Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Data-driven Approach for Quality Evaluation on Knowledge Sharing
  Platform   In recent years, voice knowledge sharing and question answering (Q&A)
platforms have attracted much attention, which greatly facilitate the knowledge
acquisition for people. However, little research has evaluated on the quality
evaluation on voice knowledge sharing. This paper presents a data-driven
approach to automatically evaluate the quality of a specific Q&A platform
(Zhihu Live). Extensive experiments demonstrate the effectiveness of the
proposed method. Furthermore, we introduce a dataset of Zhihu Live as an open
resource for researchers in related areas. This dataset will facilitate the
development of new methods on knowledge sharing services quality evaluation.

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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: stat
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The categories of this paper are: math
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The categories of this paper are: hep-ex
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The categories of this paper are: solv-int
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The categories of this paper are: patt-sol
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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: math-ph
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The categories of this paper are: econ
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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: mtrl-th
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The categories of this paper are: funct-an
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The categories of this paper are: alg-geom