Group Division Method Using Social Relationships and Selfish Preferences
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Solution Overview
Problem
Conventional group division methods neglect the influence of social relationships and selfish behavior, leading to unsatisfactory recommendation results, especially when extreme users are present, as they focus primarily on shared interests without considering the impact of users' social connections and individual preferences.
Innovation Solution
A group division method that combines social relationship analysis with a selfish preference order, where users are simulated to form groups based on shared costs and social values, and rules are established to combine or split groups until a Nash equilibrium is reached, ensuring stable divisions and maximizing user satisfaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional group division methods focus only on shared interest preferences, then the division process is simple, but the recommendation results are unsatisfactory when extreme users are present
Solution Approach 1:
The patent segments the group division process into two distinct phases: preliminary group formation based on social relationships, and stable group formation through combining/splitting operations based on selfish preferences. This segmentation allows each phase to address specific aspects of the problem independently, improving recommendation quality while managing complexity through structured decomposition
Solution Approach 2:
The patent performs preliminary group formation based on social relationships before conducting the stable group formation process. This preliminary action establishes an initial grouping structure that considers social connections, which then serves as the foundation for subsequent optimization through combining and splitting operations, ensuring both social awareness and preference alignment
2Ease of operation
If group division considers social relationships and selfish preferences, then user satisfaction improves, but the calculation complexity increases
Solution Approach 1:
The patent introduces dynamic combining and splitting rules that allow groups to evolve based on users' selfish preferences. The system dynamically adjusts group compositions through iterative operations where users can leave or join groups, and groups can merge or split, until reaching a stable state. This dynamic approach enhances user satisfaction by accommodating individual preferences while managing complexity through defined transition rules
Solution Approach 2:
The patent implements feedback mechanisms where users evaluate their satisfaction with current group assignments and adjust their preferences accordingly. The system continuously monitors whether users want to leave current groups or join others, and whether groups should merge or split, using this feedback to iteratively improve group divisions until stability is achieved, thereby enhancing user satisfaction through responsive optimization
3Adaptability or versatility
If extreme users are present in groups, then group diversity increases, but recommendation satisfaction deteriorates
Solution Approach 1:
The patent extracts extreme users from groups through the combining and splitting operations. When a user's selfish preferences indicate strong dissatisfaction with their current group (representing extreme views), the system allows that user to leave the group or form a separate group. This extraction process removes extreme elements that would otherwise deteriorate overall recommendation satisfaction while preserving group diversity through legitimate preference-based separations
Data Source
AI summary
A group division method based on a social relationship in combination with a selfish preference order is provided, the method includes the following steps: step 1, forming a preliminary group by simulating choices of users to gather into groups for sharing cost based on social values of the users; and step 2, drawing up combining and splitting rules according to a selfish preference order, subjecting the groups obtained in step 1 to combining or splitting on a basis of the combining and splitting rules, and ending the combining or splitting upon reaching a Nash equilibrium point, thereby obtaining stable groups. In the scenario of a static game with complete information, a Nash equilibrium point is found out based on the combination of a social relationship and a selfish preference order, so that the stability of group division is improved, and extreme users are removed.