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非结构化商业文本信息中隐私信息识别-rank2

Shell 0.67% Python 99.33%

ccf-bdci2020-information-reg's Introduction

赛题介绍

赛题名:非结构化商业文本信息中隐私信息识别

背景:随着社交网络、移动通讯等技术的迅速发展,网络中存在大量包含隐私数据的文本信息,如何在非结构化的本文信息中精准识别隐私数据并对其进行保护已经成为隐私保护领域中亟需解决的问题。例如,商业领域中,在保证双方隐私信息(公司及其客户的技术数据等)不被非相关人员或企业泄漏的情况下收集客户需求并进行挖掘是较为困难的,往往需要对本文中的隐私数据提取后进行进一步的匿名化等隐私保护操作。现有的隐私保护方法,如K-匿名、差分隐私等技术较为成熟,但缺少对隐私信息识别的关键技术。针对这一问题,本赛题将关注点集中在隐私属性的识别问题中,针对非结构化的本文信息进行分析,对文本中所涉及到的隐私信息精准提取。该任务为后续隐私保护操作提供强有力的支撑,是隐私保护领域的重要前提。

任务:本赛题要求参赛者从提供的非结构化商业文本信息中识别出文本中所涉及到的隐私数据,包括但不限于: (1)公司或个人基本信息:账号、姓名、联系方式、地址等; (2)商业秘密:制造方法、工艺流程、产品名称、专利名称等。

出题单位:明略科技

文件目录说明:

  • data/user_data/cluener 文件夹中存放了 train.json dev.json 这是符合比赛方规定的外部数据。
  • data/user_data/language_model 中存放了我们的预训练模型
  • data/raw_data 路径下存放了该赛道提供的比赛数据,包括train/data train/label test
  • src目录是源码

成绩说明

  • 初赛B榜 rank2
  • 决赛 rank2

ccf-bdci2020-information-reg's People

Contributors

joleo avatar

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