A scientific research topic trend prediction model based on multi‐LSTM and graph convolutional network-Reference-Cited by-同舟云学术

A scientific research topic trend prediction model based on multi‐LSTM and graph convolutional network

Published:2022-02-09 Issue:9 Volume:37 Page:6331-6353
ISSN:0884-8173
Container-title:International Journal of Intelligent Systems
language:en
Short-container-title:Int J of Intelligent Sys

Author:

Xu Mingying¹^ORCID,Du Junping¹^ORCID,Xue Zhe¹^ORCID,Guan Zeli¹^ORCID,Kou Feifei¹^ORCID,Shi Lei²^ORCID

Affiliation:

1. Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia School of Computer Science Beijing University of Posts and Telecommunications Beijing China

2. State Key Laboratory of Media Convergence and Communication Communication University of China Beijing China

Publisher

Hindawi Limited

Subject

Artificial Intelligence,Human-Computer Interaction,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/int.22846

Reference58 articles.

1. Topic-linked innovation paths in science and technology

2. The use of citation context to detect the evolution of research topics: a large-scale analysis

3. An alternative topic model based on Common Interest Authors for topic evolution analysis

4. Understanding the formation of interdisciplinary research from the perspective of keyword evolution: a case study on joint attention

5. Mapping the technology evolution path: a novel model for dynamic topic detection and tracking

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Evolutions of semantic consistency in research topic via contextualized word embedding;Information Processing & Management;2024-11

2. Modeling topic evolution in public opinion events: an unsupervised spatio-temporal graph attention approach;Applied Intelligence;2024-07-22

3. A Triplet Multimodel Transfer Learning Network for Speech Disorder Screening of Parkinson’s Disease;International Journal of Intelligent Systems;2024-03-20

4. Mining technology trends in scientific publications: a graph propagated neural topic modeling approach;Knowledge and Information Systems;2024-01-30

5. Quantitative Analysis of Scholars’ Topic Switching Behavior in Computer Science: A Two- Dimensional Metric Approach;IEEE Access;2024