determine the content of the next interaction.
13. An electronic device, characterized in that, include: One or more processors; as well as A memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform the steps of the method according to any one of claims 1 to 12.