Results 31 to 40 of about 73 (69)
Abstract This study focused on a kleptoparasitic bee, Melecta chinensis, which is not well‐known in the Republic of Korea. We provided a detailed morphological illustration of the adult bees and their nesting biological characteristics with distributional data.
Sora Kim +5 more
wiley +1 more source
Redescription Mining With Three Primary Data Mining Functionalities
Describing an object in two ways or shifting the vocabulary of the same concept is Redescription. Not a new problem, Redescription Mining premise had resulted the subsets of objects that afford multiple definitions, in a given Universal set of the same, and a collection of features to describe them.
openaire +1 more source
Abstract Identifying and understanding limiting conditions is at the centre of ecology and biogeography. Traditionally, associations between climate and occurrences of organisms are inferred from observational data using regression analysis, correlation analysis or clustering.
Galbrun Esther +4 more
openaire +3 more sources
Commodity risk assessment of Petunia spp. and Calibrachoa spp. unrooted cuttings from Kenya
Abstract The European Commission requested the EFSA Panel on Plant Health to evaluate the probability of entry of pests (likelihood of pest freedom at entry), including both regulated and non‐regulated pests, associated with unrooted cuttings of the genera Petunia and Calibrachoa produced under physical isolation in Kenya. The relevance of any pest for
EFSA Panel on Plant Health (PLH) +33 more
wiley +1 more source
Using Redescriptions and Formal Concept Analysis for Mining Definitions in Linked Data [PDF]
In this article, we compare the use of Redescription Mining (RM) and Association Rule Mining (ARM) for discovering class definitions in Linked Open Data (LOD). RM is aimed at mining alternate descriptions from two datasets related to the same set of individuals.
Reynaud, Justine +2 more
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Psyche: A Journal of Entomology, Volume 41, Issue 3, Page 133-149, 1934.
A. L. Melander
wiley +1 more source
Exploratory data analysis consists of multiple iterated steps: a data mining method is run on the data, the results are interpreted, new insights are formed, and the resulting knowledge is utilized when executing the method in a next round, and so on until satisfactory results are obtained.
Galbrun, E., Miettinen, P.
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Redescription Mining for Learning Definitions and Disjointness Axioms in Linked Open Data [PDF]
In this article, we present an original use of Redescription Mining (RM) for discovering definitions of classes and incompatibility (disjointness) axioms between classes of individuals in the web of data. RM is aimed at mining alternate descriptions from two datasets related to the same set of individuals.
Reynaud, Justine +2 more
openaire +2 more sources
Turning CARTwheels: An Alternating Algorithm for Mining Redescriptions
We present an unusual algorithm involving classification trees where two trees are grown in opposite directions so that they are matched at their leaves. This approach finds application in a new data mining task we formulate, called "redescription mining". A redescription is a shift-of-vocabulary, or a different way of communicating information about a
Kumar, Deept +3 more
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Redescription Mining: An Overview.
In many real-world data analysis tasks, we have different types of data over the same objects or entities, perhaps because the data originate from distinct sources or are based on different terminologies. In order to understand such data, an intuitive approach is to identify thecorrespondences that exist between these different aspects.
Galbrun, Esther, Miettinen, Pauli
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