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Hej, I'm Jayjay and in this blog you can find some thoughts of mine.
It is a random collection of some project mixed with thoughts of computational devices, algorithms, and the humans' personal deep neural network: the brain.
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General Topics of mine
In Human-Computer Interaction (HCI) it is of high interest to understanding users behaviour since this can be used to personalise the user interface and ensure a satisfying user experience. At this, I try to leverage machine learning techniques to investigate data from mouse movements to identify single users and predict the short- and long-term behaviour of users.

Mouse Movement Analysis

The evaluation of the mouse information is usable to measure the users’ mood, draw conclusions about a users’ satisfaction, or get information about a users’ working behaviour and performance.

Anomaly Detection/ One Class Approaches

Mouse cursor movements are highly influences by many factors (eg. hardware, mood or user interface (UI)) Independent of those influences we try to identify the idiosyncratic movements within the mouse trajectory to autheticate users.

Motif discovery

Similar to gestures, mouse cursor movement encompasses individual components for every user. Likewise some motifs are not user, but task or cognition load dependent.

Time-series analysis

Regarding mouse cursor movements as a sequence of data points collected over time, can deliver valuable information about the point anomalies or other time dependent behaviour.