Deep learning in citation recommendation models survey
The huge amount of research papers on the web makes finding a relevant manuscript a
difficult task. In recent years many models were introduced to support researchers by …
difficult task. In recent years many models were introduced to support researchers by …
Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network
Abstract (Aim) COVID-19 is an infectious disease spreading to the world this year. In this
study, we plan to develop an artificial intelligence based tool to diagnose on chest CT …
study, we plan to develop an artificial intelligence based tool to diagnose on chest CT …
Specter: Document-level representation learning using citation-informed transformers
Representation learning is a critical ingredient for natural language processing systems.
Recent Transformer language models like BERT learn powerful textual representations, but …
Recent Transformer language models like BERT learn powerful textual representations, but …
An anatomization of research paper recommender system: Overview, approaches and challenges
The purpose of this study is to present an exhaustive analysis on research paper
recommender systems which have become very popular and gained a lot of research …
recommender systems which have become very popular and gained a lot of research …
VGCN-BERT: augmenting BERT with graph embedding for text classification
Much progress has been made recently on text classification with methods based on neural
networks. In particular, models using attention mechanism such as BERT have shown to …
networks. In particular, models using attention mechanism such as BERT have shown to …
Incorporating medical knowledge in BERT for clinical relation extraction
A Roy, S Pan - Proceedings of the 2021 conference on empirical …, 2021 - aclanthology.org
In recent years pre-trained language models (PLM) such as BERT have proven to be very
effective in diverse NLP tasks such as Information Extraction, Sentiment Analysis and …
effective in diverse NLP tasks such as Information Extraction, Sentiment Analysis and …
Citation recommendation: approaches and datasets
Citation recommendation describes the task of recommending citations for a given text. Due
to the overload of published scientific works in recent years on the one hand, and the need …
to the overload of published scientific works in recent years on the one hand, and the need …
Towards more robust hate speech detection: using social context and user data
In this paper, we present a novel approach to detecting hate speech on Twitter. Our method
incorporates textual, social context and language features of the author to better capture the …
incorporates textual, social context and language features of the author to better capture the …
Citation intent classification using word embedding
Citation analysis is an active area of research for various reasons. So far, statistical
approaches are mainly used for citation analysis, which does not look into the internal …
approaches are mainly used for citation analysis, which does not look into the internal …
Deep learning for patent landscaping using transformer and graph embedding
Patent landscaping is used to search for related patents during research and development
projects. Patent landscaping is a crucial task required during the early stages of an R & D …
projects. Patent landscaping is a crucial task required during the early stages of an R & D …