Language Operator UI for Scalable Communication Summarization
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Solution Overview
Problem
The increasing volume of communications between entities and their representatives poses challenges in efficiently monitoring, triaging, and summarizing large volumes of data, requiring improved methods for analysis and navigation.
Innovation Solution
A system and method utilizing an enterprise intelligence platform (EIP) with customizable language operators, implemented via machine learning, to analyze and summarize communications, incorporating user feedback for model improvement, and optimized for various display sizes, including mobile devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual monitoring and analysis of communications is used, then accuracy of analysis can be maintained, but productivity and efficiency deteriorate due to increasing communication volumes
Solution Approach 1:
The patent replaces manual mechanical analysis of communications with automated machine learning models and natural language processing systems. These systems automatically monitor, triage, and summarize communications at scale, eliminating the time-consuming manual review process while maintaining or improving analysis accuracy through sophisticated algorithms.
Solution Approach 2:
The patent introduces an enterprise intelligence platform as an intermediary between communication data and human analysts. This platform uses language operators and machine learning models to pre-process, filter, and summarize communications before presenting them to users, thereby increasing productivity while reducing the time burden on human operators.
2Measurement precision
If comprehensive communication analysis is performed, then understanding of communication data quality improves, but device complexity and computational resources increase
Solution Approach 1:
The patent segments the communication analysis system into modular language operators with specific functions (e.g., sentiment analysis, topic detection, entity recognition). Each operator handles a specific aspect of communication analysis, making the overall system more manageable and less complex while achieving comprehensive analysis through composition of these specialized modules.
Solution Approach 2:
The patent creates a universal enterprise intelligence platform that handles multiple types of communications (emails, chats, calls) and multiple analysis objectives (quality assessment, triage, summarization) through a single multi-functional system. This reduces device complexity by consolidating what would otherwise require separate specialized systems.
3Loss of information
If detailed communication summaries are generated, then understanding of communication content improves, but loss of time for processing and presenting data increases
Solution Approach 1:
The patent performs preliminary analysis and summarization of communications automatically before they reach human reviewers. Language operators pre-process communications to extract key information, generate summaries, and identify important patterns, so that users receive pre-digested content rather than raw data requiring extensive review time.
Solution Approach 2:
The patent incorporates feedback mechanisms where user interactions with generated summaries are used to continuously improve the machine learning models. This feedback loop enables the system to learn from user preferences and behaviors, progressively improving summary quality and relevance while reducing the time users need to spend reviewing communications.
Data Source
AI summary
A method and system for automatically analyzing and/or summarizing communications using language operators, the method receiving a definition of a language operator, the definition comprising one or more phrases indicative of a match to a concept associated with a communication; surfacing, in a UI, one or more results of applying the language operator to the communication, the surfacing of each result of the one or more results using an interactive UI element linked to one or more communication phrases, the interactive UI element highlighting a match between the concept and the one or more communication phrases; and training a machine learned (ML) model to improve an accuracy of the result based on one or more inputs received via the UI.