Cooking device-based recipe pushing method and apparatus
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Solution Overview
Problem
Users face inconvenience due to a lack of knowledge about cooking devices and mismatched recipes, leading to suboptimal use of cooking devices and unsatisfied personal preferences.
Innovation Solution
A cooking device-based recipe pushing method that receives product information, extracts user preferences, and generates recommendations matching both the device capabilities and personal preferences, enhancing user experience by optimizing recipe suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users select recipes from diverse information sources, then recipe variety increases, but recipe-device compatibility decreases
Solution Approach 1:
The system collects user browsing behavior data (dwell time, click patterns) as feedback signals, processes this information through the server, and generates personalized recipe recommendations that are compatible with the cooking device. This closed-loop feedback mechanism enables the system to continuously improve recommendation accuracy while ensuring device compatibility.
Solution Approach 2:
The system changes the parameters of recipe selection by transitioning from generic recipe databases to personalized recommendation parameters based on user behavior analysis. The server processes browsing data to generate customized recipe parameters that match both user preferences and cooking device capabilities, resolving the contradiction between variety and compatibility.
2Adaptability or versatility
If cooking devices offer diverse functions, then device capability increases, but user understanding decreases
Solution Approach 1:
The system enables self-service by automatically analyzing user browsing behavior and generating personalized recipe recommendations without requiring users to manually search or understand complex device functions. The cooking device autonomously processes user interaction data and provides tailored recommendations, making diverse device capabilities accessible to users regardless of their technical knowledge.
Solution Approach 2:
The server acts as an intermediary between the cooking device and the user, translating complex device capabilities into simple, personalized recipe recommendations. By processing user behavior data and matching it with device functions, the intermediary simplifies the interaction interface while preserving full device functionality.
3Adaptability or versatility
If personalized recommendations are generated, then user preference matching increases, but data processing complexity increases
Solution Approach 1:
The system segments the data processing task by separating data collection (performed by the cooking device on the user terminal), data transmission (via network), and data analysis (performed by the server). This segmentation allows the cooking device to remain relatively simple while the server handles the complex processing of browsing behavior data to generate personalized recommendations.
Data Source
AI summary
A recipe pushing method includes receiving cooking device product information of a cooking device transmitted by a terminal device via a cooking service application, extracting a recipe preference characteristic of a user according to a history of the user browsing recipes in the cooking service application and a preset filtering condition, generating a recommended recipe matching the cooking device product information according to the recipe preference characteristic, and transmitting the recommended recipe to the cooking service application.