Deep learning for medication recommendation: a systematic survey
Making medication prescriptions in response to the patient's diagnosis is a challenging task.
The number of pharmaceutical companies, their inventory of medicines, and the …
The number of pharmaceutical companies, their inventory of medicines, and the …
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 …
On the current state of deep learning for news recommendation
The exponential outbreak of news articles makes it troublesome for the readers to find,
select and read the most relevant ones and alleviate the resulting information and cognitive …
select and read the most relevant ones and alleviate the resulting information and cognitive …
Citation recommendation employing heterogeneous bibliographic network embedding
The massive number of research articles on the Web makes it troublesome for researchers
to identify related works that could meet their preferences and interests. Consequently …
to identify related works that could meet their preferences and interests. Consequently …
Mutually reinforced network embedding: An integrated approach to research paper recommendation
With the rapid growth of research publications, it has become time-consuming and
cumbersome for researchers to find research papers relevant to their research. Research …
cumbersome for researchers to find research papers relevant to their research. Research …
RAR-SB: research article recommendation using SciBERT with BiGRU
The wide range and enormous volume of academic papers on the Internet prompted
researchers to recommend models that could provide users with customized academic …
researchers to recommend models that could provide users with customized academic …
RefCit2vec: embedding models considering references and citations for measuring document similarity
C Huang, K Chen - Scientometrics, 2024 - Springer
This study outlines the intellectual structure of Library and Information Science in terms of
the venues with RefCit2vec, an embedding method inspired by word2vec. The reference …
the venues with RefCit2vec, an embedding method inspired by word2vec. The reference …
A scientific paper recommendation method using the time decay heterogeneous graph
Z Huang, D Tang, R Zhao, W Rao - Scientometrics, 2024 - Springer
Finding appropriate and relevant papers about a project in various digital libraries with
millions of scientific papers is challenging for researchers, resulting in a research innovation …
millions of scientific papers is challenging for researchers, resulting in a research innovation …
Paper Retrieval, Summarization and Citation Generation
N Gu - 2023 - research-collection.ethz.ch
In scientific writing, retrieving, summarizing, and citing relevant papers is necessary but
usually time-consuming. Recent research in natural language processing (NLP) has …
usually time-consuming. Recent research in natural language processing (NLP) has …
Dual Cloud Bibliographic Network Model for Citation Recommendation Systems
VA Nurjahan, S Jancy - 2023 Annual International Conference …, 2023 - ieeexplore.ieee.org
Finding relevant and appropriate papers for citation is becoming more and more difficult for
researchers as a result of the exponential growth in the number of scientific papers. To …
researchers as a result of the exponential growth in the number of scientific papers. To …