151,982 research outputs found
How to Find Suitable Ontologies Using an Ontology-based WWW Broker
Knowledge reuse by means of outologies now faces three important problems: (1) there are no standardized identifying features that characterize ontologies from the user point of view; (2) there are no web sites using the same logical organization, presenting relevant information about ontologies; and (3) the search for appropriate ontologies is hard, time-consuming and usually fruitless. To solve the above problems, we present: (1) a living set of features that allow us to characterize ontologies from the user point of view and have the same logical organization; (2) a living domain ontology about ontologies (called ReferenceOntology) that gathers, describes and has links to existing ontologies; and (3) (ONTO)2Agent, the ontology-based www broker about ontologies that uses the Reference Ontology as a source of its knowledge and retrieves descriptions of ontologies that satisfy a given set of constraints. (ONTO)~Agent is available at http://delicias.dia.fi.upm.es/REFERENCE ONTOLOGY
Categorical invariance and structural complexity in human concept learning
An alternative account of human concept learning based on an invariance measure of the categorical\ud
stimulus is proposed. The categorical invariance model (CIM) characterizes the degree of structural\ud
complexity of a Boolean category as a function of its inherent degree of invariance and its cardinality or\ud
size. To do this we introduce a mathematical framework based on the notion of a Boolean differential\ud
operator on Boolean categories that generates the degrees of invariance (i.e., logical manifold) of the\ud
category in respect to its dimensions. Using this framework, we propose that the structural complexity\ud
of a Boolean category is indirectly proportional to its degree of categorical invariance and directly\ud
proportional to its cardinality or size. Consequently, complexity and invariance notions are formally\ud
unified to account for concept learning difficulty. Beyond developing the above unifying mathematical\ud
framework, the CIM is significant in that: (1) it precisely predicts the key learning difficulty ordering of\ud
the SHJ [Shepard, R. N., Hovland, C. L.,&Jenkins, H. M. (1961). Learning and memorization of classifications.\ud
Psychological Monographs: General and Applied, 75(13), 1-42] Boolean category types consisting of three\ud
binary dimensions and four positive examples; (2) it is, in general, a good quantitative predictor of the\ud
degree of learning difficulty of a large class of categories (in particular, the 41 category types studied\ud
by Feldman [Feldman, J. (2000). Minimization of Boolean complexity in human concept learning. Nature,\ud
407, 630-633]); (3) it is, in general, a good quantitative predictor of parity effects for this large class of\ud
categories; (4) it does all of the above without free parameters; and (5) it is cognitively plausible (e.g.,\ud
cognitively tractable)
Ontology-based composition and matching for dynamic cloud service coordination
Recent cross-organisational software service offerings, such as cloud computing, create higher integration needs.
In particular, services are combined through brokers and mediators, solutions to allow individual services to collaborate and their interaction to be coordinated are required. The need to address dynamic management - caused by cloud and on-demand environments - can be addressed through service coordination based on ontology-based composition and matching techniques. Our solution to composition and matching utilises a service coordination space that acts as a passive infrastructure for collaboration where users submit requests that are then selected and taken on by providers. We discuss the information models and the coordination principles of such a collaboration environment in terms of an ontology and its underlying description logics. We provide ontology-based solutions for structural composition of descriptions and matching between requested and provided services
Exploring the Academic/Creative Writing Binary
I began to work on this study in my ENG 201: Writing in the Disciplines class during my junior year at Pace University. After being asked to write a paper on what writing looks like in my discipline, I realized that my perceptions of the kinds of writing done by faculty and students in a university English department were limited and constricting as a result of the binary way in which I viewed academic and creative forms of writing. For instance, I had trouble believing that my creative writing professor studied pre-med in undergrad. I continued my research on this topic by developing a study to discover how faculty and undergraduates think about writing in an English department. In conducting this research, I hoped to redefine and illustrate potential overlaps between academic and creative writing and to propose new (perhaps more fluid or capacious) ways of labeling and conveying the kind of writing students and faculty produce. Specifically, I wanted to explore whether these are terms or categories that either groups use, or whether faculty and studentsâ perceptions of academic and creative writing challenge these categories.
I explored these concepts through a qualitative study. After obtaining IRB approval, I devoted one class of Meaghan Brewerâs English 201:Writing in the Discplines to a workshop where students in the class brought in samples of their own writing and then put them into categories and created labels. Students filled out a form giving a rationale for how they labeled different kinds of writing before having a class discussion. I repeated the same process in a composition faculty meeting in the English department. These activities are modeled on activities described in research by composition scholar Anne Ruggles Gere. This highly contextual, qualitative research is commonplace in composition studies and has been present in the majority of my initial literature review.
In conducting this study, my largest obstacle was the small amount of time I had to analyze the results of my activities between drafts. However, the data collected exceeded my expectations in that, like in much of the research cited in this paper, I found students had binary views of academic and creative writing despite not using them often as labels. For the most part, they described academic as being constricting and reliant on structure whereas they saw creative as a freer style that allowed them to voice an opinion. On the contrary, faculty used these terms more frequently, but thought about them in less binary ways. After having a group discussion, both faculty and students appeared to have broadened the way they looked at writing which is what I was hoping to encourage with this study. My findings suggest that faculty members need to create curricula that encourage students to see genres in more complex ways. Future research might explore how expanding the approach to teaching genre could redefine student perceptions of college writing
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