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George Bradford

A naïve ontology for concepts of time and space for searching and learning - 0 views

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    "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.
George Bradford

Semantic Networks - 0 views

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    John F. Sowa - This is a revised and extended version of an article that was originally written for the Encyclopedia of Artificial Intelligence, edited by Stuart C. Shapiro, Wiley, 1987, second edition, 1992. A semantic network or net is a graphic notation for representing knowledge in patterns of interconnected nodes and arcs. Computer implementations of semantic networks were first developed for artificial intelligence and machine translation, but earlier versions have long been used in philosophy, psychology, and linguistics. What is common to all semantic networks is a declarative graphic representation that can be used either to represent knowledge or to support automated systems for reasoning about knowledge. Some versions are highly informal, but other versions are formally defined systems of logic. Following are six of the most common kinds of semantic networks, each of which is discussed in detail in one section of this article.
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