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Found 9 papers, 1 papers with code
Embeddings for Tabular Data: A Survey
The classical learning phase consists of the models such as SVMs, linear and logistic regression, and tree-based methods.
A Survey of Knowledge Graph Embedding and Their Applications
This paper includes the utility of the Knowledge graph in real-world applications.
Twitter corpus of Resource-Scarce Languages for Sentiment Analysis and Multilingual Emoji Prediction
In this paper, we leverage social media platforms such as twitter for developing corpus across multiple languages.
Cross-Lingual Task-Specific Representation Learning for Text Classification in Resource Poor Languages
The model learns the representation of resource-poor and resource-rich sentences in a common space by using the similarity between their assigned annotation tags.
Contrastive Learning of Emoji-based Representations for Resource-Poor Languages
The model learns the representations of resource-poor and resource-rich language in a common emoji space by using a similarity metric based on the emojis present in sentences from both languages.
Automatic Normalization of Word Variations in Code-Mixed Social Media Text
Social media platforms such as Twitter and Facebook are becoming popular in multilingual societies.
Emotions are Universal: Learning Sentiment Based Representations of Resource-Poor Languages using Siamese Networks
Machine learning approaches in sentiment analysis principally rely on the abundance of resources.
Sentiment Analysis of Code-Mixed Languages leveraging Resource Rich Languages
Code-mixed data is an important challenge of natural language processing because its characteristics completely vary from the traditional structures of standard languages.
Neural Network Architecture for Credibility Assessment of Textual Claims
CREDO consists of different modules for capturing various features responsible for the credibility of an article.
