The information discovery framework

CHI '05 Extended Abstracts on Human Factors in Computing Systems

Smith

Choi

et al. 2005

Self Cite

Navigational surrogates are representations that stand for information resources within search engine result sets, e-commerce sites, and digital libraries. They also form the basis of personal collections of media, such as web pages. Our hypothesis is that the formats of individual surrogates and collections play an important role in how people use collections. We are particularly interested in processes of information discovery, in which ideas are iteratively reformulated in the context of working with information.To investigate how the representation of navigational surrogates affects how people work with information, we have created a collection of undergraduate psychology curriculum resources in 3 alternative formats: a linear list of textual elements, a spatialized set of textual elements, and a spatialized set of labeled images that have been composited. To evaluate navigation with these surrogate formats during information discovery, we designed divergent browsing tasks, that is, tasks that require assembling information from multiple diverse sources. A within-subjects evaluation indicates that users prefer the spatial labeled images format, and navigate more effectively with it.

Section: Discussionmentioning

confidence: 94%

Section: Experimental Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Evaluating navigational surrogate formats with divergent browsing tasks

CHI '05 Extended Abstracts on Human Factors in Computing Systems

Smith

Choi

et al. 2005

Self Cite

“…Likewise, in such scenarios, the initial semantic definition of cluster centers is problematic. We are interested in addressing scenarios of information discovery [13], in which topics of interest and goals emerge through processes of interacting with and understanding information. The methods developed in this paper address this need by allowing "clusters" to form spontaneously.…”

Section: Implicit and Explicit Clusteringmentioning

confidence: 99%

Generative semantic clustering in spatial hypertext

Proceedings of the 2005 ACM Symposium on Document Engineering

Koh

Sundaram

et al. 2005

Self Cite

This paper presents an iterative method for generative semantic clustering of related information elements in spatial hypertext documents. The goal is to automatically organize them in ways that are meaningful to the user. We consider a process in which elements are gradually added to a spatial hypertext. The method for generating meaningful layout is based on a quantitative model that measures and represents the mutual relatedness between each new element and those already in the document. The measurement is based on attributes such as metadata, term vectors, user interest expressions, and document locations. We call this model relatedness potential, because it represents how much the new element is related and thus attracted to existing elements as a vector field across the space. Using this field as a gradient potential, the new element will be placed near the most attracted elements, forming clusters of related elements. The relative magnitude of contribution of attributes to relatedness potential can be controlled through an interactive interface.Unlike prior clustering methods such as k-means and selforganizing-maps, relatedness potential works well in iterative systems, in which the collection of elements is not defined a priori. Further, users can invoke relatedness potential to re-cluster elements, as they engage in on-the-fly provisional acts of direct manipulation reorganization and latching of a few most significant elements. A preliminary study indicates that users find this method generates spatial hypertext documents that are easier to read.

“…The goal is to learn. Information-based ideation is the creative process where new ideas emerge from seeing relationships between existing ideas while working with information [19]. This can occur when Grace is authoring a prior work collection for her science project, highlighting a new focus for her research.…”

Section: Introductionmentioning

confidence: 99%

Integrating implicit structure visualization with authoring promotes ideation

Webb

Proceedings of the 11th Annual International ACM/IEEE Joint Conference on Digital Libraries

2011

Self Cite

We need to harness the growing wealth of information in digital libraries to support intellectual work involving creative and exploratory processes. Prior research on hypertext authoring shifted the focus from explicit structure to direct presentation of content aided by "implicit" spatial representation of structure. We likewise shift the field of information visualization. Using hypertext's rubric, we redefine what most people think of as "information visualization" as explicit structure visualization. We alternatively address implicit structure visualization, presenting content directly, representing structure with spatiality and other visual features. We integrate authoring to emphasize the role of human thought in learning and ideation. Prior research has shown that people iteratively collect and organize information by clipping magazines, piling clippings in somewhat messy ways, and organizing them.MessyOrganizer is an iterative implicit structure visualization algorithm which, like human practice, gradually collects and organizes information clippings. Content is depicted directly. Structural relationships are visualized implicitly through spatial positioning of related elements, with overlap and translucence. The simulated annealing algorithm is applied to a model of semantic relatedness over a spatial grid. We develop an experiment comparing products created with the integrated environment versus separated visualization and authoring spaces. Results reveal that participants have more novel and varied ideas when visualization is integrated with authoring.