This is one example of concepts introduced in the free source: The Epistemological Lifeboat. Epistemology and Philosophy of Science for Information Scientists. Birger Hjørland & Jeppe Nicolaisen (eds.) - Web design: Pernille Brandt. / Present the concept of knowledge representation from an epistemological point of view. A given knowledge representation is always reflecting the object being represented as well as the subject doing the representation. Any given knowledge representation is always biased and perspectival. Knowledge representation in Media Studies, Psychology, Linguistics,Computer Science & Artificial Intelligence is briefly overviewed. The article is intended as an introduction to this concept for library and Information Scientists.

Artificial Intelligence Lab, Department of MIS, University of Arizona / Concept maps (CM) are informal, semantic, node-link conceptual graphs used to represent knowledge in a variety of applications. Algorithms that compare concept maps would be useful in supporting educational processes and in leveraging indexed digital collections of concept maps. Map comparison begins with element matching and faces computational challenges arising from vocabulary overlap, informality, and organizational variation. Our implementation of an adapted similarity flooding algorithm improves matching of CM knowledge elements over a simple string matching approach.

Theories of categorization typically assume that categories are represented by some set of features that describe the properties of category members. However this view of category representation is incomplete. This dissertation lays out a framework for category representation, following Markman and Stilwell (2001), that creates a taxonomy of categories based on different components of relational structures. Relational categories are categories of entire relational systems while, role-governed categories, are represented as the roles in these systems. Lastly, thematic-relation categories group entities together that play complementary roles within a system. Four experiments are presented in support of this framework. They contrast thematic-relation categorization with role-governed categorization. Thematic-relation categorization entails categorizing objects together that play different roles within a domain, while role-governed categorization entails categorizing two entities that play the same role across domains. When the two are put in direct conflict, people prefer to form a thematic-relation category because within-domain connections are easier to find than across-domain connections. The purpose of the four experiments is to examine ways to boost the preference for role-governed categorization, thus revealing underlying processes. Here, role-governed categorization is facilitated in two ways. Experiment 1 re-frames the question of category formation as novel word extension. Natural role-governed categories have labels while thematic-relation categories do not. This pattern is reflected in the measured behavior as novel labels are extended across members of role-governed categories more readily than across members of thematic-relation categories. By claiming relational structures are critical to category representation, the framework described in this dissertation predicts that role-governed categorization and analogical reasoning share underlying mechanisms. Experiments 2-4 examine how making an analogy between the members of role-governed categories facilitates forming such categories. When making an analogy, people align the relational representations of a pair of domains, putting entities into correspondence by role, ignoring featural dissimilarities. When analogical comparison is induced, the rate of role-governed categorization is shown to double as compared to a baseline with no such analogical processes. The thesis concludes by outlining several future lines of research generated by unifying the fields of analogy and concept learning. / text

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Thesis (Ph. D.)--University of Sydney, 2009. / Title from title screen (viewed November 13, 2009). Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy to the Faculty of Architecture, Design and Planning in the Faculty of Science. Includes graphs and tables. Includes bibliographical references. Also available in print form.

This article provides an overview of recent developments relating to the application of thesauri in information organisation and retrieval on the World Wide Web. It describes some recent thesaurus projects undertaken to facilitate resource description and discovery and access to wide-ranging information resources on the Internet. Types of thesauri available on the Web, thesauri integrated in databases and information retrieval systems, and multiple-thesaurus systems for cross-database searching are also discussed. Collective efforts and events in addressing the standardisation and novel applications of thesauri are briefly reviewed.

Artificial Intelligence Lab, Department of MIS, University of Arizona / We report results of an investigation where thirty subjects were observed performing subject-based search in an online catalog system. The observations have revealed a range of misconceptions users have when performing subject-based search. We have developed a taxonomy that characterizes these misconceptions and a knowledge representation which explains these misconceptions. Directions for improving search performance are also suggested.

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