Results 1 to 10 of about 16,154 (230)

Enhanced Sentiment Intensity Regression Through LoRA Fine-Tuning on Llama 3

IEEE Access
Sentiment analysis and emotion detection are critical research areas in natural language processing (NLP), offering benefits to numerous downstream tasks.
Diefan Lin, Yi Wen, Weishi Wang, Yan Su
doaj   +1 more source

A New Sentiment-Enhanced Word Embedding Method for Sentiment Analysis

Applied Sciences, 2022
Since some sentiment words have similar syntactic and semantic features in the corpus, existing pre-trained word embeddings always perform poorly in sentiment analysis tasks.
Qizhi Li, Xianyong Li, Yajun Du, Yongquan Fan, Xiaoliang Chen   +4 more
doaj   +1 more source

OhioState at SemEval-2018 Task 7: Exploiting Data Augmentation for Relation Classification in Scientific Papers using Piecewise Convolutional Neural Networks

, 2018
We describe our system for SemEval-2018 Shared Task on Semantic Relation Extraction and Classification in Scientific Papers where we focus on the Classification task.
Dhyani, Dushyanta
core   +1 more source

Multi-prompt Learning Based Aspect-Category Sentiment Analysis [PDF]

Jisuanji kexue yu tansuo
Aspect-category sentiment analysis (ACSA) aims to discern aspect categories in review texts and simultaneously predict their sentiment polarity. It is an important fine-grained subtask in the field of sentiment analysis.
LIU Jinhang, LI Lin, WU Renwei, LIU Jia
doaj   +1 more source

What Matters in Irony Detection: An Extended Feature Engineering for Irony Detection in English Tweets.

Proceedings of the International Florida Artificial Intelligence Research Society Conference
In recent years, large-scale language models (LLMs) have nearly become the dominant force in almost every natural language processing (NLP) task. The primary research approach has focused on selecting the most appropriate language model for specific NLP ...
Linrui Zhang, Qixiang Pang, Belinda Copus   +2 more
doaj   +1 more source

Modern Approaches to Aspect-Based Sentiment Analysis

Труды Института системного программирования РАН, 2018
The paper presents a survey of methods solving the actual task of aspect-based sentiment analysis. Solutions for this task were proposed at multiple natural language processing conferences.
I. . Andrianov, V. . Mayorov, D. . Turdakov   +2 more
doaj   +1 more source

Robust Incremental Neural Semantic Graph Parsing

, 2017
Parsing sentences to linguistically-expressive semantic representations is a key goal of Natural Language Processing. Yet statistical parsing has focused almost exclusively on bilexical dependencies or domain-specific logical forms.
Blunsom, Phil, Buys, Jan
core   +1 more source

Query-Based Keyphrase Extraction from Long Documents

Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022
Transformer-based architectures in natural language processing force input size limits that can be problematic when long documents need to be processed. This paper overcomes this issue for keyphrase extraction by chunking the long documents while keeping
Martin Dočekal, Pavel Smrž
doaj   +1 more source

Improving Multi-Label Emotion Classification on Imbalanced Social Media Data With BERT and Clipped Asymmetric Loss

IEEE Access
This research addresses the challenge of multi-label emotion classification on imbalanced datasets using a BERT-based model. Emotion classification, essential for applications like social media analysis and sentiment monitoring, often suffers from class ...
Sandhya Ramakrishnan, L. D. Dhinesh Babu
doaj   +1 more source

ShotgunWSD 2.0: An Improved Algorithm for Global Word Sense Disambiguation

IEEE Access, 2019
ShotgunWSD is a recent unsupervised and knowledge-based algorithm for global word sense disambiguation (WSD). The algorithm is inspired by the Shotgun sequencing technique, which is a broadly-used whole genome sequencing approach. ShotgunWSD performs WSD
Andrei M. Butnaru, Radu Tudor Ionescu
doaj   +1 more source