Collaboration Network Search Tree Optimization
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Solution Overview
Problem
Conventional social and professional networking sites fail to effectively connect individuals for new opportunities due to limitations in identifying relevant collaborations and relationships.
Innovation Solution
Systems and methods that utilize collaboration data to perform a breadth search within a search tree, optimizing the search process to locate the shortest path between nodes, allowing users to find collaborations and opportunities by leveraging existing connections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional networking sites store and display user profile information and connections, then users can maintain social relations, but the sites fail to effectively connect appropriate individuals for new opportunities
Solution Approach 1:
The patent segments the network data into hierarchical levels (Level 0: source node, Level 1: direct connections, Level 2: connections of connections, etc.) and processes each level separately using breadth-first search. This segmentation allows the system to efficiently identify collaborations at different degrees of separation without overwhelming complexity, resolving the contradiction by making the search process manageable while improving connection effectiveness.
Solution Approach 2:
The patent performs preliminary actions by pre-processing and storing collaboration data in an optimized format before searches are conducted. The system pre-calculates and stores network paths, connection degrees, and collaboration metrics, which enables rapid identification of relevant opportunities without complex real-time computation, thus improving productivity while controlling complexity.
2Reliability
If the network search includes all possible connections and paths, then complete collaboration data is found, but the search process becomes inefficient and time-consuming
Solution Approach 1:
The patent applies partial action by limiting the search to a specified number of levels (e.g., 2nd degree connections) rather than exhaustively searching the entire network. This allows the system to find the most relevant collaborations (those within acceptable distance) without the excessive time cost of searching all possible paths, maintaining reliability for practical purposes while reducing search time significantly.
Solution Approach 2:
The patent uses breadth-first search to systematically skip through levels of the network hierarchy, rapidly moving from Level 0 to Level 1 to Level 2 connections. This methodical skipping through the network layers allows complete data collection within each level while avoiding the time waste of exploring irrelevant deeper connections, balancing completeness with efficiency.
3Measurement precision
If the system processes and analyzes all collaboration data in real-time, then accurate connections are identified, but the system becomes slow and unresponsive
Solution Approach 1:
The patent performs preliminary processing of collaboration data by pre-calculating network paths, connection degrees, and collaboration metrics during off-peak times or during data updates. This pre-processing stores optimized search structures that enable rapid, accurate connection identification during user queries, maintaining measurement precision while dramatically improving response speed.
Solution Approach 2:
The system uses self-service by automatically maintaining and updating the collaboration data structures as new connections are made or data is added. The breadth-first search algorithm automatically traverses and updates the network hierarchy without requiring manual intervention, ensuring accurate connection identification while keeping the processing overhead minimal and responsive.
Data Source
AI summary
Various embodiments enable finding collaborations in a network. One embodiment obtains collaboration data for a plurality of nodes, receives a request to locate at least one collaboration for a user, generates a search tree starting by determining a source node of the collaboration data, the search tree including at least two levels, and expanding the search tree until at least one target node is located that corresponds to a solution for the request, optimizes the search tree to attempt to reduce the number of solutions, generates an adjacency list of adjacent nodes in the optimized search tree, searches the adjacency list to locate at least one shortest path to the target node, and generates a list of collaboration data that is associated with the at least one shortest path from the source node to the target node.