Results 161 to 170 of about 662,867 (210)

Knowledge Discovery in Neuroinformatics

2009
Traditionally, the process of turning data into biomedical knowledge has involved “manual” meta-analyses of results reported in journals. Since the amount of scientific data produced in neuroscience today increases dramatically, the resultant expansion of the medical databases has created a significant potential for the design of ...
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Recommendation Knowledge Discovery

2006
Recently we presented a novel approach to the discovery of recommendation rules from a product case base that take account of all features of a recommended product, including those with respect to which the user’s preferences are unknown. In this paper, we investigate the potential role of default preferences in the discovery of recommendation rules ...
David McSherry, Christopher Stretch
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Knowledge discovery with NEFCLASS

KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516), 2002
In order to use fuzzy systems for knowledge discovery, we need algorithms to induce comprehensible fuzzy systems from data. The comprehensibility of a fuzzy model is mainly determined by its number of rules and variables, but also by meaningful membership functions.
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Adversarial Knowledge Discovery

IEEE Intelligent Systems, 2009
In adversarial settings, knowledge discovery must be dynamic, adapting to both the changing face of normality and the rapidly changing properties of adversaries.
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Knowledge discovery in GenBank.

Proceedings. International Conference on Intelligent Systems for Molecular Biology, 1995
We describe various methods designed to discover knowledge in the GenBank nucleic acid sequence database. Using a grammatical model of gene structure, we create a parse tree of a gene using features listed in the FEATURE TABLE. The parse tree infers features that are not explicitly listed, but which follow from the listed features.
Jeffery S. Aaronson, Juergen Haas, G. Christian Overton   +2 more
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Knowledge discovery by inspection

Decision Support Systems, 1997
Abstract Given the enormous size of many business databases, algorithms for knowledge discovery can often be applied to only a sample of the original data. Other methods used to improve efficiency include focusing on a restricted class of rules such as exact rules, or limiting the number of conditions in the discovered rules.
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Discovery of Knowledge in Practice

The American Journal of Occupational Therapy
Abstract Given the number of occupational therapy doctorate (OTD) programs and graduates with professional doctoral degrees, the concept of practice scholarship is increasingly important. The scholarly work of occupational therapy practitioners guided by a research model is appropriate for those who have trained as researchers or OTD ...
Penelope, Moyers, Nicole, Quint
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Qualitative Knowledge Discovery

2008
Knowledge discovery and data mining deal with the task of finding useful information and especially rules in unstructured data. Most knowledge discovery approaches associate conditional probabilities to discovered rules in order to specify their strength. In this paper, we propose a qualitative approach to knowledge discovery.
Gabriele Kern-Isberner, Matthias Thimm, Marc Finthammer   +2 more
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Supporting Knowledge Discovery in Medicine

2014
Our ontology-based benchmarking infrastructure for hospitals, we presented on the eHealth 2012, has meanwhile proven useful. Besides, we gathered manifold experience in supporting knowledge discovery in medicine. This also led to further functions and plans with our software.
Dominic Girardi, Klaus Arthofer
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Applications of Knowledge Discovery

2005
Knowledge Discovery from Databases (KDD) - also named Data Mining - is a growing field since 10 years which combines techniques from databases, statistics, and machine learning. Applications of KDD most often have one of the following goals: - Customer relationship management: who are the best customers, which products are to be offered to which ...
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