Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Quality Assessment of Linked Datasets using Probabilistic Approximation   With the increasing application of Linked Open Data, assessing the quality of
datasets by computing quality metrics becomes an issue of crucial importance.
For large and evolving datasets, an exact, deterministic computation of the
quality metrics is too time consuming or expensive. We employ probabilistic
techniques such as Reservoir Sampling, Bloom Filters and Clustering Coefficient
estimation for implementing a broad set of data quality metrics in an
approximate but sufficiently accurate way. Our implementation is integrated in
the comprehensive data quality assessment framework Luzzu. We evaluated its
performance and accuracy on Linked Open Datasets of broad relevance.

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The categories of this paper are: hep-ex
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The categories of this paper are: plasm-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: q-fin
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The categories of this paper are: dg-ga
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The categories of this paper are: q-bio
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The categories of this paper are: nucl-ex
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The categories of this paper are: astro-ph
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The categories of this paper are: stat
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The categories of this paper are: nucl-th
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The categories of this paper are: cond-mat
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The categories of this paper are: chem-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: cmp-lg
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The categories of this paper are: physics
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The categories of this paper are: funct-an