Group items tagged

The paper describes some models for knowledge construction and analyzes them in terms of their suitability as instruments for the introduction of semantics on the web. The paper then provides evidence regarding some limits for the systematic use of semantic search engine and ontology domain systems in everyday teaching and knowledge construction.

Traditionally, visitors to museums have been left having to choose between finding their way around exhibits on their own or taking a standardized group tour with a guide. In this paper, we describe a context-aware museum tour guide that adjusts its recommendations to the interests and contexts of individual visitors and enables them to selectively share their experience with others. The tour guide is built around an innovative semantic Web framework that minimizes the development and maintenance costs associated with the introduction of new exhibits, new visitor-oriented services and new sources of contextual information. In particular, it features a semantic Web rule reasoning engine that enables visitor-oriented services to identify relevant sources of contextual information and to enforce user-specified privacy preferences about what information they are willing to share with others (e.g. "only members of my group can see my current location", or "only my friends can see how I rate exhibits"). While still in prototype stage, the tour guide's target environment is the National Museum of Natural Science, one of Taiwan's largest museums with over 3 million visitors per year.

This document is designed as being a simple but comprehensive introductory publication for anybody trying to get into the Semantic Web: from beginners through to long time hackers. Recommended pre-reading: the Semantic Web in Breadth.

"Special issue on the Semantic Web Issue Editor's Introduction ball The Semantic Web: opportunities and challenges for next-generation Web applications, by Shiyong Lu, Ming Dong and Farshad Fotouhi, Department of Computer Science, Wayne State University, Detroit, Michigan, USA ball Forms of labour in information systems, by Julian Warner, School of Management and Economics, The Queen's University of Belfast, UK ball The Semantic Web, universalist ambition and some lessons from librarianship, by Terrence A. Brooks, Information School, University of Washington, Seattle, Washington, USA ball The necessity for information space mapping for information retrieval on the semantic web, by Gregory B. Newby, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA"

"A naïve ontology for concepts of time and space for searching and learning" Introduction. In this paper, we propose a new approach for developing naïve ontology as the basis for optimal information access interfaces for multimedia digital documents intended for novice users. Method. We try to elicit the knowledge structure of domain novices and patterns of its modification in their searching and learning processes by eye-tracker and showing eye-movements in the post-search interviews. Analysis. Recorded interview data were fully transcribed and coded using Atlas.ti and analysed following a bottom-up strategy of the constant-comparative technique. Results. We developed a taxonomy of knowledge modification which includes (1) adding, (2) correcting, (3) limiting, (4) relating, (5) specifying and (6) transforming. Conclusion.The taxonomy may be expanded and elaborated as the project progress and findings are expected to be incorporated into the design of the naïve ontology. The study results provided theoretical implications on knowledge building, methodological implications on data collection using eye-tracker and showing eye-movements in the post-search interviews and useful information on the design of information access interface for novices users.

"Antoniou, Grigoris and Van Harmelen, Frank. A semantic web primer. Second edition. Cambridge, MA: The MIT Press, 2008. " This is the second edition of the very popular primer that introduces the semantic Web. Explaining what the semantic Web is involves not only contrasting it to the familiar 'everyday' Web, but also sorting out the various visions of the semantic Web suggested over the last decade. Explaining how it works involves relating a thicket of angle-bracket technology to semantics and logic processing. This book is an excellent introduction to both of these explanations.

Thomas K Landauer, Department of Psychology, University of Colorado at Boulder Peter W. Foltz, Department of Psychology, New Mexico State University Darrell Laham, Department of Psychology, University of Colorado at Boulder Latent Semantic Analysis (LSA) is a theory and method for extracting and representing the contextual-usage meaning of words by statistical computations applied to a large corpus of text (Landauer and Dumais, 1997). The underlying idea is that the aggregate of all the word contexts in which a given word does and does not appear provides a set of mutual constraints that largely determines the similarity of meaning of words and sets of words to each other. The adequacy of LSA's reflection of human knowledge has been established in a variety of ways. For example, its scores overlap those of humans on standard vocabulary and subject matter tests; it mimics human word sorting and category judgments; it simulates word<>word and passage<>word lexical priming data; and, as reported in 3 following articles in this issue, it accurately estimates passage coherence, learnability of passages by individual students, and the quality and quantity of knowledge contained in an essay.