Text Classification with Document Embeddings

  • Chaochao Huang
  • Xipeng Qiu
  • Xuanjing Huang
Conference paper

DOI: 10.1007/978-3-319-12277-9_12

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8801)
Cite this paper as:
Huang C., Qiu X., Huang X. (2014) Text Classification with Document Embeddings. In: Sun M., Liu Y., Zhao J. (eds) Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data. Lecture Notes in Computer Science, vol 8801. Springer, Cham

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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