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💪 Relational Graph Convolutional Networks for Sentiment Analysis
#computerscience

Relational Graph Convolutional Networks for Sentiment Analysis
With the growth of textual data across online platforms, sentiment analysis has become crucial for extracting insights from user-generated content. While traditional approaches and deep learning models have shown promise, they cannot often capture complex relationships between entities. In this paper, we propose leveraging Relational Graph Convolutional Networks (RGCNs) for sentiment analysis, which offer interpretability and flexibility by capturing dependencies between data points represented…

Dynamical systems of an infinite-dimensional non-linear operator
U. R. Olimov, U. A. Rozikov
https://arxiv.org/abs/2402.15479 https://

Dynamical systems of an infinite-dimensional non-linear operator
We investigate discrete-time dynamical systems generated by an infinite-dimensional non-linear operator that maps the Banach space $l_1$ to itself. It is demonstrated that this operator possesses up to seven fixed points. By leveraging the specific form of our operator, we illustrate that analyzing the operator can be simplified to a two-dimensional approach. Subsequently, we provide a detailed description of all fixed points, invariant sets for the two-dimensional operator and determine the se…