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Eon（Eon）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种无真实数据的企业级多系统业务数据生成器，通过参考统计和五轴记分卡等无参考评估验证真实性，并支持从业务问题构建关系数据库。
AI 中文摘要
合成关系数据通常由在真实数据集上训练的模型生成，其质量通过与该数据集的距离来衡量。本文描述了一个在两端都没有真实数据集的生成器。给定一个行业、公司规模、商业模式、一组业务应用和一个随机种子，它生成一个完整的虚构企业：员工队伍、客户群、销售交易、支持工单、录音电话、聊天消息和文档，所有这些都彼此一致。一个实体图被投影到66个业务产品的原生格式中，因此同一个客户以同一身份出现在CRM、支持台和电话系统中。由于不存在真实对应物，真实性基于引用的参考统计数据构建，并通过无参考测量进行验证：一个包含28项统计检查的五轴记分卡、一个寻找合成生成痕迹的对抗性检测器，以及一组健全性检查，其中包括对数据独立洗牌副本的分类器测试。由于这些工具在生成器调优之前就已存在，进展是在固定标尺下衡量的：在23家生成的公司中，平均真实性从60.3升至99.1，最弱公司从41.1升至94.9，而最初标记55.2%记录的检测器现在不标记任何记录。分数在开发中从未使用过的种子上保持稳定。第二个生成器从业务问题列表构建关系数据库。它为每个可回答的问题强制生成符合条件的行，添加受控的近似匹配，并从完成的表格中计算精确标签。该生成器作为托管服务在此https URL运行。按规格构建的公司通过其模拟器通过MCP和REST提供服务，模拟器也作为容器镜像发布以供离线使用。
英文摘要
Synthetic relational data is normally produced by a model trained on a real dataset, and its quality is measured as the distance to that dataset. This paper describes a generator that has no real dataset at either end. Given an industry, a company size, a business model, a set of business applications, and a random seed, it produces a complete fictional enterprise: a workforce, a customer base, sales deals, support tickets, recorded calls, chat messages, and documents, all consistent with one another. One entity graph is projected into the native formats of 66 business products, so the same customer appears in the CRM, the support desk, and the call system under one identity. Because no real counterpart exists, realism is built in from cited reference statistics and verified by reference-free measurement: a five-axis scorecard of 28 statistical checks, an adversarial detector that hunts for the marks of synthetic generation, and a set of soundness checks that include a classifier test against an independently shuffled copy of the data. Because these instruments existed before the generator was tuned, progress is measured under a fixed yardstick: over 23 generated companies, mean realism climbed from 60.3 to 99.1, the weakest company from 41.1 to 94.9, and the detector, which initially flagged 55.2% of all records, now flags none. The scores hold on a seed never used during development. A second generator builds relational databases from a list of business questions. It forces qualifying rows for each answerable question, adds controlled near misses, and computes exact labels from the finished tables. The generator runs as a hosted service at https://console.era.eon.io. A company built there to a specification is served through its simulators over MCP and REST, and the simulators are also published as container images for offline use
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