1 citations · 1 across the 13 of their papers we have counts for
13 papers
Topic model based on co-occurrence word networks for unbalanced short text datasets
Chengjie Ma, Junping Du, Meiyu Liang +1
We propose a straightforward solution for detecting scarce topics in unbalanced short-text datasets. Our approach, named CWUTM (Topic model based on co-occurrence word networks for…
Federated Topic Model and Model Pruning Based on Variational Autoencoder
Chengjie Ma, Yawen Li, Meiyu Liang +1
Topic modeling has emerged as a valuable tool for discovering patterns and topics within large collections of documents. However, when cross-analysis involves multiple parties, dat…
Semantic Representation Learning of Scientific Literature based on Adaptive Feature and Graph Neural Network
Hongrui Gao, Yawen Li, Meiyu Liang +2
Because most scientific literature data are unlabeled, semantic representation learning based on unsupervised graphs has become crucial. To enrich scientific-literature features, t…
Cross-modal Search Method of Technology Video based on Adversarial Learning and Feature Fusion
Xiangbin Liu, Junping Du, Meiyu Liang +1
Technology videos contain rich multi-modal information. In cross-modal information search, the data features of different modalities cannot be compared directly, so the semantic ga…
Embedding Representation of Academic Heterogeneous Information Networks Based on Federated Learning
Junfu Wang, Yawen Li, Meiyu Liang +1
Academic networks in the real world can usually be portrayed as heterogeneous information networks (HINs) with multi-type, universally connected nodes and multi-relationships. Some…
Unsupervised Semantic Representation Learning of Scientific Literature Based on Graph Attention Mechanism and Maximum Mutual Information
Hongrui Gao, Yawen Li, Meiyu Liang +1
Since most scientific literature data are unlabeled, this makes unsupervised graph-based semantic representation learning crucial. Therefore, an unsupervised semantic representatio…
Research on accurate stereo portrait generation algorithm of scientific research team
Mingying Xu, Junping DU, Meiyu Liang +2
In order to smoothly promote the establishment of scientific research projects, accurately identify the excellent scientific research team, and intuitively and comprehensively desc…
Cross-media Scientific Research Achievements Query based on Ranking Learning
Benzhi Wang, Meiyu Liang, Ang Li
With the advent of the information age, the scale of data on the Internet is getting larger and larger, and it is full of text, images, videos, and other information. Different fro…
Mining and searching association relation of scientific papers based on deep learning
Jie Song, Meiyu Liang, Zhe Xue +2
There is a complex correlation among the data of scientific papers. The phenomenon reveals the data characteristics, laws, and correlations contained in the data of scientific and…
Research on Domain Information Mining and Theme Evolution of Scientific Papers
Changwei Zheng, Zhe Xue, Meiyu Liang +2
In recent years, with the increase of social investment in scientific research, the number of research results in various fields has increased significantly. Cross-disciplinary res…
An unsupervised cluster-level based method for learning node representations of heterogeneous graphs in scientific papers
Jie Song, Meiyu Liang, Zhe Xue +2
Learning knowledge representation of scientific paper data is a problem to be solved, and how to learn the representation of paper nodes in scientific paper heterogeneous network i…
Research topic trend prediction of scientific papers based on spatial enhancement and dynamic graph convolution network
Changwei Zheng, Zhe Xue, Meiyu Liang +1
In recent years, with the increase of social investment in scientific research, the number of research results in various fields has increased significantly. Accurately and effecti…
Cross-Media Scientific Research Achievements Retrieval Based on Deep Language Model
Benzhi Wang, Meiyu Liang, Feifei Kou +1
Science and technology big data contain a lot of cross-media information.There are images and texts in the scientific paper.The s ingle modal search method cannot well meet the nee…