research data . Dataset . 2018

Neural Network Doc Summarization

Cheng, Junjie;
Open Access English
  • Published: 07 May 2018
  • Publisher: Virginia Tech
  • Country: United States
This is the Neural Network Document Summarization project for the Multimedia, Hypertext, and Information Access (CS 4624) course at Virginia Tech in the 2018 Spring semester. The purpose of this project is to generate a summary from a long document through deep learning. As a result, the outcome of the project is expected to replace part of a human’s work. The implementation of this project consists of four phases: data preprocessing, building models, training, and testing. In the data preprocessing phase, the data set is separated into training set, validation set, and testing set, with the 3:1:1 ratio. In each data set, articles and abstracts are tokenized to ...
Persistent Identifiers
free text keywords: Deep Learning, Natural Language Processing, Text Summarization, Recurrent Neural Network, Sequence to sequence
Related Organizations
Digital Humanities and Cultural Heritage
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