Tree-Based Convolutional Neural Networks Principles and Applications /

• Κύριοι συγγραφείς: Mou, Lili (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Jin, Zhi (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: SpringerBriefs in Computer Science,
• Θέματα: Artificial intelligence.; Data mining.; Computational intelligence.; Software engineering.; Artificial Intelligence.; Data Mining and Knowledge Discovery.; Computational Intelligence.; Software Engineering.

 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. 

 Introduction -- Preliminaries and Related Work -- General Concepts of Tree-Based Convolutional Neural Networks (TBCNNs) -- TBCNN for Programs' Abstract Syntax Trees (ASTs) -- TBCNN for Constituency Trees in Natural Language Processing -- TBCNN for Dependency Trees in Natural Language Processing -- Concluding Remarks.