Extraction of aspects from Online Reviews Using a Convolution Neural Network

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 channe...

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Veröffentlicht in:Ratio mathematica 2022-12, Vol.44, p.213-221
Hauptverfasser: Kamma Vidya, Gutta Sridevi, Dandibhotla, Teja Santosh
Format: Artikel
Sprache:eng
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Zusammenfassung: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
ISSN:1592-7415
2282-8214
DOI:10.23755/rm.v44i0.909