Large-Model Project Evaluation for Objective Delivery Assessment
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Solution Overview
Problem
Existing project evaluation methods rely heavily on manual data collection and human judgment, leading to inefficiencies and reduced reliability due to personnel experience and subjective biases, impacting the efficiency and controllability of project delivery.
Innovation Solution
A method utilizing a large model, specifically a large language model, to automate the project evaluation process by obtaining an evaluation intention, generating an initial evaluation result, and processing it to achieve a target evaluation result, minimizing human involvement and subjective factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data collection and human judgment are used for project evaluation, then the evaluation process can be performed with existing tools and methods, but the efficiency is reduced and reliability is compromised due to personnel experience and subjective biases
Solution Approach 1:
The patent replaces the manual mechanical evaluation process with an automated system using large language models. The system automatically collects project data, processes it through the large model to generate evaluation results, and outputs comprehensive assessments including project health, risks, and completion time estimates. This substitution eliminates human subjective biases and significantly improves both evaluation reliability and efficiency simultaneously.
2Reliability
If manual evaluation methods are used, then the system complexity remains low with simple processes, but the evaluation results are affected by personnel experience and subjective factors
Solution Approach 1:
The patent introduces a large language model as an intermediary between raw project data and evaluation results. This intermediary automatically processes project data, extracts relevant information, and generates objective evaluation outcomes. The system includes components for data collection, processing, and result generation that work together to eliminate human subjective influence while maintaining manageable system complexity through modular architecture.
3Measurement precision
If more manpower is allocated to project evaluation, then the evaluation thoroughness can be improved, but the manpower consumption and time cost increase
Solution Approach 1:
The patent implements a self-service evaluation system where the large language model automatically performs data collection, analysis, and evaluation generation without requiring manual intervention. The system autonomously processes project data, identifies key metrics, and produces comprehensive evaluation reports. This automation achieves high evaluation thoroughness equivalent to or exceeding manual review while dramatically reducing time cost and resource consumption.
Data Source
AI summary
Provided is a method apparatus for evaluating a project based on a large model, an electronic device, and a storage medium, relating to the field of computer technology, and in particular to fields of software and hardware project development, software and hardware project evaluation, machine learning, large model and other applications. The method includes: obtaining an evaluation intention for a target project; where the evaluation intention is used to request an evaluation of the target project under a specific evaluation indicator; obtaining an initial evaluation result for the target project under the specific evaluation indicator based on the evaluation intention using the large model; and obtaining a target evaluation result for the target project based on the initial evaluation result.