Search (27 results, page 2 of 2)

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Abstract

Attempts to automate classification have focused on mimicking the intellectual processes whereby human classifiers assign entities to mutually exclusive groups that exhibit or more shared characteristics. A more viable approach might be to construct an adaptive retrieval system that produces groupings of related entities by generating dynamic categories based on document content and on the system's emergent structure as it adapts to modifications in the database and to observed patterns of access. Presents a theoretical model for adaptive information networks using relevance feedback and genetic algorithms to generate emergent structure

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Series

Advances in knowledge organization; vol.8

Source

Challenges in knowledge representation and organization for the 21st century: Integration of knowledge across boundaries. Proceedings of the 7th ISKO International Conference Granada, Spain, July 10-13, 2002. Ed.: M. López-Huertas

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Abstract

Icons are graphic images with functional roles in human-computer interaction. They may be used as conceptual tools to represent the organization of information or as operators affecting an activity such as printing or moving to another document. An icon may represent its referent either as a sign, a purely arbitrary relationship that must be learned by the user; as a pictograph, a visual image of the object represented, or as an ideogram, whre the referent is not a concrete entity but an attribute, a set of attributes, or an abstract concept associated with the referent. The symbolicity of an icon reflects the drgree of representativeness that obtains between an icon and its referent(s). We propose to examine symbolic languages composed of sets of icons and to assess their effectiveness as classificatory structures in terms of: 1) representation of hierarchical structure; 2) level of symbolicity; 3) contexts that promote the capability of icons to represent organization; 4) relationship between an underlying metaphorical framework and iconic representation of the organization; 5) graphic elements of effective symbolic languages; and 6) social or cultural factors related to the effectiveness of icons

Series

Advances in knowledge organization; vol.5

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Abstract

One major aspect of T.D. Wilson's research has been his insistence on situating the investigation of information behaviour within the context of its occurrence - within the everyday world of work. The significance of this approach is reviewed in light of the notion of embodied cognition that characterises the evolving theoretical episteme in cognitive science research. Embodied cognition employs complex external props such as stigmergic structures and cognitive scaffoldings to reduce the cognitive burden on the individual and to augment human problem-solving activities. The cognitive function of the classification scheme is described as exemplifying both stigmergic structures and cognitive scaffoldings. Two different but complementary approaches to the investigation of situated cognition are presented: cognition-as-scaffolding and cognition-as-infrastructure. Classification-as-scaffolding views the classification scheme as a knowledge storage device supporting and promoting cognitive economy. Classification-as-infrastructure views the classification system as a social convention that, when integrated with technological structures and organisational practices, supports knowledge management work. Both approaches are shown to build upon and extend Wilson's contention that research is most productive when it attends to the social and organisational contexts of cognitive activity by focusing on the everyday world of work.

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Abstract

Social tagging is one of the major phenomena transforming the World Wide Web from a static platform into an actively shared information space. This paper addresses various aspects of social tagging, including different views on the nature of social tagging, how to make use of social tags, and how to bridge social tagging with other Web functionalities; it discusses the use of facets to facilitate browsing and searching of tagging data; and it presents an analogy between bibliometrics and tagometrics, arguing that established bibliometric methodologies can be applied to analyze tagging behavior on the Web. Based on the Upper Tag Ontology (UTO), a Web crawler was built to harvest tag data from Delicious, Flickr, and YouTube in September 2007. In total, 1.8 million objects, including bookmarks, photos, and videos, 3.1 million taggers, and 12.1 million tags were collected and analyzed. Some tagging patterns and variations are identified and discussed.

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Abstract

Data integration and mediation have become central concerns of information technology over the past few decades. With the advent of the Web and the rapid increases in the amount of data and the number of Web documents and users, researchers have focused on enhancing the interoperability of data through the development of metadata schemes. Other researchers have looked to the wealth of metadata generated by bookmarking sites on the Social Web. While several existing ontologies have capitalized on the semantics of metadata created by tagging activities, the Upper Tag Ontology (UTO) emphasizes the structure of tagging activities to facilitate modeling of tagging data and the integration of data from different bookmarking sites as well as the alignment of tagging ontologies. UTO is described and its utility in modeling, harvesting, integrating, searching, and analyzing data is demonstrated with metadata harvested from three major social tagging systems (Delicious, Flickr, and YouTube).

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Abstract

Usability of Web sites has become an increasingly important area of research as Web sites proliferate and problems with use are noted. Generally, aspects of Web sites that have been investigated focus on such areas as overall design and navigation. The exploratory study reported on here investigates one specific component of a Web site-the index structure. By employing index usability metrics developed by Liddy and Jörgensen (1993; Jörgensen & Liddy, 1996) and modified to accommodate a hypertext environment, the study compared the effectiveness and efficiency of 20 subjects who used one existing index (the A-Z index on the FedStats Web site at http://www.fedstats.gov) and three experimental variants to complete five researcher-generated tasks. User satisfaction with the indexes was also evaluated. The findings indicate that a hypertext index with multiple access points for each concept, all linked to the same resource, led to greater effectiveness and efficiency of retrieval on almost all measures. Satisfaction measures were more variable. The study offers insight into potential improvements in the design of Web-based indexes and provides preliminary assessment of the validity of the measures employed