Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Induction of Word and Phrase Alignments for Automatic Document
  Summarization   Current research in automatic single document summarization is dominated by
two effective, yet naive approaches: summarization by sentence extraction, and
headline generation via bag-of-words models. While successful in some tasks,
neither of these models is able to adequately capture the large set of
linguistic devices utilized by humans when they produce summaries. One possible
explanation for the widespread use of these models is that good techniques have
been developed to extract appropriate training data for them from existing
document/abstract and document/headline corpora. We believe that future
progress in automatic summarization will be driven both by the development of
more sophisticated, linguistically informed models, as well as a more effective
leveraging of document/abstract corpora. In order to open the doors to
simultaneously achieving both of these goals, we have developed techniques for
automatically producing word-to-word and phrase-to-phrase alignments between
documents and their human-written abstracts. These alignments make explicit the
correspondences that exist in such document/abstract pairs, and create a
potentially rich data source from which complex summarization algorithms may
learn. This paper describes experiments we have carried out to analyze the
ability of humans to perform such alignments, and based on these analyses, we
describe experiments for creating them automatically. Our model for the
alignment task is based on an extension of the standard hidden Markov model,
and learns to create alignments in a completely unsupervised fashion. We
describe our model in detail and present experimental results that show that
our model is able to learn to reliably identify word- and phrase-level
alignments in a corpus of <document,abstract> pairs.

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The categories of this paper are: nlin
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The categories of this paper are: eess
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The categories of this paper are: cmp-lg
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The categories of this paper are: funct-an
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The categories of this paper are: hep-ex
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The categories of this paper are: q-fin
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The categories of this paper are: plasm-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: hep-th
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The categories of this paper are: math
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The categories of this paper are: chao-dyn
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The categories of this paper are: acc-phys
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The categories of this paper are: comp-gas
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The categories of this paper are: hep-lat
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The categories of this paper are: stat
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The categories of this paper are: q-alg