1410 results about "Recipe" patented technology

A system can process an indication of user data, wherein the user data comprises a food item including at least one recipe having one or more ingredients, and a query, wherein the query is associated with at least one ingredient, and generate, based at least in part on the query, nutrition data associated with the at least one ingredient, wherein the nutrition data comprises preparation data, sourcing data, delivery data, and a list of nutrients for the at least one ingredient. The system can further estimate, based at least in part on the nutrition data associated with the least one ingredient, a nutritional score, then compare the estimated nutritional score to a threshold, and based on the compared nutritional score, generate one or more instructions to cause an indication of the nutritional score on a user device.

Systems and techniques for are described herein. Natural language workflow descriptions are received from expert users, the descriptions are processed using language models to identify action sequences, and directed acyclic graphs (DAGs) are generated that represent workflows by mapping actions to automated agents. These DAGs are stored as composite action recipes in a vector database. End users can then submit natural language queries, which the system matches to stored recipes. Selected recipes are executed in a sandboxed environment, with the system sequentially invoking automated agents according to the DAG structure. The systems and techniques described herein provide real-time feedback during execution and support features such as graphical workflow validation, dynamic parameter collection, role-based access control, and dry run simulations. This approach enables efficient creation and reuse of complex workflows based on natural language inputs.

To provide an information processing method, an information processing device and a program capable of easily customizing a recipe in accordance with equipment and utensils owned by a user.SOLUTION: An information processing method includes the steps of: acquiring a first recipe including a plurality of blocks including first information indicating equipment and utensils to be used in a plurality of cooking steps; acquiring second information indicating equipment and utensils owned by a user and information indicating operating states of the equipment and the utensils indicated by the second information; generating a second recipe obtained by deleting, from the first recipe, blocks including equipment and utensils that are included in the first information but are not included in the second information and blocks including equipment and utensils having an operating state indicating being in operation; and outputting information indicating the second recipe to be displayed on a display.SELECTED DRAWING: Figure 14

An online system retrieves historical interaction data for a user describing objects with which the user previously interacted and health data associated with the user. The system accesses and applies a multiclass classification model to classify whether the user has each of a set of health conditions based on the historical interaction and health data. The system generates a prompt including a set of classes associated with the user and a request for a set of objects appropriate for the user, in which the set of classes indicates whether the user has each health condition and an appropriateness of an object is based on whether the user has each health condition. The system provides the prompt to a large language model to obtain a textual output, extracts one or more objects (e.g., items and / or recipes) from the output, and sends a recommendation for the object(s) for display to the user.

The invention discloses a recipe retrieval method based on modal interaction, and the method is specifically implemented according to the following steps: 1, obtaining a cross-modal recipe retrieval data set, and dividing the cross-modal recipe retrieval data set into a training set and a test set; step 2, constructing a cross-modal recipe retrieval network model based on interaction between fine-grained modals; 3, using a training set to train the cross-modal recipe retrieval network model based on the interaction between the fine-grained modals constructed in the step 2; 4, testing the network model trained in the step 3 by using a test set to obtain a recipe text retrieval image result, and evaluating the retrieval result; and 5, testing the network model trained in the step 3 on the test set to obtain a recipe image retrieval text result, and evaluating the retrieval result. The problem that in the prior art, due to the fact that semantic gaps between different modes exist in a cross-modal recipe retrieval task, accuracy of cross-modal recipe retrieval is insufficient is solved.

The invention relates to the technical field of intelligent cook machine recommendation, and discloses an intelligent cook machine recipe recommendation and operation control method, which comprises a user input module used for receiving user instructions including food material types, cooking targets, diet restrictions and equipment models; the recognition module is used for collecting food material weight and state data; the data processing module adopts a multi-modal fusion algorithm; the recipe recommendation module is based on an improved collaborative filtering algorithm and a knowledge graph; and the output module is used for controlling the instruction generation unit to output a sectional operation instruction set according to the selected recipe. By integrating the image recognition unit and the weight sensor, the type, weight and state data of food materials placed in the chef machine by a user can be collected in real time, and correction processing is carried out in combination with the environment temperature and humidity sensor; therefore, the existing food material inventory of the user can be accurately considered during recipe recommendation, and the problem that the existing food materials of the user cannot be fully utilized during recipe recommendation by an existing system is solved.

A recipe search support apparatus 10 is provided with: a storage unit 11 to hold recipe information; an information storage unit 100 configured to, when a recipe site receives a use report of a recipe from a user, receive an input of feature information of the recipe and store the feature information in association with the recipe and the use report in the storage unit 11; and an information output unit 101 configured to, when the recipe site receives a recipe search request, search the storage unit 11 for feature information matching a search keyword included in the request and output at least one of a recipe and a use report associated with the feature information.

In a dietary modification computing system, a taste-restrictions combination neural network generates a taste-restrictions vector based on a combination of restriction profile data and taste profile data. Also, a recipe-restrictions combination neural network generates a recipe-restrictions vector based on a combination of the restriction profile data and recipe data. An entity-recipe relational recommendation module generates entity-recipe prediction data that describing similarity among the taste-restrictions vector and the recipe-restrictions vector. An entity-recipe relational modification module generates optimization data that identifies an impact of the recipe data on the similarity. Based on the impact data identified by the optimization data, the dietary modification computing system generates modified recipe data that includes substitution recipe data and omits additional recipe data associated with the impact data. The dietary modification computing system provides the modified recipe data to one or more additional computing systems.

The invention discloses a customer health data intelligent management system and method, and belongs to the technical field of health data management. Basic data and health data are collected; the client inputs a daily menu and calculates nutrients; establishing a daily nutrient matrix based on nutrients, and identifying a diet mode; defining a taste space, and extracting taste features based on the seasoning use condition of the menu every day; integrating to form an input vector; establishing a personalized nutrition demand prediction model, and training to obtain nutrition constraints; retrieving the candidate recipes based on nutrition constraints, and performing taste matching to obtain recommended recipes; based on the menu selection records of the similar clients, the recommended menu is optimized; dynamically adjusting the recommendation strategy according to the score of the customer for the recommended menu to obtain an optimal menu; when the customer eats the optimal menu, the change of health data before and after diet intervention is calculated, and the intervention effect is quantified; nutrients needed by the client are adjusted based on the intervention effect, and the optimal menu is correspondingly adjusted.

To provide a system.SOLUTION: A system includes: means for analyzing numerical data included in the result of health screening provided by a user that indicates the health state of the user; means for inputting a specific prompt sentence to a generative AI model and thereby providing, on the basis of the analysis result, advice on the health habit and meal of the user and the exercise performed by the user, as advice on the health of the user; means for providing, on the basis of the analysis result, the user with a one-week recipe customized in conformity with the heath state of the user; means for analyzing the photographs of the meal registered by the user and proposing a plan for improving the meal of the user; and optimization means for optimizing the advice on health and the recipe on the basis of emotion by using an emotion engine that recognizes the emotion of the user and the generative AI model.SELECTED DRAWING: Figure 1

The invention relates to the technical field of information recommendation, in particular to a recipe recommendation method based on multi-modal anti-fact learning, which comprises the following steps: constructing a heterogeneous graph; using a graph neural network to obtain network fusion embedding characteristics of each user node as target embedding characteristics of each user node, and network fusion embedding characteristics of each recipe node in each mode; based on network fusion embedding characteristics of each recipe node in each mode, a multi-mode characteristic decoupling module is utilized to obtain mode sharing embedding characteristics, mode specific embedding characteristics and mode fusion embedding characteristics of each recipe node, and then an anti-fact learning network is utilized to obtain final anti-fact embedding characteristics of each recipe node; fusing the modal sharing embedding feature, the modal specific embedding feature and the final anti-fact embedding feature of each recipe node as the target embedding feature of each recipe node; and inputting the target embedded features of each user node and each recipe node into a prediction module, and outputting a prediction score between each user and each recipe. The recipe recommendation precision is improved.

The invention relates to the technical field of cocktails, discloses a cocktail formula retrieval enhanced generation method based on multi-modal feature fusion, and aims to solve the problems of poor accuracy and low individuation degree of an existing method. The scheme mainly comprises the steps that a cocktail finished product image and an ingredient constraint condition text uploaded by a user side are acquired; visual feature extraction and semantic feature extraction are carried out, fusion coding is carried out, and a unified query vector is generated; searching candidate formulas with similarity scores Top-K from a pre-constructed cocktail formula knowledge base; and inputting the query vector and the candidate formula into a retrieval enhanced generation model, generating a cocktail formula recommendation result including a formula name, main ingredients, alternative ingredient suggestions, making steps, formula difficulty and estimated making time, and returning the cocktail formula recommendation result to a user side for display. According to the method, the accuracy and the individuation degree of cocktail formula retrieval are improved, and the method is suitable for intelligent bartending, catering training and personal customization service scenes.

In one implementation, a device receives an input request for a large language model-based network troubleshooting agent regarding an issue in a network. The large language model-based network troubleshooting agent performs a lookup of a recipe based on the input request, wherein the recipe comprises contextual information for the issue. The device generates, by the large language model-based network troubleshooting agent, a prompt for a large language model based on the input request and on the recipe. The device provides, by the large language model-based network troubleshooting agent, the prompt to the large language model to troubleshoot the issue in the network.

To make an electronic device take an appropriate action in response to an action of a user.SOLUTION: An action control system disclosed herein comprises an input unit for receiving user input including information on date of birth and an area of residence of a particular infant, a processing unit for performing specific processing using a sentence generation model for generating a sentence according to an input sentence, and an output unit configured to control an action of an electronic device to output a result of the specific processing, where the specific processing comprises suggesting meal recipes for the infant. The processing unit determines whether a predetermined trigger condition is met or not and, when affirmative, suggests meal recipes for the infant using an output of the sentence generation model that uses information obtained from the user input as the input sentence.SELECTED DRAWING: Figure 2

In one implementation, a device receives an input request for a large language model-based network troubleshooting agent regarding an issue in a network. The large language model-based network troubleshooting agent performs a lookup of a recipe based on the input request, wherein the recipe comprises contextual information for the issue. The device generates, by the large language model-based network troubleshooting agent, a prompt for a large language model based on the input request and on the recipe. The device provides, by the large language model-based network troubleshooting agent, the prompt to the large language model to troubleshoot the issue in the network.

This disclosure relates to using machine learning, more specifically a trained generative adversarial network (GAN) for developing a flavour blend for a food product, such as chewing gum or other confectionary. The method comprises receiving, by one or more processors, a target profile for a food flavour, such as chewing gum and flavour data; predicting, by the one or more processors, one or more flavour blends based on the flavour data and the target profile; comparing, by the one or more processors, the one or more flavour blends to the target profile to identify at least one best flavour blend; and displaying, by the one or more processors, the at least one best flavour blend on at least one user interface of at least one user device.

A method for providing recipes for cooking to a user of a cooking device includes providing a trained recipe generator and / or training a recipe generator, receiving a trigger, especially a request, a query or a prompt, from the user of the cooking device, generating, based on the trigger, a new recipe using the recipe generator, and providing the new recipe to the user. A related data processing program product, a control unit of the cooking device, a related central entity and a system, are also provided.

The invention provides a personalized precise nutrition recipe recommendation method and system based on a genetic algorithm, and the method comprises the steps: inputting various personal information, including gender, age, weight, height, and nutrition risk information (lack of nutrients, risk genes or risk SNP ID), all the personal information being dynamically linked together, and quantitative nutrient demands are generated for specific individuals according to the resident dietary nutrient reference intake and a pre-constructed nutrient-gene interaction database. A food nutrient composition database is pre-constructed on the system and comprises various foods from four different countries and nutritional ingredients of the foods. And then, according to individual quantitative nutrient requirements, selecting and combining food by writing a genetic algorithm, iteratively perfecting the combination of food types and food amounts, and finally outputting an accurate nutrition recipe meeting individual nutrition requirements.

To provide a cooking system which can handle controlling of a kitchen ventilation device in automatic cooking, and to provide the kitchen ventilation device, a heating cooker, and a control method of the cooking system.SOLUTION: A cooking system 400 has a kitchen ventilation device 100, an acquisition unit 510, and a control unit 130. The acquisition unit 510 acquires cooking data including recipe information including cooking procedure and operation contents of the kitchen ventilation device 100 appropriate to the recipe information and used to perform processing selected according to the recipe information. The control unit 130 controls the kitchen ventilation device 100 based on the cooking data so as to perform the processing selected according to each recipe information.SELECTED DRAWING: Figure 5

The invention discloses a nutrition recipe intelligent generation system and method, and belongs to the technical field of nutrition information processing and intelligent recommendation. The system is suitable for individual nutrition management of individuals of all ages, and particularly, optimization design is carried out for infant stages of 0-72 months. The system intelligently generates a personalized nutrition recipe based on individual basic information, growth indexes, nutrition standards, available food materials, user preferences and feedback and other multi-dimensional data, and supports nutrition intake evaluation and dynamic optimization. The system comprises core modules of data input, nutritional requirement calculation, recipe generation, nutrition analysis and interactive display and the like, and expands and supports functions of sensitization screening, regional and seasonal adaptation, work and rest linkage, family sharing and the like. Through fusion of individual growth data and environmental conditions, the system realizes scientific and high-adaptability nutrition recommendation, improves feeding convenience and intervention accuracy, and has a wide application prospect.

The invention discloses a nutrition improvement nursing method for a gastrointestinal digestion patient, and relates to the field of medical monitoring, and the method comprises the following steps: analyzing to obtain the current absorption amount of to-be-supplemented nutrient elements of the gastrointestinal digestion patient; analyzing to obtain a health influence coefficient of the to-be-supplemented nutrient elements on the gastrointestinal digestion patient; acquiring an absorption promotion coefficient between the to-be-supplemented nutrient elements and other to-be-supplemented nutrient elements; forming a to-be-updated recipe of the current recipe; calculating a health contribution value of the to-be-updated recipe to the gastrointestinal digestion patient; and calculating the coincidence proportion of the to-be-updated recipe relative to the current recipe, and performing recipe change on the current recipe. According to the method, the health influence coefficient is obtained through analysis, the absorption promotion coefficient is obtained, the to-be-updated recipe is formed, the corresponding health influence is obtained according to the deficiency of different to-be-supplemented nutrient elements, and the mutual influence condition existing between the different to-be-supplemented nutrient elements is also considered, so that the prediction result of nutrient absorption is closer to the reality.

There is provided a cooking robot, a cooking robot control device, and a control method that enable a cooking robot to customize a dish prepared according to a preference of an eater. The cooking robot (1) according to one aspect of the present technology controls a cooking operation performed by a cooking arm (321), using recipe data including a data set in which cooking operation data and cook biological data are linked, the cooking operation data describing information regarding an ingredient of a dish and information regarding an operation of a cook in a cooking process using the ingredient, and the cook biological data indicating a biological reaction of the cook measured in conjunction with a progress of the cooking process. The present technology can be applied to a cooking robot that operates an arm to cook.

The invention discloses a health data analysis and nutrition recipe generation method based on an enhanced large model, and the method comprises the steps: constructing an enhanced large language model, and obtaining an optimal autoregression language model according to an optimized multi-source heterogeneous data set; constructing a medical nutrition knowledge graph to fuse the structured data and the unstructured data of the medical nutrition to obtain an optimized medical nutrition knowledge graph; according to the optimized multi-source heterogeneous data set, constructing a user health portrait used for obtaining multi-dimensional health features of the user; and constructing a user health state time sequence prediction model to obtain user health state data, and obtaining a personalized nutrition recipe in combination with the optimized medical nutrition knowledge graph. The problems that in a traditional method, a data source of health data analysis is single, integration of multi-source heterogeneous data is lacked, the health condition of an individual is difficult to comprehensively reflect, knowledge coverage of the generated recommended recipe is incomplete, the illusion phenomenon is likely to be generated, and the generated recipe is insufficient in pertinence and scientificity are solved.

The invention relates to the field of catering management, in particular to a healthy diet-based catering management method, which comprises the following steps of: acquiring and integrating user information, acquiring user diet basic information, distributing a monitoring period and continuously observing the dynamic change of the user diet basic information to provide a basis for subsequently generating a diet scheme; by generating the initial recipe, processing to obtain the personalized recipe and optimizing the recipe recommendation strategy, the diet plan is ensured to be closer to the actual demand of the user, and the user experience is improved; according to the optimized recipe recommendation strategy, an intelligent diet scheme is evaluated, accurate tracking of food materials and intelligent dish matching are carried out, and the accuracy and controllability of cooking are improved; the financial information of the restaurant is analyzed, the cost control is optimized, the operation cost of the restaurant is reduced, the profitability is improved, and a powerful guarantee is provided for sustainable development of the restaurant. The method is used for solving the technical problem that the current catering management efficiency is not high.

Embodiments relate to a system and method to plan preparation of a meal that may include more than one dish. Online recipes are obtained from a database based on criteria set by the user. Recipes are analyzed for time and effort requirements at each step. If a meal includes more than one dish, a merge of the timelines is performed to determine if it is feasible to prepare all dishes concurrently. Suppliers that can supply all ingredients required by the recipes that meet all user criteria are recommended to the user.

A system performs either inference using a first model or inference using a second model and a third model according to accuracy of at least one model of the first to third models and, upon the inference, generates or updates recipe properties data that is data indicating an association between a manufacturing method recipe for a material and a material property / properties. The first model is a model to which a manufacturing method recipe dataset indicating a manufacturing method recipe is input and from which a material properties dataset indicating a material property / properties is output. The second model is a model to which a material characteristics dataset indicating a material characteristic(s) is input and from which a material properties dataset is output. The third model is a model to which a manufacturing method recipe dataset is input and from which a material characteristics dataset is output.

The invention relates to the technical field of automatic pattern generation and execution, and provides a beverage garland track generation method based on a specific pattern, which can be widely applied to the fields of beverage garland, food decoration, artistic creation and the like, and comprises the following steps: S1, receiving pattern input; s2, analyzing the pattern input to obtain control parameters; s3, generating an execution path based on the control parameters; and S4, generating a control track according to the execution path and executing the control track. Through the basic geometric primitive combination, the pattern formula system and the user input conversion pipeline, the preset garland pattern and user-defined input are adapted, accurate and stable reproduction and flexible expansion of the garland pattern are realized, and the personalized creation capability of the automatic coffee machine is improved. The system is compatible with multiple types of executing mechanisms such as 4-7-axis mechanical arms, breaks through traditional input limitation, supports multi-mode interaction such as natural languages and gestures, can autonomously learn and evolve, constructs open creative ecology, and has four innovation points.

Embodiments relate to utilizing an optical character recognition extraction and a large language model (LLM) to automatically populate a shopping cart of a user of an online system with items from a physical recipe. The online system receives an image capturing the physical recipe and extracts a raw text from the received image. The online system generates a prompt for input into the LLM, the prompt including a task request for the LLM to generate a list of ingredients using the raw text. The online system inputs the prompt into the LLM to generate the list of ingredients. The online system maps the list of ingredients to a list of items available by one or more retailers associated with the online system. The online system causes a device of the user to display a user interface with the list of items.

A recipe acquisition unit acquires a plurality of cooking steps. An operation block processing unit associates one or more blocks to each of the plurality of cooking steps. A situation acquisition unit acquires information on a situation of a user. A cooking block selection processing unit selects, in each of the plurality of cooking steps, a block suited to the situation of the user from the one or more blocks. A cooking program creation processing unit creates a cooking program suited to the situation of the user by combining the block selected in each of the plurality of cooking steps. An output unit outputs the cooking program created.

Provided in the present application are a process recipe synchronization method and apparatus, and a semiconductor process device. The process recipe synchronization method comprises: using a multi-thread asynchronous task processing method, determining a target process recipe, which is not stored in a recipe database, in a target process device, and synchronizing the target process recipe to the recipe database. Compared with the usage of a single thread to process a process recipe synchronization task, in the present application, a plurality of threads are independent of each other and simultaneously process a process recipe synchronization task, such that the duration required for process recipe synchronization can be greatly shortened, and the waiting duration of a user is reduced.