Search Results Weighted by Social Sharing Activity
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Solution Overview
Problem
Social networking sites face challenges in providing relevant search results due to the vastness of the internet, often resulting in search results that are of little interest to users.
Innovation Solution
A mechanism is introduced to weight search results based on active and passive sharing activity among users within a social network, where information recently shared is monitored and used to calculate relevance, ensuring that search results are more pertinent to the user's social context.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional search engines are used to search the vast internet, then the coverage of search results is comprehensive, but the relevance of search results to users decreases
Solution Approach 1:
The patent applies local quality by personalizing search results based on individual user profiles, social networks, and sharing activities. Instead of providing uniform search results for all users, the system tailors the relevance weighting to each user's specific context, making the search results locally optimized for each user while maintaining comprehensive coverage through the underlying search engine.
Solution Approach 2:
The system performs preliminary action by pre-collecting and analyzing sharing activities, social network structures, and user preferences before the search is executed. This pre-processing of social context data allows the search engine to quickly weight and rank results based on established relevance criteria, improving both coverage and relevance simultaneously.
2Productivity
If social networking features are added to enhance user engagement, then user interaction increases, but system complexity increases
Solution Approach 1:
The patent applies universality by designing a search system that serves multiple functions: traditional web search, social network analysis, sharing activity monitoring, and personalized result ranking. This multi-functional approach consolidates what could be separate complex systems into a unified search platform, enhancing user interaction while managing complexity through integration rather than multiplication of separate components.
Solution Approach 2:
The system implements self-service by automatically collecting sharing activities, analyzing social network structures, and dynamically weighting search results without requiring manual user configuration. The system serves itself by autonomously building and updating user profiles and relevance models, reducing the operational complexity while maintaining high user interaction through personalized results.
Data Source
AI summary
Embodiments of the present invention provide a mechanism for weighting search results based on active and passive sharing activity among users in the context of a social network. In particular, information being shared among users is monitored. When a search is requested by a user, information recently shared among a user's social network is consulted and is used to weight the search results in the relevance calculation. For example, sharing activity that occurred recently or ongoing is used to weight the search results.