Tree-Based Convolutional Neural Networks

Principles and Applications

  • Lili Mou
  • Zhi Jin

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Lili Mou, Zhi Jin
    Pages 1-7
  3. Lili Mou, Zhi Jin
    Pages 9-35
  4. Lili Mou, Zhi Jin
    Pages 41-57
  5. Lili Mou, Zhi Jin
    Pages 91-94
  6. Back Matter
    Pages 95-96

About this book


This book proposes a novel neural architecture, tree-based convolutional neural networks (TBCNNs),for processing tree-structured data. TBCNNsare related to existing convolutional neural networks (CNNs) and recursive neural networks (RNNs), but they combine the merits of both: thanks to their short propagation path, they are as efficient in learning as CNNs; yet they are also as structure-sensitive as RNNs. 

In this book, readers will also find a comprehensive literature review of related work, detailed descriptions of TBCNNs and their variants, and experiments applied to program analysis and natural language processing tasks. It is also an enjoyable read for all those with a general interest in deep learning.


Tree-Based Convolution Neural Networks Deep Learning Natural Language Processing Program Analysis

Authors and affiliations

  • Lili Mou
    • 1
  • Zhi Jin
    • 2
  1. 1.AdeptMind ResearchTorontoCanada
  2. 2.Institute of SoftwarePeking UniversityBeijingChina

Bibliographic information