Short Text Classification
Related Papers
Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks
Recent approaches based on artificial neural networks (ANNs) have shown promising re- sults for short-text classification. However, many short texts occur in sequences (e.g., sen- tences in a document or …...
Solving Feature Sparseness in Text Classification using Core-Periphery Decomposition
AbstractFeature sparseness is a problem common to cross-domain and short-text classification tasks. To overcome this feature sparseness problem, we propose a novel method based on graph decomposition to find candidate …...
Turkish Tweet Classification with Transformer Encoder
AbstractShort-text classification is a challenging task, due to the sparsity and high dimensionality of the feature space. In this study, we aim to analyze and classify Turkish tweets based on …...
Hierarchical Heterogeneous Graph Representation Learning for Short Text Classification
AbstractShort text classification is a fundamental task in natural language processing. It is hard due to the lack of context information and labeled data in practice. In this paper, we …...
ProFormer: Towards On-Device LSH Projection Based Transformers
AbstractAt the heart of text based neural models lay word representations, which are powerful but occupy a lot of memory making it challenging to deploy to devices with memory constraints …...
Linguistically Motivated Features for Classifying Shorter Text into Fiction and Non-Fiction Genre
AbstractThis work deploys linguistically motivated features to classify paragraph-level text into fiction and non-fiction genre using a logistic regression model and infers lexical and syntactic properties that distinguish the two …...
Simplified Graph Learning for Inductive Short Text Classification
AbstractShort text classification (STC) is hard as short texts lack context information and labeled data is not enough. Graph neural networks obtain the state-of-the-art on STC since they can merge …...