The document summarizes the applications of LoggerMan, a system for human-computer interaction modeling. It describes how passively collected data from user interactions can be used for (1) creating a digital memory/diary by preserving content created and consumed, (2) security and identification through mouse dynamics, keystrokes dynamics and GUI modeling, (3) analyzing learning difficulties and writing development by logging keyboard activities, and (4) detecting mood, emotion and profiling users based on their computer usage patterns.

1. © Insight 2014. All Rights Reserved
LoggerMan and Applications of Human-
Computer Interaction Modeling
Zaher Hinbarji
Dublin City University
Cathal Gurrin, Rami Albatal

2. © Insight 2015. All Rights Reserved
Outline
• LoggerMan:
• Demo (LoggerMan.org).
• Applications:
• Digital Memory/Diary.
• Security & Identification.
• Learning Difficulties Analysis.
• Mood and Emotion Detection.
• Profiling for Personalisation and Recommendation.
Slide 2

3. © Insight 2015. All Rights Reserved Slide 3
Live demo (LoggerMan.org).
LoggerMan

4. © Insight 2015. All Rights Reserved Slide 4
The passively collected data can be seen as digital memory of
our computer activities.
Digital Memory/Diary

5. © Insight 2015. All Rights Reserved Slide 5
The passively collected data can be seen as digital memory of
our computer activities.
• Content we create (via typing, drawing,..) is preserved.
Digital Memory/Diary

6. © Insight 2015. All Rights Reserved Slide 6
The passively collected data can be seen as digital memory of
our computer activities.
• Content we consume (via reading, web surfing,..) is preserved.
Digital Memory/Diary

7. © Insight 2015. All Rights Reserved Slide 7
The passively collected data can be seen as digital memory of
our computer activities.
• Interest, communication, socialisation and habits are captured.
Digital Memory/Diary

8. © Insight 2015. All Rights Reserved Slide 8
The passively collected data can be seen as digital memory of
our computer activities.
• Automatic summarisation and event/activity/content detection
can be applied to produce richer Diary.
Digital Memory/Diary
Image source:
thesocialbot.com

9. © Insight 2015. All Rights Reserved Slide 9
The passively collected data can be seen as digital memory of
our computer activities.
• Personal search engine.
Digital Memory/Diary

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Capturing the current computer usage prints and matching that
back to the previously built user profiles database.
• Mouse Dynamics
• A signature for each user based on mouse usage
characteristics.
• Keystrokes Dynamics
• Based on the way and the rhythm in which a user types on a
keyboard.
• GUI Modeling.
• Based on the method, skill or style of interaction with a
graphical user interface environment.
• Comprehensive Intrusion Detection System.
Identification & Security

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Keyboard logging provides detailed information about the writing
process that was not accessible previously.
• Cognitive writing.
• Description of writing strategies.
• Children writing development.
• Writing and spelling difficulties analysis.
• Programming and typing skills.
• Predicting pass/fail and supporting online learning.
Learning Difficulties Analysis

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• Stress detection based on keyboard & mouse usage analysis.
• Emotion detection.
• Depression detection?
Mood and Emotion Detection.
Credit: Syda Productions/Shutterstock.com

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• Male/Female.
• Right handed, left handed detection.
• Age categorization.
• Interest (Sport, Movies, NEWS, …).
• Writing style.
• Work shift/schedule detection.
Profiling

14. Thank You