Service Synthesis Graph Traversal for Budget and Time Constraints
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Solution Overview
Problem
The service industry faces challenges in efficiently synthesizing and evaluating services at scale due to the intangible nature of services, manual and time-consuming processes, and the difficulty in arriving at an optimal service experience within economic constraints.
Innovation Solution
A method and system for on-the-fly pattern-based synthesis and evaluation of services, utilizing a system with an input/output interface, hardware processors, and memory to create nodes and pattern languages, generate a meta-graph, and apply heuristic traversal and breadth-first search algorithms to produce novel services within budgetary and time constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual synthesis of service experience is performed by human experts, then service quality can be evaluated with domain knowledge, but the process is time-consuming, inconsistent, and not scalable
Solution Approach 1:
The patent replaces the manual mechanical process of human expert analysis with an automated computational system using natural language processing, machine learning models, and algorithms to synthesize and evaluate service experiences, achieving both speed and consistency
Solution Approach 2:
The system enables self-service evaluation by automatically processing service reviews and feedback without requiring human expert intervention, allowing the service experience synthesis to be performed autonomously at scale
2Reliability
If comprehensive service synthesis is performed manually to ensure quality, then evaluation accuracy can be maintained, but scalability is limited and consistency cannot be guaranteed
Solution Approach 1:
The patent substitutes human expert judgment with standardized computational algorithms and machine learning models that apply consistent evaluation criteria across all service experiences, ensuring reliability while enabling high-volume processing
Solution Approach 2:
The system creates a universal evaluation framework that can process diverse service experiences across multiple domains using the same standardized algorithms and metrics, achieving both consistency and scalability simultaneously
3Manufacturing precision
If optimal service experience is achieved through detailed manual analysis, then service quality can be maximized, but economic constraints and time limits cannot be met
Solution Approach 1:
The patent replaces complex manual service configuration and optimization processes with automated algorithms that can evaluate multiple service combinations and configurations rapidly, achieving optimization without proportional increases in process complexity
Solution Approach 2:
The system dynamically adjusts evaluation parameters and service configuration weights based on service type, consumer preferences, and contextual factors, enabling precise optimization through parameter tuning rather than complex procedural changes
Data Source
AI summary
A method and system that allows on-the-fly synthesis and evaluation of services a scale has been provided. The method and system provide a mechanism where the service offering and their price points are accessible in a machine format and allow themselves to be lent to synthesize new service offerings with budgetary constraints, within the parameters of the predefined time windows. The system allows both a service provider and a service consumer to use a shared screen environment for service synthesis and valuation with the service provider playing the role of navigator. The system comprises of re-routing and navigating a plurality of nodes in the service composition graphs based on specified optimization parameters as chosen by the service consumer and tuned by the service provider. The method comprises of generation of the graph and graph traversal algorithms for along with service composition nodes and their specifications.