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Database Module
The 'Database Module' aims to introduce database analysis, focusing on DBMS architecture, Relational Models, SQL language and SQL nested queries. It is part of the Master in...-
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Information Retrieval Module
Study, design and analysis of IR systems which are efficient and effective to process, mine, search, cluster and classify bigdata document collections, coming from textual as...-
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Business Data Analytics Course
The training material provided by the University of Tartu is about the Business Data Analytics course. This course is meant for students as a hands-on experience for solving...-
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Archive Spark
An Apache Spark framework for easy data processing, extraction as well as derivation for archival collections. Originally developed for the use with Web archives, it has now... -
Efficiency - Effectiveness Trade-offs in Learning to Rank
This tutorial provides an 'Introduction to Learning to Rank' and focuses on 'Dealing with the Efficiency/Effectiveness trade-off in Web Search'. Moreover, it provides two...-
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Text Analytics and Opinion Mining Module
The goals of this module are: - Have a general knowledge of text mining problems and methods. - Recognize situations in which Sentiment Analysis techniques can solve...-
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GATE Course
The material is the 2017 version of a week-long training course delivered annually by the GATE team. Over almost ten years, this course has been developed to provide basic and...-
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Data Management for Business Intelligence Module
This module provides an introduction to information storage and management performed in order to support business decisions of organizations. It is part of the Master in Big...-
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Data Mining and Machine Learning Module
The module provides an introduction to base concepts of data mining and knowledge extraction process, introducing analytical models and algorithms for clustering,...-
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Visual Analytics for Data Scientists
Participants to this module shall - Learn the principles and rules underlying the design of visual data representations and human-computer interactions - Understand,...-
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Data Visualisation and Visual Analytics Module
This module provides an introduction to the concepts of vision and perception in order to design an effective data visualisation. Moreover, it provides insight into visual...-
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Ego network analysis, information-driven social links and impact on informati...
Slide from the Summer School on Computational Misinformation Analysis 2019 lesson-
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The Role of the GDPR in Designing the European Strategy on Artificial Intelli...
Starting from an analysis of the EU Reg. n. 2016/679 on General Data Protection Regulation (GDPR), the Author deals with the opportunity to translate the current strategies on...-
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Big other Surveillance capitalism and the prospects of an information civiliz...
This article describes an emergent logic of accumulation in the networked sphere, ‘surveillance capitalism,’ and considers its implications for ‘information civilization.’ The... -
Compressed and Learned Data Structures Seminar
In this seminar cycle, students are guided in the direct usage of a powerful C++ library implementing many state-of-the-art compressed data structures for big data. Other than...-
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Big Data and Due Process Toward a Framework to Redress Predictive Privacy Harms
The rise of “Big Data” analytics in the private sector poses new challenges for privacy advocates. Through its reliance on existing data and predictive analysis to create... -
Explaining misclassification and attacks in deep learning via random forests
Artificial intelligence, and machine learning (ML) in particular, is being used for different purposes that are critical for human life. To avoid an algorithm-based...-
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Information Technology Privacy and the Protection of Personal Data
Information technology allows us to generate, store, and process huge quantities of data. Search engines, satellites, sensor networks, scientists, security agencies,... -
Efficient detection of Byzantine attacks in federated learning using last lay...
Federated learning (FL) is an alternative to centralized machine learning (ML) that builds a model across multiple decentralized edge devices (a.k.a. workers) that own the...-
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Conformity a Path-Aware Homophily measure for Node-Attributed Networks
Unveil the homophilic/heterophilic behaviors that characterize the wiring patterns of complex networks is an important task in social network analysis, often approached...-
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