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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 …
A decade of in-text citation analysis based on natural language processing and machine learning techniques: an overview of empirical studies
In-text citation analysis is one of the most frequently used methods in research evaluation.
We are seeing significant growth in citation analysis through bibliometric metadata, primarily …
We are seeing significant growth in citation analysis through bibliometric metadata, primarily …
An LSTM short-term solar irradiance forecasting under complicated weather conditions
Y Yu, J Cao, J Zhu - IEEE Access, 2019 - ieeexplore.ieee.org
Complicated weather conditions lead to intermittent, random and volatility in photovoltaic
(PV) systems, which makes PV predictions difficult. A recurrent neural network (RNN) is …
(PV) systems, which makes PV predictions difficult. A recurrent neural network (RNN) is …
A context-aware citation recommendation model with BERT and graph convolutional networks
With the tremendous growth in the number of scientific papers being published, searching
for references while writing a scientific paper is a time-consuming process. A technique that …
for references while writing a scientific paper is a time-consuming process. A technique that …
CiteME: Can Language Models Accurately Cite Scientific Claims?
Thousands of new scientific papers are published each month. Such information overload
complicates researcher efforts to stay current with the state-of-the-art as well as to verify and …
complicates researcher efforts to stay current with the state-of-the-art as well as to verify 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 …
A robust auto encoder-gated recurrent unit (AE-GRU) based deep learning approach for short term solar power forecasting
The increasing presence of solar power plants shows its potency as one of the key
renewable energy resource to fulfill energy needs of the community. This increasing …
renewable energy resource to fulfill energy needs of the community. This increasing …
[HTML][HTML] Semantics aware intelligent framework for content-based e-learning recommendation
E-learning accounts for the emergence of re-skilling, up-skilling, and augmenting the
traditional education system by providing knowledge delivery. The meaningful learning …
traditional education system by providing knowledge delivery. The meaningful learning …
Global citation recommendation employing generative adversarial network
The variety and plethora of research papers available on the Web motivated researchers to
propose models that could assist users with personalized citation recommendations. In …
propose models that could assist users with personalized citation recommendations. In …
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 …