Sep 15, 2019 · Attention-based bidirectional long short-term network. (BiLSTM) models have recently shown promising results in text classification tasks.

This paper describes methods of improving the performance of a new pneumatic classifier based on the rapid classification principle.

Dec 2, 2020 · A practical exploration of the Natural Language Processing technique of Latent Dirichlet Allocation and its application to the task of topic modeling.

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Sep 10, 2024 · By employing our LDA filtering technique, we were able to significantly improve LSTM's performance, achieving an impressive accuracy rate of 92% ...

This paper proposes an unsupervised meta-embedding method that jointly models background knowledge from the source embeddings and domain-specific knowledge ...

Jun 24, 2024 · LDA is a probabilistic generative model that analyzes documents to discover latent topics and themes that are present across a collection of texts.

The learned embeddings also capture topic characteris- tics with input points corresponding to the same latent topic placed together. To validate this, we ...

Cross-domain data analysis is playing an increasingly important role in media convergence and can be adopted for many applications.

Jul 1, 2021 · The authors investigate the problem task of multi-source cross-domain sentiment classification under the constraint of little labeled data.