Intelligent Memory Engine for Contextual Communication Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data analytics systems fail to efficiently analyze electronic communications, particularly in the absence of dictionary definitions, and do not provide for long-term analysis, contextual recommendations, or adequate navigation and linkages between conversation data, leading to data loss and storage issues.
Innovation Solution
A system and method utilizing an intelligent memory generation engine that extracts and processes electronic communications data, performs keyword tagging, generates a multi-relational model, and transmits Recommendation Action Communications with embedded API calls to provide contextual intelligent recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing systems store conversation data associated with electronic communications, then data is preserved for future use, but storage space is consumed and duplication occurs leading to wasted space and cumbersome search operations
Solution Approach 1:
The patent creates a centralized copy of conversation data in the data lake, allowing multiple users to access the same data without duplicating storage. Instead of each user having separate copies, a single centralized copy serves all users, eliminating storage waste while maintaining data accessibility and reliability.
Solution Approach 2:
The patent merges scattered conversation data from multiple storage locations into a single centralized data lake. This consolidation eliminates data duplication across different storage systems and provides a unified access point, reducing overall storage consumption while improving search efficiency and data reliability.
2Ease of operation
If existing systems link conversation threads with employees, then individual access is enabled, but data is lost or remains untapped when employees leave or are reassigned
Solution Approach 1:
The patent transitions from employee-specific data access to role-based universal access. Conversation data is tagged with organizational roles rather than individual employee identifiers, allowing any user with the appropriate role to access relevant conversation history. This ensures data continuity and prevents information loss when employees leave or are reassigned, while maintaining ease of access for authorized users.
Solution Approach 2:
The patent introduces role-based access control as an intermediary between employees and conversation data. Instead of direct employee-to-data linking, roles serve as the intermediary layer that determines access permissions. This decoupling ensures that conversation history remains accessible to the organization through role assignments, preventing data loss when individual employees change.
3Adaptability or versatility
If existing systems scatter data in various storage locations, then data is stored across different systems, but correlations between similar actionable intelligent data cannot be determined
Solution Approach 1:
The patent consolidates scattered data from various storage locations into a single centralized data lake, enabling comprehensive correlation analysis. By merging previously distributed data sources, the system can now identify relationships and patterns across the entire dataset, determining correlations between similar actionable intelligent data that were previously inaccessible due to data silos.
Solution Approach 2:
The patent implements a feedback mechanism where the system continuously analyzes consolidated data in the data lake, identifies correlations and patterns, and uses these insights to improve future data processing and analysis. This feedback loop enables the system to learn from data relationships and enhance its ability to determine correlations between actionable intelligent data over time.
Data Source
AI summary
A system and a method creating an intelligent memory and providing contextual intelligent recommendations is provided. The invention provides extracting electronic communications data associated with active user data. Further, the invention provides performing a keyword tagging operation on conversation data present in the extracted electronic communications data based on a pre-generated keywords map. The invention provides generating a multi-relational model representative of conversation data associated with the electronic communications data in the form of graph nodes based on the keywords stored as the first tag and the second tag. The invention provides transmitting one or more electronic Recommendation Action Communication (RAC) with embedded application program interface calls based on the multi-relational model, the embedded application program interface calls enabling actions to be taken on information units via a single click.