id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_caanmurdszbqbhldgzaf4tsziy	Aminu Da'u	Aspect extraction on user textual reviews using multi-channel convolutional neural network	2019	16	.pdf	application/pdf	7315	985	55	Aspect extraction on user textual reviews using multi-channel convolutional neural the performance of the aspect extraction models (Poria, Cambria & Gelbukh, 2016; semantic feature for the aspect extraction, although word embeddings have shown general-purpose word embeddings in aspect extraction. For further improvement, the attention-based model has been used for aspect extraction embeddings method has been used to model aspect extraction using two different embedding features to improve the model performance. channels for better performance of the aspect extraction model. For the POS Tag embeddings, the main idea is to improve the aspect extraction process tag features improves the performance of NLP methods including aspect extraction. attention-based deep learning model for improving aspect extraction is worth exploring, Figure 4 F1 score of the MCNN-WV2-POS Variant of our model on different word embedding Aspect extraction on user textual reviews using multi-channel convolutional neural network Aspect extraction on user textual reviews using multi-channel convolutional neural network	./cache/work_caanmurdszbqbhldgzaf4tsziy.pdf	./txt/work_caanmurdszbqbhldgzaf4tsziy.txt