ABSTRACT
The classic TileBars paradigm has been used to show distribution information of query terms in full-text documents. However, when used to show the distribution of a large number of entities of interest to users within a document, it hinders users' quick comprehension due to the inherent visual complexity problem. In this paper, we present a novel approach to improve the visual presentation of TileBars, in which barycenter heuristic for bigraph crossing minimization is used to reorder TileBars' elements. The reordered TileBars enables users to quickly and easily identify which entities appear in the beginning, end, or throughout a document. A user study has shown that the reordered TileBars can provide users with better focus and navigation while exploring text documents.
- W. Ahmad and A. Khokhar. cHawk: An Efficient Biclustering Algorithm based on Bipartite Graph Crossing Minimization. In VLDB Workshop on Data Mining in Bioinformatics, 2007.Google Scholar
- I. S. Dhillon. Co-clustering documents and words using bipartite spectral graph partitioning. Knowledge Discovery and Data Mining, (3):269--274, 2001. Google ScholarDigital Library
- M. A. Hearst. TileBars: visualization of term distribution information in full text information access. In CHI '95: Proceedings of the SIGCHI Conference on Human factors in computing systems, pages 59--66, New York, NY, USA, 1995. ACM. Google ScholarDigital Library
- D. A. Keim and D. Oelke. Literature Fingerprinting: A New Method for Visual Literary Analysis. In VAST 2007: Proceedings of the IEEE Symposium on Visual Analytics Science and Technology 2007, pages 115--122, 2007. Google ScholarDigital Library
- T. M. Mann. Visualization of search results from the World Wide Web. PhD thesis, University of Konstanz, 2002.Google Scholar
- B. Shneiderman. The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations. In IEEE Visual Languages, pages 336--343, 1996. Google ScholarDigital Library
- H. Siirtola and E. Mäkinen. Constructing and reconstructing the reorderable matrix. Information Visualization, 4(1):32--48, 2005. Google ScholarDigital Library
- K. Sugiyama, S. Tagawa, and M. Toda. Methods for Visual Understanding of Hierarchical System Structures. IEEE Transactions on Systems, Man, and Cybernetics, 11(2):109--125, 1981.Google Scholar
- V. Thai, S. Handschuh, and S. Decker. IVEA: An Information Visualization Tool for Personalized Exploratory Document Collection Analysis. In ESWC'08: Proceedings of the 5th European Semantic Web Conference, pages 139--153, Tenerife, Spain, 2008. Springer. Google ScholarDigital Library
- V. Thai, S. Handschuh, and S. Decker. Tight coupling of personal interests with multi-dimensional visualization for exploration and analysis of text collections. In IV'08: Proceedings of the 12th International Conference on Information Visualisation, pages 221--226. IEEE Computer Society, 2008. Google ScholarDigital Library
Index Terms
- Enhanced navigation and focus on TileBars with barycenter heuristic-based reordering
Recommendations
TiCCo: Time-Centric Content Exploration
CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge ManagementTime is a natural way to order information and can be utilized to summarize events and to construct a chronology of contents within a document collection in many application domains. Structuring the sequence of events along a timeline allows users to ...
Fine-grained latency and loss measurements in the presence of reordering
SIGMETRICS '11: Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systemsModern trading and cluster applications require microsecond latencies and almost no losses in data centers. This paper introduces an algorithm called FineComb that can estimate fine-grain end-to-end loss and latency measurements between edge routers in ...
Fine-grained latency and loss measurements in the presence of reordering
Performance evaluation reviewModern trading and cluster applications require microsecond latencies and almost no losses in data centers. This paper introduces an algorithm called FineComb that can estimate fine-grain end-to-end loss and latency measurements between edge routers in ...
Comments