报告题目：Large Scale Privacy Preserving Data Integration

主讲人：Fausto Giunchiglia

讲座时间：2019年4月9日（星期二）10:00-11:30

讲座地点：吉林大学中心校区匡亚明楼2层匡亚明第一会议室

报告人简介：

Fausto Giunchiglia，吉林大学未来科学国际合作联合实验室首席科学家，意大利特伦托大学教授，欧洲科学院院士，国际著名人工智能专家。

报告摘要：

The theory says that big data analytics will allow us tounderstand and predict the evolution of almost any world phenomenon. Thepractice tells us that, at the moment, there are at least two hiddencomplexities which limit substantially the full exploitation of analytics,machine learning and AI in general. The first is that, with a fewexceptions (e.g., Google, WeChat or Facebook) the big data which areneeded, for instance to train our models, do not exist. In practice theymust be constructed via the integration of data which come from multipleheterogeneous data silos. And the cost of this operation is very high,growing exponentially with the size of data. The second is that anyexperiment we have done provides evidence that the amount of informationwhich can be extracted from data is very high, far beyond our initialexpectations. And this rises a lot of issues when these data involve, asit is often the case, personal data.

The goal of this talk is to describe a general data integrationmethodology, and support tools, which allow to cut radically the cost ofthe data integration while, at the same time being privacy aware bydesign. We will also describe how it has been applied in a case study inthe Health domain in a way to be GDPR compliant, as required by theEuropean legislation.

主办单位：吉林大学人工智能学院

吉林大学计算机科学与技术学院

吉林大学人工智能研究院