TileBars: visualization of term distribution information in full text information access
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
SCAN: designing and evaluating user interfaces to support retrieval from speech archives
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
A scrollbar-based visualization for document navigation
Proceedings of the fourth ACM conference on Digital libraries
A language modelling approach to relevance profiling for document browsing
Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries
Modern Information Retrieval
ThemeRiver: Visualizing Thematic Changes in Large Document Collections
IEEE Transactions on Visualization and Computer Graphics
Visualization of WWW-Search Results
DEXA '99 Proceedings of the 10th International Workshop on Database & Expert Systems Applications
Visualizing Sequential Patterns for Text Mining
INFOVIS '00 Proceedings of the IEEE Symposium on Information Vizualization 2000
Within-Document Retrieval: A User-Centred Evaluation of Relevance Profiling
Information Retrieval
Incident Response & Computer Forensics, 2nd Ed.
Incident Response & Computer Forensics, 2nd Ed.
Sequential Document Visualization
IEEE Transactions on Visualization and Computer Graphics
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Visualization for Information Retrieval (The Information Retrieval Series)
Visualization for Information Retrieval (The Information Retrieval Series)
Digital Investigation: The International Journal of Digital Forensics & Incident Response
Term distribution visualizations with Focus+Context
Multimedia Tools and Applications
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Digital forensic string search is vital to the forensic discovery process, but there has been little research on improving tools or methods for this task. We propose the use of term distribution visualizations to aid digital forensic string search tasks. Our visualization model enables an analyst to quickly identify relevant sections of a text and provides brushing and drilling-down capabilities to support analysis of large datasets. Initial user study results suggest that the visualizations are useful for information retrieval tasks, but further studies must be performed to obtain statistically significant results and to determine specific utility in digital forensic investigations.