Node Profile State Change Detection for Event Record Automation
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Solution Overview
Problem
Managing large volumes of heterogeneous electronic communications in organizational systems of record is challenging due to the manual data input requirements, which is time-consuming and error-prone.
Innovation Solution
A method and system for detecting events based on updates to node profiles from electronic activities, involving parsing electronic activities to generate field-value pairs, maintaining node profiles with confidence scores, and identifying state changes to determine event conditions, thereby associating node profiles with event types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual data input is used to manage electronic communications, then data accuracy can be maintained through human verification, but time consumption and labor requirements increase significantly
Solution Approach 1:
The system enables automated self-service data extraction and validation from electronic communications. The processor automatically parses emails, calendars, and contacts to populate node profiles, eliminating the need for manual data entry while maintaining accuracy through systematic validation rules and confidence scoring mechanisms.
Solution Approach 2:
The patent replaces manual mechanical data entry processes with automated computational systems. The processor uses parsing algorithms and data extraction techniques to automatically transfer information from electronic communications to the system of record, substituting human labor with machine-based automation.
2Reliability
If manual data input is used for electronic communications, then data can be verified through human judgment, but error rates increase due to human fatigue and inconsistency
Solution Approach 1:
The system implements feedback mechanisms through confidence scoring, where each extracted data point receives a confidence score based on source reliability and data consistency. This automated feedback system continuously validates and verifies data accuracy without human intervention, reducing errors while maintaining high reliability standards.
Solution Approach 2:
The patent replaces human judgment and verification processes with automated computational validation. The system uses algorithms to consistently verify data accuracy across large volumes of electronic communications, eliminating human fatigue and inconsistency while maintaining or improving verification reliability.
3Loss of information
If comprehensive node profiles are maintained for all contacts, then data completeness improves, but system complexity and storage requirements increase
Solution Approach 1:
The system applies local quality by maintaining different levels of profile completeness based on individual contact importance and interaction frequency. Rather than uniformly complex profiles for all contacts, the system dynamically adjusts profile depth and detail based on local needs, reducing overall system complexity while preserving data completeness where necessary.
Solution Approach 2:
The patent implements dynamic node profiles that adapt their complexity based on usage patterns and data availability. Profiles evolve over time, adding or removing fields based on actual interaction needs, which reduces unnecessary complexity while ensuring data completeness is maintained for relevant information.
4Measurement precision
If real-time monitoring of node profile changes is implemented, then event detection accuracy improves, but processing overhead and computational resources increase
Solution Approach 1:
The system uses partial monitoring by focusing computational resources on detecting specific types of state changes that are most relevant to event detection. Rather than monitoring all possible profile changes equally, the system selectively monitors critical fields and uses confidence scoring to prioritize processing, reducing overhead while maintaining detection accuracy for important events.
Data Source
AI summary
The present disclosure relates to methods, systems, and storage media for detecting events based on updates to node profiles from electronic activities. Exemplary implementations may access an electronic activity transmitted or received via an electronic account associated with a data source provider; generate a plurality of activity field-value pairs; maintain a plurality of node profiles; identify a first state of a first node profile of the plurality of node profiles; update the first node profile using the electronic activity; identify a second state of the first node profile subsequent to updating the first node profile using the electronic activity; detect a state change of the first node profile based on the first state and the second state; determine that the state change satisfies an event condition; and store an association between the first node profile and an event type corresponding to the event condition.