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Found 10 papers, 4 papers with code
Opinion-based Relational Pivoting for Cross-domain Aspect Term Extraction
In this paper, we investigate and establish empirically a prior conjecture, which suggests that the linguistic relations connecting opinion terms to their aspects transfer well across domains and therefore can be leveraged for cross-domain aspect term extraction.
Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs
The extraction of aspect terms is a critical step in fine-grained sentiment analysis of text.
Efficient Few-Shot Learning Without Prompts
This simple framework requires no prompts or verbalizers, and achieves high accuracy with orders of magnitude less parameters than existing techniques.
InterpreT: An Interactive Visualization Tool for Interpreting Transformers
With the increasingly widespread use of Transformer-based models for NLU/NLP tasks, there is growing interest in understanding the inner workings of these models, why they are so effective at a wide range of tasks, and how they can be further tuned and improved.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
Syntactically Aware Cross-Domain Aspect and Opinion Terms Extraction
A fundamental task of fine-grained sentiment analysis is aspect and opinion terms extraction.
3D Neural Network for Lung Cancer Risk Prediction on CT Volumes
Reducing the high error rates in lung cancer screening is imperative because of the high clinical and financial costs caused by diagnosis mistakes.
ABSApp: A Portable Weakly-Supervised Aspect-Based Sentiment Extraction System
We present ABSApp, a portable system for weakly-supervised aspect-based sentiment extraction.
Term Set Expansion based NLP Architect by Intel AI Lab
We present SetExpander, a corpus-based system for expanding a seed set of terms into amore complete set of terms that belong to the same semantic class.
SetExpander: End-to-end Term Set Expansion Based on Multi-Context Term Embeddings
We present SetExpander, a corpus-based system for expanding a seed set of terms into a more complete set of terms that belong to the same semantic class.
Term Set Expansion based on Multi-Context Term Embeddings: an End-to-end Workflow
We present SetExpander, a corpus-based system for expanding a seed set of terms into a more complete set of terms that belong to the same semantic class.
