- Walking Wales: the visualisation challenge
- Word Clouds: Can they be misleading?
- VIPS-Visual Interactive Parameter Steering
- Confirmation bias : do multiple views really help?
- Visual Query Interface for Infrastructure Networks
- MADucator – Matrix Educator
- Concensus Matrix Sort
- Multiscale Multiples: An Overview+Detail Interface for Small Multiples
- Analyzing Image Similarity to Detect Disguised Plagiarism
- Tackling the Multi-Analyst Problem in Soccer: How to Improve Collaborative Pattern Detection in Team Sports
- MDSQ – Quality Assessment of Distance-Preserving Projections
- Internal Quality Measures for Subspace Clusterings
- Exploration of Datasets for Visualizations of High-Dimensional Data
- Search and Visual Exploration of Scientific Literature
- Star Glyph – Optimal Dimension Layout
- Visual Analytics of Molecular Neurochemicals and Biological Markers in Mental Illness
- Ensembles of classifiers: Visual construction of classification models
- Cutting-Down the Complexity of Parallel Coordinates Plots in High-Dimensional Data
- Investigating Analytic Behavior in VA
- Hierarchical Matrix Visualization
- Realisierung und Evaluierung einer stereoskopischen 3D Perspective Wall Umgebung für verlinkte Informationsvisualisierung (Master)
- Combination of Matrices + Graphs
- TreeMap Evaluation
- Visual Analysis of Language Change over Time
- Visual Parameter Space Analysis of Topic Models
|Theoretical (Analytical):||(3 / 5)|
|Practical (Implementation):||(5 / 5)|
|Literature Work:||(2 / 5)|
The aim of this project is to develop a method or methods that analyse the similarity of images in documents to identify potential instances of plagiarism. These methods shall be made available by the integration in the CitePlag tool of the Information Science Group of the University of Konstanz.
Available Plagiarism Detection Systems (PDS) capably identify copies, but often fail to detect disguised plagiarism, such as paraphrases, translations, or idea plagiarism. The weakness of current systems results in a large fraction of today’s disguised forms of plagiarism going undetected. We hypothesize that analyzing similarities in images, i.e. figures or graphics, can improve the detection of disguised plagiarism such as strong paraphrases or translations. By additionally visualizing and highlighting the similarity of images the effectiveness of PDS can be further enhanced.
- Review state-of-the-art methods for image analysis.
- Evaluate which image features and analysis methods are most suitable for a plagiarism detection use case.
- Integrate the most suitable features and methods as part of your analysis approach.
- Evaluate the effectivesness and efficiency of your approach.
- (Bring in your own ideas!)
- Good programming skills in Java, basics in web development (HTML, JS, CSS).
- Interest in learning and applying image analysis methods.
- Basic knowledge about information visualization.
- Scope: Bachelor/Master
- 6 Months Project, 3/6 Months Thesis