3,356 research outputs found
Visualizing and Interacting with Concept Hierarchies
Concept Hierarchies and Formal Concept Analysis are theoretically well
grounded and largely experimented methods. They rely on line diagrams called
Galois lattices for visualizing and analysing object-attribute sets. Galois
lattices are visually seducing and conceptually rich for experts. However they
present important drawbacks due to their concept oriented overall structure:
analysing what they show is difficult for non experts, navigation is
cumbersome, interaction is poor, and scalability is a deep bottleneck for
visual interpretation even for experts. In this paper we introduce semantic
probes as a means to overcome many of these problems and extend usability and
application possibilities of traditional FCA visualization methods. Semantic
probes are visual user centred objects which extract and organize reduced
Galois sub-hierarchies. They are simpler, clearer, and they provide a better
navigation support through a rich set of interaction possibilities. Since probe
driven sub-hierarchies are limited to users focus, scalability is under control
and interpretation is facilitated. After some successful experiments, several
applications are being developed with the remaining problem of finding a
compromise between simplicity and conceptual expressivity
Browsing Digital Collections with Reconfigurable Faceted Thesauri
Faceted thesauri group classification terms into hierarchically arranged facets. They enable faceted browsing, a well-known browsing technique that makes it possible to navigate digital collections by recursively choosing terms in the facet hierarchy. In this paper we develop an approach to achieve faceted browsing in live collections, in which not only the contents but also the thesauri can be constantly reorganized. We start by introducing a digital collection model letting users reconfigure facet hierarchies. Then we introduce navigation automata as an efficient way of supporting faceted browsing in these collections. Since, in the worst-case, the number of states in these automata can grow exponentially, we propose two alternative indexing strategies able to bridge this complexity: inverted indexes and navigation dendrograms. Finally, by comparing these strategies in the context of Clavy, a system for managing collections with reconfigurable structures in digital humanities and educational settings, we provide evidence that navigation dendrogram organization outperforms the inverted index-based one
An application of machine learning to the organization of institutional software repositories
Software reuse has become a major goal in the development of space systems, as a recent NASA-wide workshop on the subject made clear. The Data Systems Technology Division of Goddard Space Flight Center has been working on tools and techniques for promoting reuse, in particular in the development of satellite ground support software. One of these tools is the Experiment in Libraries via Incremental Schemata and Cobweb (ElvisC). ElvisC applies machine learning to the problem of organizing a reusable software component library for efficient and reliable retrieval. In this paper we describe the background factors that have motivated this work, present the design of the system, and evaluate the results of its application
Interacting with Web Hierarchies
Web site interfaces are a particularly good fit for hierarchies in the broadest sense of that idea, i.e. a classification with multiple attributes, not necessarily a tree structure. Several adaptive interface designs are emerging that support flexible navigation orders, exposing and exploring dependencies, and procedural information-seeking tasks. This paper provides a context and vocabulary for thinking about hierarchical Web sites and their design. The paper identifies three features that interface to information hierarchies. These are flexible navigation orders, the ability to expose and explore dependencies, and support for procedural tasks. A few examples of these features are also provide
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