InfoCrystal, a visual tool for information retrieval

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1995.Includes bibliographical references (p. 227-232).by Anselm Spoerri.Ph.D

A review of data visualization: opportunities in manufacturing sequence management.

Data visualization now benefits from developments in technologies that offer innovative ways of presenting complex data. Potentially these have widespread application in communicating the complex information domains typical of manufacturing sequence management environments for global enterprises. In this paper the authors review the visualization functionalities, techniques and applications reported in literature, map these to manufacturing sequence information presentation requirements and identify the opportunities available and likely development paths. Current leading-edge practice in dynamic updating and communication with suppliers is not being exploited in manufacturing sequence management; it could provide significant benefits to manufacturing business. In the context of global manufacturing operations and broad-based user communities with differing needs served by common data sets, tool functionality is generally ahead of user application

The effect of different set-based visualizations on user exploration of recommendations

When recommendations fail, trust in a recommender system often decreases, particularly when the system acts like a "black box". To deal with this issue, it is important to support exploration of recommendations by explicitly exposing relationships that can provide explanations. As an example, a graph-based visualization can help to explain collaborative filtering results by representing relationships among items and users. In our work, we focus on the use of visualization techniques to support exploration of multiple relevance prospects - such as relationships between different recommendation methods, socially connected users and tags. More specifically, we researched how users explore relationships between such multiple relevance prospects with two set-based visualization techniques: a clustermap and a Venn diagram. A comparative analysis of user studies with these two approaches indicates that, although effectiveness of recommendations increases with the use of a clustermap, the approach is too complex for a non-technical audience. A Venn diagram representation is more intuitive and users are more likely to explore relationships that help them find relevant items

Linguistic Geometries for Unsupervised Dimensionality Reduction

Text documents are complex high dimensional objects. To effectively visualize such data it is important to reduce its dimensionality and visualize the low dimensional embedding as a 2-D or 3-D scatter plot. In this paper we explore dimensionality reduction methods that draw upon domain knowledge in order to achieve a better low dimensional embedding and visualization of documents. We consider the use of geometries specified manually by an expert, geometries derived automatically from corpus statistics, and geometries computed from linguistic resources.Comment: 13 pages, 15 figure

The State-of-the-Art of Set Visualization

Sets comprise a generic data model that has been used in a variety of data analysis problems. Such problems involve analysing and visualizing set relations between multiple sets defined over the same collection of elements. However, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-the-art techniques for visualizing different kinds of set relations. We classify these techniques into six main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address these challenges. Further resources on set visualization are available at http://www.setviz.net