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A survey on text classification: From traditional to deep learning
Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …
processing. The last decade has seen a surge of research in this area due to the …
A survey on text classification: From shallow to deep learning
Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …
processing. The last decade has seen a surge of research in this area due to the …
Short text topic modelling approaches in the context of big data: taxonomy, survey, and analysis
Social media platforms such as (Twitter, Facebook, and Weibo) are being increasingly
embraced by individuals, groups, and organizations as a valuable source of information …
embraced by individuals, groups, and organizations as a valuable source of information …
Large language models are zero-shot text classifiers
Retrained large language models (LLMs) have become extensively used across various sub-
disciplines of natural language processing (NLP). In NLP, text classification problems have …
disciplines of natural language processing (NLP). In NLP, text classification problems have …
A hierarchical recommendation system for E-commerce using online user reviews
Recommendation systems are considered as one of the important components of e-
commerce platforms due to their direct impact on profitability. In this study, we propose a …
commerce platforms due to their direct impact on profitability. In this study, we propose a …
Cgraphnet: Contrastive graph context prediction for sparse unlabeled short text representation learning on social media
Unlabeled text representation learning (UTRL), encompassing static word embeddings such
as Word2Vec and contextualized word embeddings such as bidirectional encoder …
as Word2Vec and contextualized word embeddings such as bidirectional encoder …
Zero-shot micro-video classification with neural variational inference in graph prototype network
Micro-video classification plays a central role in online content recommendation platforms,
such as Kwai and Tik-Tok. Existing works on video classification largely exploit the …
such as Kwai and Tik-Tok. Existing works on video classification largely exploit the …
Dynamic evolutionary data and text document clustering approach using improved Aquila optimizer based arithmetic optimization algorithm and differential evolution
Data and text clustering are popular and frequently used in the data mining domain, mainly
to deal with big data analytics. The main problem in these techniques is finding the most …
to deal with big data analytics. The main problem in these techniques is finding the most …
A context-enhanced Dirichlet model for online clustering in short text streams
Online clustering of short text streams has become significant due to the popularity of news
and social media platforms. The objective of online clustering is to maintain active topics …
and social media platforms. The objective of online clustering is to maintain active topics …
Recent methods on short text stream clustering: A survey study
E Maden, P Karagoz - Wiley Interdisciplinary Reviews …, 2023 - Wiley Online Library
The volume and the velocity of data in social media are increasing and the social media has
become a very useful environment to detect and track the real‐world events. However, to …
become a very useful environment to detect and track the real‐world events. However, to …