Entity Connection Map Visualization via Spidering and Graphics Engines
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Solution Overview
Problem
Current tools for determining degrees of separation between entities are limited in their description and visualization, and none utilize connection metadata to graphically represent relationships between entities.
Innovation Solution
The technology generates connection maps and stories between entities by scraping web pages to extract user contacts and determining connection paths, using a spidering engine, connection engine, and graphics engine to create visual representations of topological and chronological relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated systems are used to determine connection maps between users, then information filtering efficiency is improved, but device complexity increases
Solution Approach 1:
The system is divided into distinct functional modules: a spidering engine for data collection, a connection engine for analysis, and a graphics engine for visualization. Each module performs a specific task in the information filtering process, improving overall efficiency while managing complexity through functional separation.
Solution Approach 2:
The connection engine acts as an intermediary between the spidering engine and the graphics engine. It processes raw connection data from the spidering engine, determines connection paths and stories, and prepares structured information for the graphics engine to visualize, thereby managing the complexity of data transformation.
2Loss of information
If connection metadata is utilized to graphically represent relationships, then information completeness is improved, but device complexity increases
Solution Approach 1:
The system transforms tabular connection metadata into graphical visual representations by adding a spatial dimension. Connection paths and stories are displayed as visual narratives with nodes and edges, allowing users to perceive relationship structures that would be difficult to understand in traditional tabular formats.
Solution Approach 2:
The graphics engine serves as an intermediary that translates structured connection metadata into visual formats. It receives connection paths and stories from the connection engine and renders them as graphical representations, preserving information completeness while presenting it in an accessible visual form.
3Ease of operation
If visual representations of connection paths are generated, then user experience is improved, but processing time increases
Solution Approach 1:
The spidering engine performs preliminary data collection by crawling web pages and extracting contact information in advance. Connection paths and stories are determined and stored in a database before visualization is requested, so that when the graphics engine needs to generate visual representations, the underlying data is already prepared and available.
Solution Approach 2:
The system replaces manual information filtering and connection analysis with automated computational processes. The connection engine automatically determines connection paths and stories using algorithms that analyze the database of extracted contact information, eliminating the need for manual analysis and reducing processing time.
Data Source
AI summary
The technology disclosed relates to identifying connection maps between entities (persons and organizations) and generating so-called connection stories between them based on the connection maps. The connection stories are graphic and visual representations of the connection paths that present to entities topological and chronological aspects of their relationships with other entities.