An integrated clustering and BERT framework for improved topic modeling [0.03%]
一种改进主题模型的集成聚类和BERT框架
Lijimol George,P Sumathy
Lijimol George
Topic modelling is a machine learning technique that is extensively used in Natural Language Processing (NLP) applications to infer topics within unstructured textual data. Latent Dirichlet Allocation (LDA) is one of the most used topic mod...
A two-staged NLP-based framework for assessing the sentiments on Indian supreme court judgments [0.03%]
基于NLP的两阶段框架在印度最高法院判决中评估情感状态
Isha Gupta,Indranath Chatterjee,Neha Gupta
Isha Gupta
Topic modeling is a powerful technique for uncovering hidden patterns in large documents. It can identify themes that are highly connected and lead to a certain region while accounting for temporal and spatial complexity. In addition, senti...
Rajesh Singh,Sumeet Saurav,Tarun Kumar et al.
Rajesh Singh et al.
The three-dimensional convolutional neural network (3D-CNN) and long short-term memory (LSTM) have consistently outperformed many approaches in video-based facial expression recognition (VFER). The image is unrolled to a one-dimensional vec...
Technology enabled communication during COVID 19: analysis of tweets from top ten Indian IT companies using NVIVO [0.03%]
基于NVIVO的印度十大IT公司的COVID-19期间沟通内容分析
Swati Chawla,Puja Sareen,Sangeeta Gupta et al.
Swati Chawla et al.
The corona virus (COVID-19) pandemic has impacted industries across the globe. Lockdown was imposed to curb the spread of the deadly virus. This resulted in closure of the factories and manufacturing units. Few sectors switched to work from...
A novel centroid based sentence classification approach for extractive summarization of COVID-19 news reports [0.03%]
一种基于向量中心的句子分类方法，用于COVID-19新闻报道的提取摘要
Sumanta Banerjee,Shyamapada Mukherjee,Sivaji Bandyopadhyay
Sumanta Banerjee
A COVID-19 news covers subtopics like infections, deaths, the economy, jobs, and more. The proposed method generates a news summary based on the subtopics of a reader's interest. It extracts a centroid having the lexical pattern of the sent...
Closed-set automatic speaker identification using multi-scale recurrent networks in non-native children [0.03%]
基于多尺度循环网络的非英语国家儿童说话人识别研究
Kodali Radha,Mohan Bansal
Kodali Radha
Children may benefit from automatic speaker identification in a variety of applications, including child security, safety, and education. The key focus of this study is to develop a closed-set child speaker identification system for non-nat...
The moderating role of trust in government adoption e-service during Covid-19 pandemic: health belief model perspective [0.03%]
政府信任在新冠肺炎疫情期间采纳医疗电子服务的调节作用：健康信念模型视角
Dony Martinus Sihotang,Muhammad Raihan Andriqa,Futuh Nurmuntaha Alfahmi et al.
Dony Martinus Sihotang et al.
The present paper discusses the influence of factors in the health belief model (HBM) on adopting government e-services during the Covid-19 pandemic in Indonesia. Furthermore, the present study demonstrates the moderating effect of trust in...
K Aditya Shastry,Sheik Abdul Sattar
K Aditya Shastry
Alzheimer's disease (AD) is a common and well-known neurodegenerative condition that causes cognitive impairment. In the field of medicine, it is the "nervous system" disorder that has received the most attention. Despite this extensive res...