Mobile Forensic Record Data Visualization
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Solution Overview
Problem
Conventional mobile forensic tools lack the ability to effectively visualize and present call and SMS record data in a meaningful way, making it difficult for users to identify frequent contacts and understand relationships between individuals.
Innovation Solution
A method and apparatus that calculate event occurrence frequency for call and SMS services, classify partner information based on this frequency, and generate graphic data to display relationships between user and partner information, allowing for the visualization of frequent interactions and common relations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If call record data and SMS use record data are arranged in occurrence order and displayed in text form, then the data can be displayed simply, but the user cannot efficiently identify frequent contacts or understand relationships between individuals
Solution Approach 1:
The patent transforms the flat, linear text display of call records into a multi-dimensional radial graph where contacts are positioned in spatial relationships around the user. This dimensional transformation allows users to visually perceive frequent contacts through their proximity to the user center and relationship strength through connection line thickness, solving the problem of identifying frequent contacts without requiring complex search operations.
Solution Approach 2:
The patent employs color coding in the radial graph to represent different relationship types or communication frequencies between users and contacts. By assigning distinct colors to different relationship categories, the system enables users to quickly identify and differentiate between various types of contacts without requiring detailed text analysis, thus improving ease of operation.
2Productivity
If conventional mobile forensic tools simply arrange record data in text form, then the implementation remains simple, but the tool cannot deliver information to users more efficiently
Solution Approach 1:
The patent performs preliminary analysis of call record data and SMS use record data to calculate relationship strength and frequency metrics before generating the radial graph. By pre-processing the data to identify frequent contacts and relationship patterns, the system can efficiently deliver meaningful information through the visual representation, avoiding the need for users to manually analyze raw text data.
Solution Approach 2:
The patent introduces an intermediary data processing layer that transforms raw communication records into structured relationship data. This intermediary layer calculates event occurrence frequencies, determines relationship strengths, and organizes contact information before passing it to the visualization component, thereby enabling efficient information delivery while managing complexity through modular architecture.
3Loss of information
If the system calculates event occurrence frequency and generates graphic data showing relationships, then the user can easily identify frequent contacts, but the data processing and visualization complexity increases
Solution Approach 1:
The patent extracts key relationship information from comprehensive communication records by calculating event occurrence frequencies and relationship strengths. Instead of processing and displaying all raw data, the system extracts only the essential relationship metrics and visualizes them in the radial graph, thereby preserving important relationship information while managing processing complexity through selective data extraction.
Data Source
AI summary
A method for visualizing record data with a mobile forensic device for collecting and managing the record data including partner information when an event, such as a call or text service, occurs, includes: calculating an event occurrence frequency for each partner information using the collected record data; and classifying the partner information on the basis of a grade according to the calculated event occurrence frequency. Further, the method includes generating graphic data showing a relation between the partner information and user information of a mobile terminal on the basis of the classified grade; and displaying the graphic data.