Jan 15, 2022 · In this paper, we present a GCN-based clustering method for short text clustering, named as Deep Structured Clustering (DSC) method, to explore ...
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Short text clustering is beneficial in many applications such as articles recommendations, user clustering and event exploration. Recent works of short text ...
Abstract. Driven by recent advances in neural networks, various Deep Embedding Clustering (DEC) based short text clustering models are being developed.
Jan 5, 2024 · Text clustering is the task of grouping text data based on similarity, and it holds particular importance in the medical field.
This paper studies the model construction and sentiment analysis based on BL_CNN, gives the mathematical model and training algorithm of deep learning,
This study focuses on STC techniques: text clustering, challenges to short texts, pre-processing, document representation, dimensionality reduction, similarity ...
Mar 24, 2024 · Text clustering involves grouping a set of texts so that texts in the same group (referred to as a cluster) are more similar to each other than ...
Trained representations from the CNN are clustered using the k-means algorithm. Two re- cent surveys provide an overview of research on deep clustering methods ...
In this paper, we propose a deep feature-based text clustering (DFTC) framework that incorporates pretrained text encoders into text clustering tasks.
Jan 11, 2024 · Short text clustering is an important issue in text mining and aims to group short texts with similar topics or semantics into the same cluster.