Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Comprehend DeepWalk as Matrix Factorization   Word2vec, as an efficient tool for learning vector representation of words
has shown its effectiveness in many natural language processing tasks. Mikolov
et al. issued Skip-Gram and Negative Sampling model for developing this
toolbox. Perozzi et al. introduced the Skip-Gram model into the study of social
network for the first time, and designed an algorithm named DeepWalk for
learning node embedding on a graph. We prove that the DeepWalk algorithm is
actually factoring a matrix M where each entry M_{ij} is logarithm of the
average probability that node i randomly walks to node j in fix steps.

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The categories of this paper are: adap-org
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The categories of this paper are: nucl-ex
28
The categories of this paper are: alg-geom
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The categories of this paper are: chao-dyn
20
The categories of this paper are: acc-phys
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat
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The categories of this paper are: nucl-th
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The categories of this paper are: atom-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: eess
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The categories of this paper are: stat
2
The categories of this paper are: math
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The categories of this paper are: chem-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: ao-sci