paper-with-me

홈 › Papers

Structured Citation Trend Prediction Using Graph Neural Networks

2021-04-06 · Daniel Cummings, Marcel Nassar

Academic citation graphs represent citation relationships between publications across the full range of academic fields. Top cited papers typically reveal future trends in their corresponding domains which is of importance to both researchers and practitioners. Prior citation prediction methods often require initial citation trends to be established and do not take advantage of the recent advancements in graph neural networks (GNNs). We present GNN-based architecture that predicts the top set of papers at the time of publication. For experiments, we curate a set of academic citation graphs for a variety of conferences and show that the proposed model outperforms other classic machine learning models in terms of the F1-score.

📄 PDF Abstract BibTeX arXiv:2104.02562

Code (0)

등록된 구현이 없습니다.

Tasks

BIG-bench Machine LearningCitation PredictionPrediction

Similar Papers 제목 키워드 기반

Modeling Dynamic Heterogeneous Graph and Node Importance for Future Citation Prediction

2023-05-27 · Hao Geng, Deqing Wang, Fuzhen Zhuang, Xuehua Ming 외

Accurate citation count prediction of newly published papers could help editors and readers rapidly figure out the influential papers in the future. Though many approaches are proposed to predict a paper's future citatio…

Citation PredictionNetwork Embedding

Longitudinal Citation Prediction using Temporal Graph Neural Networks

2020-12-10 · Andreas Nugaard Holm, Barbara Plank, Dustin Wright, Isabelle Augenstein

Citation count prediction is the task of predicting the number of citations a paper has gained after a period of time. Prior work viewed this as a static prediction task. As papers and their citations evolve over time, c…

Citation PredictionPrediction

MIRAI: Prediction and Generation of High-Impact Academic Research

2026-06-03 · Alex Li, Joseph Jacobson arxiv

The rapid pace of scientific publishing has made the identification and synthesis of high-impact work an increasingly urgent challenge. We introduce MIRAI (Multi-year Inference of Research trends and Academic Impact), a …

Variational Graph Auto-Encoders

2016-11-21 · Thomas N. Kipf, Max Welling

We introduce the variational graph auto-encoder (VGAE), a framework for unsupervised learning on graph-structured data based on the variational auto-encoder (VAE). This model makes use of latent variables and is capable …

DecoderGraph ClusteringLink PredictionPrediction

Proof of Reference(PoR): A unified informetrics based consensus mechanism

2021-07-01 · Parul Khurana, Geetha Ganesan, Gulshan Kumar, Kiran Sharma

Bibliometrics is useful to analyze the research impact for measuring the research quality. Different bibliographic databases like Scopus, Web of Science, Google Scholar etc. are accessed for evaluating the trend of publi…