Property:Query depth

"Query depth" is a predefined property that informs about the depth of a query and is provided by Semantic MediaWiki. It is a numerical value computed on the basis of subquery nesting, property chains, and available description elements with the execution of a query being restricted by the $smwgQMaxDepth configuration parameter. This property is pre-deployed (also known as special property) and comes with additional administrative privileges but can be used just like any other user-defined property.

Usage1497

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Filter<p>The <a rel="nofollow" class="external text" href="https://www.semantic-mediawiki.org/wiki/Help:Property_page/Filter">search filter</a> allows the inclusion of <a rel="nofollow" class="external text" href="https://www.semantic-mediawiki.org/wiki/Help:Query_expressions">query expressions</a> such as <code>~</code> or <code>!</code>. The selected <a rel="nofollow" class="external text" href="https://www.semantic-mediawiki.org/wiki/Query_engine">query engine</a> might also support case insensitive matching or other short expressions like:</p><ul><li><code>in:</code> result should include the term, e.g. '<code>in:Foo</code>'</li></ul><ul><li><code>not:</code> result should to not include the term, e.g. '<code>not:Bar</code>'</li></ul>

Showing 20 pages using this property.

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Ulf Holmberg +

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Ulf Holmberg +

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Ulf Holmberg +

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Ulf Holmberg +

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Understanding Association Between Logged Vehicle Data and Vehicle Marketing Parameters - Using Clustering and Rule-Based Machine Learning +

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Understanding Association Between Logged Vehicle Data and Vehicle Marketing Parameters -- Using Clustering and Rule-Based Machine Learning +

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Unsupervised classification of slip events for planetary exploration rovers +

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Unsupervised colour image segmentation applied to printing quality assessment +

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Unsupervised deviation detection by GMM - A simulation study +

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Upper limit for context-based crop classification in robotic weeding applications +

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Using Histograms to Find Compressor Deviations in Bus Fleet Data +

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Using Labelled and Unlabelled Data to Train a Multilayer Perceptron for Colour Classification in Graphic Arts +

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Using Multiple Cylinder Ion Measurements for Improved Estimation of Combustion Variability +

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Using Unlabelled Data to Train a Multilayer Perceptron +

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Using artificial neural networks for process and system modelling +

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Using linear symmetry features as a pre-processing step for fingerprint images +

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Using the patient's questionnaire data to screen laryngeal disorders +

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Using unlabelled data to train a multilayer perceptron +

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V-Charge +

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V-Charge +

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