Thesis

1
1.1
1.1.1
1.1.2
1.1.3
1.2
1.3
Introduction
Thesis objective
Evaluation properties
Evaluation methodology
Success criteria
The visual explanation system
Next chapters
2
2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.2
2.2.1
2.2.2
2.2.3
2.3
2.3.1
2.3.2
2.4
2.4.1
2.4.2
2.4.3
2.4.4
2.4.5
2.4.6
2.5
Literature study
Recommender systems
Properties of recommender systems
A classification of recommendation algorithms
Challenges for recommender systems
Music recommendation
Information visualization
Types of data
Visual encoding and visual channels
Graph-based visualization
Gaining insight into interactive visualization
Insight gaining
Interactive visualization
Visual explanation systems
Comparing visual explanation systems for item recommendation
PeerChooser
Pharos
SFVis
Smallworlds
TasteWeights
Summary
3
3.1
3.2
3.3
3.4
Requirement analysis
User profile
User story
Story board
Use case diagram
4
4.1
4.1.1
4.1.2
4.2
4.2.1
4.2.2
4.2.3
4.2.4
Iterative development
Methodology
Prototyping
Evaluation techniques
Iterations
Iteration 1: paper prototype
Iteration 2: First digital prototype (SoundSuggest 1.x)
Iteration 3: second digital prototype (SoundSuggest 2.x)
Iteration 4: third digital prototype (SoundSuggest 3.x)
5
5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.2
5.3
5.3.1
5.3.2
Implementation: the SoundSuggest application
Technologies
Chrome extensions
The Last.fm API
D3.js JavaScript Library
Additional libraries
Software design and application architecture
Implementation
Configuration file manifest.JSON
The visualization infovis
6
6.1
6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.3
6.3.1
6.3.2
Conclusion and future work
Objectives
Future work
Issues
Evaluation
Visualization and music
Extensions
Personal reflection
An overview of how the project unfolded
Lessons learned
References
Appendix