IoannaDi05/resume-score-details

该数据集包含**1,031个样本**，由**GPT-4o**生成和评估的简历与职位描述（JD）。主要目标是评估简历与职位描述的对齐情况，帮助研究简历相关性、技能对齐和基于预定义标准的职位匹配评分。数据集包括与职位描述匹配的简历，评估和评分细节基于各种匹配标准：**201个不匹配的JSON**（简历与提供的JD不相关）、**648个匹配的JSON**（简历与JD相关且对齐）、**142个无效的JSON**（简历或JD不完整或无效）、**40个缺少附加信息的JSON**（附加输入信息被省略的情况）。每个样本JSON文件包含输入（职位描述文本、宏观和微观标准及其权重、附加信息、最低要求、简历文本）和输出（评分理由、宏观和微观分数、要求满足情况、汇总分数、个人信息、简历和JD有效性）以及详细信息（简历分析，包括教育、认证、技能、项目历史和专业经验）。数据集支持AI驱动招聘、职位匹配算法和自然语言处理（NLP）的研究。

This dataset contains **1,031 samples** of resumes and job descriptions (JDs) generated and assessed using **GPT-4o**. The primary goal of this dataset is to evaluate the alignment between resumes and job descriptions, aiding in the study of resume relevance, skill alignment, and job fit scoring based on predefined criteria. The dataset includes resumes matched with job descriptions, with the assessment and scoring details based on various matching criteria: **201 Mismatched JSONs** (resumes not relevant to the provided JD), **648 Matched JSONs** (resumes relevant and aligned with the JD), **142 Invalid JSONs** (cases where either the resume or JD is incomplete or invalid), and **40 JSONs Missing Additional Info** (instances where additional input information was omitted). Each sample JSON file includes input (job description text, macro and micro criteria with their weighting, additional info, minimum requirements, resume text) and output (justification for scores, macro and micro scores, requirements met indicators, aggregated scores, personal info, resume and JD validity) as well as details (resume analysis, including education, certifications, skills, project history, and professional experience). The dataset supports research in AI-driven recruitment, job matching algorithms, and Natural Language Processing (NLP).