Intelligent Information Sharing System for Data and User Selection
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Solution Overview
Problem
Sharing information with other users through communication devices is often time-consuming and cumbersome, lacking efficient methods to identify and select relevant data items and users for sharing.
Innovation Solution
A system that analyzes data items and users based on criteria such as time windows and spatial regions to identify subsets for sharing, presenting them to users for modification and action, using metadata and social network analysis to determine co-proximity and generate lists of recipients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual selection of data items and users for sharing is performed, then user control and precision are improved, but time consumption and operational complexity increase
Solution Approach 1:
The system performs preliminary analysis of data items and users before the actual sharing action. It pre-processes metadata, establishes spatial-temporal relationships, and identifies potential sharing candidates in advance, so that when sharing is needed, the system can quickly present pre-filtered options rather than requiring manual evaluation of all possible items and users
Solution Approach 2:
The system enables self-service sharing by automatically analyzing user behavior patterns, spatial-temporal data, and social network relationships to generate recommended sharing lists. The system serves itself by autonomously identifying relevant data items and users based on established criteria, reducing the need for manual intervention while maintaining high selection accuracy
2Loss of information
If comprehensive analysis of all data items and users is performed, then sharing relevance is improved, but computational complexity and processing time increase
Solution Approach 1:
The system segments the comprehensive analysis into distinct modular components: metadata analysis module, spatial-temporal analysis module, social network analysis module, and candidate generation module. Each module handles a specific aspect of the analysis independently, processing data items and users through separate analytical pipelines that can be executed in parallel, thereby reducing overall computational complexity while maintaining comprehensive coverage
Solution Approach 2:
The system applies different analysis criteria and processing depths to different data items and users based on their local characteristics. Rather than applying uniform comprehensive analysis to all items and users, the system tailors the analysis intensity and criteria to each specific context, analyzing only the relevant attributes for each candidate based on the sharing scenario and user profile
3Ease of operation
If automatic identification of sharing candidates is implemented, then operational ease is improved, but automation extent and control precision may be compromised
Solution Approach 1:
The system implements feedback mechanisms where user selections, rejections, and modifications to automatically generated sharing lists are captured and used to refine future recommendations. The system learns from user feedback to adjust its analysis criteria, weighting, and candidate generation algorithms, progressively improving automation accuracy while maintaining user control through iterative refinement
Data Source
AI summary
Systems and techniques are described for facilitating sharing information. Some embodiments can receive a set of data items that is to be analyzed for sharing, analyze the set of data items based on a first set of criteria to obtain a subset of the set of data items that is a likely candidate for sharing, and present the subset of the set of data items to a first user. Additionally, some embodiments can receive a set of users that is to be analyzed for sharing information, analyze the set of users based on a second set of criteria to obtain a subset of the set of users with whom the information is likely to be shared, and present the subset of the set of users to the first user.