Conversational Semantic Support Systems for Development Automation
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Solution Overview
Problem
Traditional product and service development processes are inefficient due to the passive role of computer programs, which lead to time-consuming and resource-intensive communication, especially in large projects involving multiple teams, and result in 'lost in translation' issues.
Innovation Solution
The integration of conversational semantic support systems (CSSS) that collaborate with subject matter experts, utilizing semantic graphs and ontologies to understand natural-language descriptions and initiate subsequent steps, thereby reducing translation layers and enhancing the development and manufacturing process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional passive computer programs are used in development processes, then system simplicity is maintained, but productivity and development speed deteriorate due to time-consuming communication and multiple translation layers
Solution Approach 1:
The patent introduces a semantic processing system as an intermediary between natural language communication and formal program execution. This mediator translates conversational input into structured commands, eliminating multiple human translation layers and enabling direct program initiation based on semantic understanding of requirements.
Solution Approach 2:
The patent replaces manual, mechanical translation processes (human-to-human communication chains) with an automated semantic processing system that understands natural language and directly generates program actions, substituting the mechanical translation workflow with intelligent semantic interpretation.
2Reliability
If multiple translation layers are used in communication across teams, then information can be transmitted, but accuracy deteriorates due to 'lost in translation' issues
Solution Approach 1:
The semantic processing system serves as a unified intermediary that all teams communicate through, replacing multiple human-to-human translation layers. This single intelligent mediator maintains information accuracy by directly interpreting semantic meaning and generating precise program commands without sequential human translations.
Solution Approach 2:
The patent extracts the translation function from multiple human operators and consolidates it into a single automated semantic processing system, removing the problematic multiple translation layers while preserving the essential function of converting natural language into actionable commands.
3Productivity
If computer programs respond passively to search requests, then system simplicity is maintained, but productivity deteriorates due to inability to initiate next steps autonomously
Solution Approach 1:
The patent transforms computer programs from static, passive responders into dynamic, autonomous agents capable of semantic understanding. Programs now actively interpret natural language, determine next steps, and initiate actions autonomously, creating a dynamic workflow where systems adapt and progress without constant human direction.
Solution Approach 2:
The semantic processing system enables programs to serve themselves by autonomously understanding requirements, determining necessary actions, and executing next steps without human intervention. The system self-manages the workflow from interpretation to execution, reducing dependency on continuous human input.
Data Source
AI summary
The invention accelerates development and manufacturing by including conversational semantic support systems (CSSS) as active participants and partners of subject matter experts, (SME) in the process.CSSS receives an initial request from SME, provides a mapping from business goals to existing business tasks, scripted rules and scenarios, automatically moving to the next step of details, when available. The interesting things start when data is not available. At this point the system initiates a set of conversations with other CSSS available on the net. If data are not found, a program initiates a search over public and private data sources, over the Internet and available Data Clouds. The last resort is a conversation with a set of SME connected to the net. Retrieved and approved by SME data is registered while constantly increasing the knowledge of a system and its efficiency.