Learning Document Semantic Representation with Hybrid Deep Belief Network
Joint Authors
Yan, Yan
Yin, Xu-Cheng
Li, Sujian
Yang, Mingyuan
Hao, Hong-Wei
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-23
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
High-level abstraction, for example, semantic representation, is vital for document classification and retrieval.
However, how to learn document semantic representation is still a topic open for discussion in information retrieval and natural language processing.
In this paper, we propose a new Hybrid Deep Belief Network (HDBN) which uses Deep Boltzmann Machine (DBM) on the lower layers together with Deep Belief Network (DBN) on the upper layers.
The advantage of DBM is that it employs undirected connection when training weight parameters which can be used to sample the states of nodes on each layer more successfully andit is also an effective way to remove noise from the different document representation type; the DBN can enhance extract abstract of the document in depth, making the model learn sufficient semantic representation.
At the same time, we explore different input strategies for semantic distributed representation.
Experimental results show that our model using the word embedding instead of single word has better performance.
American Psychological Association (APA)
Yan, Yan& Yin, Xu-Cheng& Li, Sujian& Yang, Mingyuan& Hao, Hong-Wei. 2015. Learning Document Semantic Representation with Hybrid Deep Belief Network. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1057730
Modern Language Association (MLA)
Yan, Yan…[et al.]. Learning Document Semantic Representation with Hybrid Deep Belief Network. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1057730
American Medical Association (AMA)
Yan, Yan& Yin, Xu-Cheng& Li, Sujian& Yang, Mingyuan& Hao, Hong-Wei. Learning Document Semantic Representation with Hybrid Deep Belief Network. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1057730
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057730