Location-Based Dining Recommendation Labels in Reduced Interface Areas
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Solution Overview
Problem
Users face inefficiency when browsing and ordering food items from dining applications due to the time-consuming process of deciding between multiple options from various venues, lacking personalized and location-based recommendations.
Innovation Solution
A system that aggregates dining preference labels from nearby users based on historical data, allowing users to receive personalized recommendations for food items and venues within their proximity, facilitating efficient browsing and ordering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users browse through multiple food items from multiple dining venues to decide what to order, then users can find suitable food options, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing dining preference labels for multiple users based on their historical ordering data before a user needs to make a decision. When a user queries for recommendations, the system retrieves pre-computed labels and generates recommendations instantly without requiring real-time analysis of user history, thus reducing decision-making time while maintaining personalized food selection capability
Solution Approach 2:
The patent introduces dining preference labels as an intermediary element that mediates between user historical data and food recommendations. These labels serve as compressed representations of user preferences that can be quickly retrieved and matched with available food items, eliminating the need for users to manually browse through multiple options and enabling efficient recommendation generation
2Adaptability or versatility
If the system provides detailed dining recommendations with multiple options, then users have more choices, but the interface complexity increases
Solution Approach 1:
The system segments the recommendation interface into distinct functional areas: a first display area dedicated to showing dining preference labels and a second display area for showing detailed food item information. This segmentation allows the interface to provide comprehensive recommendations while maintaining clarity by separating the recommendation selection function from the detailed information display function, thus managing interface complexity effectively
3Loss of information
If the system displays comprehensive food item information, then users can make informed decisions, but the interface becomes cluttered and harder to navigate
Solution Approach 1:
The interface is segmented into a first display area for dining preference labels and a second display area for detailed food information. Users can view comprehensive food information in the second area without it cluttering the recommendation selection area (first area), maintaining both information completeness and ease of operation by spatially separating different types of information presentation
Solution Approach 2:
The system transitions from a single-dimension linear layout to a multi-dimensional spatial layout by utilizing separate display areas (dimensions) for different types of information. This allows comprehensive food information to be displayed without interfering with the recommendation interface, as they occupy different spatial dimensions on the screen
Data Source
AI summary
One embodiment provides a system that facilitates efficient use of a dining application by providing dining recommendations to a user. During operation, a server determines a plurality of labels associated with a plurality of users, where a label indicates dining preference information of a user, and where the dining preference information is based on historical information for the user. The server receives a request from a first user to determine dining preference information of nearby users. The server determines a location for the first user, identifies one or more second users located within a predetermined distance from the first user, and aggregates the labels associated with the second users. Subsequently, the server returns the aggregated labels to the first user.


