Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Graph Based Classification Methods Using Inaccurate External Classifier
  Information   In this paper we consider the problem of collectively classifying entities
where relational information is available across the entities. In practice
inaccurate class distribution for each entity is often available from another
(external) classifier. For example this distribution could come from a
classifier built using content features or a simple dictionary. Given the
relational and inaccurate external classifier information, we consider two
graph based settings in which the problem of collective classification can be
solved. In the first setting the class distribution is used to fix labels to a
subset of nodes and the labels for the remaining nodes are obtained like in a
transductive setting. In the other setting the class distributions of all nodes
are used to define the fitting function part of a graph regularized objective
function. We define a generalized objective function that handles both the
settings. Methods like harmonic Gaussian field and local-global consistency
(LGC) reported in the literature can be seen as special cases. We extend the
LGC and weighted vote relational neighbor classification (WvRN) methods to
support usage of external classifier information. We also propose an efficient
least squares regularization (LSR) based method and relate it to information
regularization methods. All the methods are evaluated on several benchmark and
real world datasets. Considering together speed, robustness and accuracy,
experimental results indicate that the LSR and WvRN-extension methods perform
better than other methods.

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The categories of this paper are: math
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The categories of this paper are: astro-ph
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The categories of this paper are: physics
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The categories of this paper are: q-alg
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The categories of this paper are: atom-ph
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The categories of this paper are: q-fin
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The categories of this paper are: cmp-lg
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The categories of this paper are: bayes-an
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The categories of this paper are: nlin
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The categories of this paper are: chao-dyn
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The categories of this paper are: patt-sol
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The categories of this paper are: alg-geom
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The categories of this paper are: cond-mat
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The categories of this paper are: acc-phys
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The categories of this paper are: gr-qc
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The categories of this paper are: plasm-ph