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20172021
most citedDeep Sentiment Classification and Topic Discovery on Novel Coronavirus or COVID-19 Online Discussions: NLP Using LSTM Recurrent Neural Network Approach

35 citations · 44 across the 5 of their papers we have counts for

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Showing cs.IRShow all

5 papers · 1 filter

cs.IR2020★ 35 cited

Deep Sentiment Classification and Topic Discovery on Novel Coronavirus or COVID-19 Online Discussions: NLP Using LSTM Recurrent Neural Network Approach

Hamed Jelodar, Yongli Wang, Rita Orji +1

Internet forums and public social media, such as online healthcare forums, provide a convenient channel for users (people/patients) concerned about health issues to discuss and sha…

cs.IR2019

Natural Language Processing via LDA Topic Model in Recommendation Systems

Hamed Jelodar, Yongli Wang, Mahdi Rabbani +1

Today, Internet is one of the widest available media worldwide. Recommendation systems are increasingly being used in various applications such as movie recommendation, mobile reco…

cs.IR2018

Recommendation System based on Semantic Scholar Mining and Topic modeling: A behavioral analysis of researchers from six conferences

Hamed Jelodar, Yongli Wang, Mahdi Rabbani +4

Recommendation systems have an important place to help online users in the internet society. Recommendation Systems in computer science are of very practical use these days in vari…

cs.IR2017★ 4 cited

A systematic framework to discover pattern for web spam classification

Hamed Jelodar, Yongli Wang, Chi Yuan +1

Web spam is a big problem for search engine users in World Wide Web. They use deceptive techniques to achieve high rankings. Although many researchers have presented the different…

cs.IR2017

Latent Dirichlet Allocation (LDA) and Topic modeling: models, applications, a survey

Hamed Jelodar, Yongli Wang, Chi Yuan +4

Topic modeling is one of the most powerful techniques in text mining for data mining, latent data discovery, and finding relationships among data, text documents. Researchers have…