Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Processing topical queries on images of historical newspaper pages   Historical newspapers are a source of research for the human and social
sciences. However, these image collections are difficult to read by machine due
to the low quality of the print, the lack of standardization of the pages in
addition to the low quality photograph of some files. This paper presents the
processing model of a topic navigation system in historical newspaper page
images. The general procedure consists of four modules which are: segmentation
of text sub-images and text extraction, preprocessing and representation,
induced topic extraction and representation, and document viewing and retrieval
interface. The algorithmic and technological approaches of each module are
described and the initial test results about a collection covering a range of
28 years are presented.

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The categories of this paper are: math
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The categories of this paper are: hep-th
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The categories of this paper are: quant-ph
11
The categories of this paper are: hep-lat
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The categories of this paper are: chem-ph
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The categories of this paper are: gr-qc
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The categories of this paper are: cond-mat
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The categories of this paper are: physics
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
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The categories of this paper are: stat
31
The categories of this paper are: ao-sci
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The categories of this paper are: eess
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The categories of this paper are: chao-dyn
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The categories of this paper are: q-fin
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The categories of this paper are: hep-ex