Discovering spaces

Discovering Conceptual Metaphors using Source Domain Spaces

This article makes two contributions towards the use of lexical resources and corpora; specifically making use of them for gaining access to and using word associations. The direct application of our approach is for detecting linguistic and conceptual metaphors automatically in text. We describe our method of building conceptual spaces, that is, defining the vocabulary that characterizes a Sour...

Discovering relevant task spaces using inverse feedback control

Learning complex skills by repeating and generalizing expert behavior is a fundamental problem in robotics. However, the usual approaches do not answer the question of what are appropriate representations to generate motion for a specific task. Since it is time-consuming for a human expert to manually design the motion control representation for a task, we propose to uncover such structure from...

Discovering Domains Mediating Protein Interactions

Background: Protein-protein interactions do not provide any direct information re‌garding the domains within the proteins that mediate the interactions. The majority of proteins are multi domain proteins and the interaction between them is often defined by the pairs of their domains. Most of the former studies focus only on interacting do‌main pairs. However they do not consider the in...

Process spaceship: discovering and exploring process views from event logs in data spaces

Discovering and Characterizing Mobility Patterns in Urban Spaces: A Study of Manhattan Taxi Data

Nowadays, human movement in urban spaces can be traced digitally in many cases. It can be observed that movement patterns are not constant, but vary across time and space. In this work, we characterize such spatio-temporal patterns with an innovative combination of two separate approaches that have been utilized for studying human mobility in the past. First, by using non-negative tensor factor...