Participant Inclusion via Textual Analysis and Hierarchical Distance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In organizations with dynamic membership and roles, determining the appropriate recipients for electronic communications can be challenging due to changes in positions and memberships, leading to misdirected or missed communications.
Innovation Solution
A system that generates a textual analysis of a draft communication to compute word relevance scores and probabilistically weighted distances within a hierarchical organization structure, automatically selecting recipient candidates based on these analyses to ensure timely and accurate message distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual recipient selection is used in dynamic organizational structures, then communication accuracy deteriorates due to position changes and membership changes, but automated recipient selection increases system complexity
Solution Approach 1:
The system automatically identifies and selects appropriate recipients based on organizational hierarchy data and message content analysis, eliminating the need for manual recipient selection by the user. The system serves itself by computing relevance scores and probabilistically weighted distances to determine optimal recipients.
Solution Approach 2:
The manual mechanical process of selecting recipients is replaced with an automated computational system that uses textual analysis, word relevance scoring, and hierarchical distance calculations to automatically determine recipient selection based on organizational structure and message content.
2Reliability
If comprehensive recipient analysis is performed to ensure accurate message distribution, then communication reliability improves, but processing time increases
Solution Approach 1:
The system pre-computes and stores organizational hierarchy structures and relationships before they are needed for message routing. By having this structural data readily available in advance, the system can quickly perform relevance scoring and distance calculations when a message needs to be sent, reducing actual processing time while maintaining comprehensive analysis.
Solution Approach 2:
Time-consuming manual analysis of organizational structures and message content is replaced with automated computational algorithms that rapidly calculate word relevance scores and probabilistically weighted distances, achieving comprehensive recipient analysis in fractions of a second.
Data Source
AI summary
Participant inclusion determination can include generating a textual analysis of a draft of an electronic communication in response to a sender preparing the draft for conveyance over an electronic communications network. A word relevance score can be computed for each word of the draft based on the textual analysis. Probabilistically weighted distances between the sender, an initial recipient of the electronic communication, and more additional recipient candidates for additionally receiving the electronic communication can be determined. The probabilistically weighted distances can correspond to hierarchical distances within a hierarchical structure corresponding to an organization in which the sender, the initial recipient, and one or more additional recipient candidates are members. At least one of the additional recipient candidates can be selected for receiving the electronic communication over the electronic communications network based on the word relevance scores and the probabilistically weighted distances.