Aspect extraction on user textual reviews using multi-channel convolutional neural network.

ABSTRACT: Aspect extraction is a subtask of sentiment analysis that deals with identifying opinion targets in an opinionated text. Existing approaches to aspect extraction typically rely on using handcrafted features, linear and integrated network architectures. Although these methods can achieve good performances, they are time-consuming and often very complicated. In real-life systems, a simple model with competitive results is generally more effective and preferable over complicated models. In this paper, we present a multichannel convolutional neural network for aspect extraction. The model consists of a deep convolutional neural network with two input channels: a word embedding channel which aims to encode semantic information of the words and a part of speech (POS) tag embedding channel to fac

SUBMITTER: Da'u A 

PROVIDER: S-EPMC7924670 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature