Travel Content Ranking by Geographic and User Context
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Solution Overview
Problem
Conventional travel systems fail to utilize relevant user information effectively, resulting in the display of less-relevant content and a sub-optimal user experience.
Innovation Solution
A travel system that identifies user context characteristics, scores and ranks content categories and objects based on these characteristics, and displays the most relevant content categories and objects to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional travel systems display content without utilizing relevant user information, then the system complexity is reduced, but the content relevance to users deteriorates
Solution Approach 1:
The system performs preliminary actions by collecting and storing user information (preferences, browsing history, demographic data) before content selection occurs. This pre-processing of user data enables the system to quickly retrieve and match relevant content without adding complexity to the real-time content delivery process
Solution Approach 2:
The system implements feedback mechanisms by analyzing user interactions with displayed content (clicks, views, bookings) and using this information to refine future content recommendations. This creates a closed-loop system where content relevance continuously improves based on actual user behavior patterns
2Loss of information
If the travel system scores and ranks multiple content categories based on user context characteristics, then the content relevance improves, but the processing time increases
Solution Approach 1:
The system pre-calculates and stores context characteristics (user preferences, location data, travel history) before they are needed for content selection. This preliminary preparation allows the scoring and ranking process to operate on pre-processed data, significantly reducing real-time processing requirements
Solution Approach 2:
The system applies different scoring weights and ranking criteria to different content categories based on their specific characteristics and the user's context. Rather than uniformly processing all content, the system tailors the evaluation process to each category's requirements, optimizing processing efficiency while maintaining relevance
Data Source
AI summary
A travel system generates and provides content recommendations to a user of the travel system. The travel system identifies content categories that are likely to be of interest to the user of the travel system based on context characteristics of the user such as whether the user is a traveler or a local at a particular geographic location. Additionally, the travel system further identifies content objects (e.g., attractions, activities, events, restaurants, businesses, and the like) for each identified content category that are likely to be of interest to the user based on characteristics of each content object. The identified content categories and content objects are provided as content recommendations for display to a user of the travel system, enabling a user to quickly navigate between content categories and content objects within each content category.