User data can be acquired from various domains and is characterized by a combination of
demographics such as age and occupation, and user actions such as rating a movie or …

We address the problem of discovering contexts that lead well-distinguished collections of
individuals to change their pairwise agreement wrt their usual one. For instance, in the …

Upskilling is a fast-growing segment of the education economy. Yet, there is little algorithmic
work that focuses on crafting dedicated strategies to reach high-skill mastery. In this paper …

User data is becoming increasingly available in multiple domains ranging from the social
Web to retail store receipts. User data is described by user demographics (eg, age, gender …

User data is becoming increasingly available in various domains ranging from the social
Web to electronic patient health records (EHRs). User data is characterized by a …

We strive to find contexts (ie, subgroups of entities) under which exceptional (dis-)
agreement occurs among a group of individuals, in any type of data featuring individuals …

The increasing availability of rating datasets (ie, datasets containing user evaluations on
items such as products and services) constitutes a new opportunity in various applications …

We demonstrate VEXUS, an interactive visualization framework for exploring user data to
fulfill tasks such as finding a set of experts, forming discussion groups and analyzing …

Data Science (DS) has been shifting from libraries and stacks to usage and impact. While"
database thinking" is permeating all levels in a DS stack, the DS lifecycle can only be fully …

We tackle the problem of recommending tests to learners to achieve upskilling. Our work is
grounded in two learning theories: mastery learning, an instructional strategy that guides …