Text Classification with Document Embeddings

  • Chaochao Huang
  • Xipeng Qiu
  • Xuanjing Huang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8801)

Abstract

Distributed representations have gained a lot of interests in natural language processing community. In this paper, we propose a method to learn document embedding with neural network architecture for text classification task. In our architecture, each document can be represented as a fine-grained representation of different meanings so that the classification can be done more accurately. The results of our experiments show that our method achieve better performances on two popular datasets.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Chaochao Huang
    • 1
    • 2
  • Xipeng Qiu
    • 1
    • 2
  • Xuanjing Huang
    • 1
    • 2
  1. 1.Shanghai Key Laboratory of Intelligent Information ProcessingChina
  2. 2.School of Computer ScienceFudan UniversityShanghaiChina

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