2016

A Study of MatchPyramid Models on Ad-hoc Retrieval

Pang, Liang, Lan, Yanyan, Guo, Jiafeng et al.

Understand

Deep neural networks have been successfully applied to many text matching tasks, such as paraphrase identification, question answering, and machine translation.

  • Although ad-hoc retrieval can also be formalized as a text matching task, few deep models have been tested on it.
  • In this paper, we study a state-of-the-art deep matching model, namely MatchPyramid, on the ad-hoc retrieval task.
  • The MatchPyramid model employs a convolutional neural network over the interactions between query and document to produce the matching score.

Built on

  • Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval

    S. E. Robertson and S. Walker · 1994

    Earlier work this paper cites.

  • Overfitting in neural nets: Backpropagation, conjugate gradient, and early stopping

    R. C. S. L. L. Giles · 2001

    Earlier work this paper cites.

  • A study of smoothing methods for language models applied to ad hoc information retrieval

    C. Zhai and J. Lafferty · 2001

    Earlier work this paper cites.

  • Dynamic pooling and unfolding recursive autoencoders for paraphrase detection

    R. Socher, E. H. Huang, J. Pennin, C. D. Manning, and A. Y. Ng · 2011

    Earlier work this paper cites.

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Then

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