Department of Computer Science and Telecommunication Engineering, Jiangsu University, Jiangsu, China
Research Article
Solicitation of Knowledge Graph Enhanced Neural Network Objects Detection by Sentiment Analysis
Author(s): Yacouba Conde* and Zhoulianying
In the machine learning technique, the knowledge graph is advancing swiftly; however, the basic models are not able to grasp all the affluence of the script that comes from the different personal web graphics, social media, ads, and diaries, etc., ignoring the semantic of the basic text identification. The knowledge graph provides a real way to extract structured knowledge from the texts and desire images of neural network, to expedite their semantics examination. In this study, we propose a new hybrid analytic approach for sentiment evaluation based on knowledge graphs, to identify the polarity of sentiment with positive and negative
attitudes in short documents, particularly in 4 chirps. We used the tweets graphs, then the similarity of graph highlighted metrics and algorithm classification pertain sentimentality pre-dictions. This technique facilitates the explicability and cl.. Read More»
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