Extraction of aspects from Online Reviews Using a Convolution Neural Network

Authors

  • Kamma Vidya Department of Computer Science and Engineering, KoneruLakshmaiah Education Foundation, Vaddeswaram, A.P., India. & Assistant Professor, Department of Computer Science, Neil Gogte Institute of Technology.
  • Gutta Sridevi KoneruLakshmaiah Education Foundation, Vaddeswaram, A.P., India
  • Dandibhotla Teja Santosh Sreenidhi Institute of Science and Technology, Yamnampet, Ghatkesar, Telangana, India

DOI:

https://doi.org/10.23755/rm.v44i0.909

Keywords:

Neural network, softmax function and extraction

Abstract

The quality of the product is measured based on the opinions gathered from product reviews expressed on a product. Opinion mining deals with extracting the features or aspects from the reviews expressed by the users. Specifically, this model uses a deep convolutional neural network with three channels of input: a semantic word embedding channel that encodes the semantic content of the word, a part of speech tagging channel for sequential labelling and domain embedding channel for domain specific embeddings which is pooled and processed with a Softmax function. This model uses three input channels for aspect extraction. Experiments are conducted on amazon review dataset. This model achieved better results

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Published

2022-12-11

Issue

Vol. 44 (2022): Special Issue: Recent Trends in Mathematics and its Applications

Section

Volume 45-2023

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