Group Preference Aggregation for Collaborative Item Selection
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Solution Overview
Problem
Existing preference list and recommendation services fail to consider user associations, such as shared shipping addresses or frequent item sharing, limiting their functionality.
Innovation Solution
Implementing computer services that utilize group preferences to identify suitable items for groups of users, allowing users to associate their preference lists, and providing features for item sharing and collective recommendations based on individual user histories and ratings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If individual user preference lists are used for recommendations, then personalization accuracy is improved, but the system fails to capture group dynamics and shared interests
Solution Approach 1:
The patent merges individual user preference lists into a unified group preference structure. The system combines preference data from multiple users while preserving individual user IDs to track personalization, creating a hybrid representation that captures both individual and group preferences simultaneously.
Solution Approach 2:
The preference list structure is designed to serve multiple functions: it maintains individual user preferences for personalization, aggregates group preferences for shared recommendations, and supports both rental and purchase decision-making processes through a single unified data structure.
2Ease of manufacture
If rental queues automatically remove top items for delivery, then rental fulfillment is simplified, but the system cannot accommodate shared viewing preferences
Solution Approach 1:
The rental queue system is made dynamic by allowing real-time modifications based on group preferences. When items are added to or removed from preference lists, the system automatically updates rental queue priorities and delivery schedules, enabling the static fulfillment process to adapt to changing group viewing interests.
Solution Approach 2:
The system incorporates feedback loops where rental history and viewing behavior data feed back into preference list calculations. This feedback mechanism allows the system to learn from actual group viewing patterns and adjust future rental recommendations to better match shared preferences.
3Device complexity
If recommendation services use only individual user data, then data processing is simpler, but the system misses opportunities for collaborative filtering
Solution Approach 1:
The patent segments the recommendation system into distinct processing modules: individual preference extraction, group preference aggregation, and collaborative filtering. This segmentation allows the system to handle complex collaborative filtering by breaking it down into manageable processing stages that can be executed efficiently.
Solution Approach 2:
The system performs preliminary processing by pre-aggregating preference data and pre-calculating group statistics before generating final recommendations. This preliminary action reduces the computational burden during real-time recommendation generation, making complex collaborative filtering feasible without excessive processing delays.
Data Source
AI summary
Computer services use group preferences, as partially or wholly specified by preference lists of individual members, to identify items well suited for a designated group of users. In one embodiment, items in the movie/video rental queue (one type of preference list) of a first user are prioritized based, at least partly, on the rental queue of a second, affiliated user, to give priority to items corresponding to the collective preferences of both users. Items may also be recommended to the users based on their collective preferences. In a second embodiment, the suggestion lists of multiple members of a book club are used, optionally in combination with other member preference information, to select or recommend book titles for the club. In a third embodiment, the wish lists of two or more affiliated users are used to assist others in purchasing gifts that correspond to their collective preferences.