DSpace logo

Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16394
Title: Composite Sequential Modeling for Identifying Fake Reviews
Authors: Sharma, Yashvardhan
Keywords: Computer Science
Spam detection
Deep Learning (DL)
Machine learning (ML)
Fake reviews
Issue Date: Apr-2018
Publisher: De Gruyter
Abstract: This paper presents a comprehensive analysis and comparison of various proposed sequential models based on different deep networks such as the convolutional neural network, long short-term memory, and recurrent neural network. The different sequential models are analyzed based on the number of layers, the number of output dimensions, order, and the combination of different deep network architectures. The proposed approach is compared to a baseline model based on traditional machine learning techniques.
URI: https://www.degruyter.com/document/doi/10.1515/jisys-2017-0501/html
http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16394
Appears in Collections:Department of Computer Science and Information Systems

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.