Computing Analysis of Zagreb Indices for Generalized Sum Graphs under Strong Product by Muhammad Javaid, Saira Javed, Abdulaziz Mohammed Alanazi, Majdah R. Alotaibi

“…Moreover, the obtained results are illustrated with the help of particular classes of graphs and analysed to find the efficient subclass with dominant indices.…”
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An Explainable Model Using Graph-Wavelet for Predicting Biophysical Properties of Proteins and Measuring Mutational Effects by Shreya Mishra, Neetesh Pandey, Atul Rawat, Divyanshu Srivastava, Arjun Ray, Vibhor Kumar

“…Proteins hold multispectral patterns of different kinds of physicochemical features of amino acids in their structures, which can help understand proteins’ behavior. Here, we propose a method based on the graph-wavelet transform of signals of features of amino acids in protein residue networks derived from their structures to achieve their abstract numerical representations. …”
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Research on recommendation system based on knowledge graph and large language model enhancement by WANG Min, GAO Xiaoying, WANG Shirui, XIANG Yang

“…The core of recommendation system is user and commodity, the relationship between user and commodity can be abstracted as graph structure, so graph neural network has been widely used in recommendation field. …”
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Leveraging Attribute Interaction and Self-Training for Graph Alignment via Optimal Transport by Songyang Chen, Youfang Lin, Ziyuan Zeng, Mengyang Xue

“…Unsupervised alignment of two attributed graphs finds the node correspondence between them without any known anchor links. …”
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Swamped with Too Many Articles? GraphRAG Makes Getting Started Easy by Joëd Ngangmeni, Danda B. Rawat

“…Methods: Using only abstracts and titles of research articles, we compare three retrieval methods—Bibliographic Indexing/Databasing (BI/D), Retrieval-Augmented Generation (RAG), and Graph Retrieval-Augmented Generation (GraphRAG)—which reportedly offer promising solutions to these common challenges. …”
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Knowledge Graph Representation Learning Model Based on Capsule Network and Information Fusion by Chu Zhao, Gilja So, Rui Chen

“…Based on anchor node and neighbor node and the relational sampling strategy, each node on the knowledge graph is represented by the predicted operator graph. …”
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Load aggregator adjustable capability forecasting based on graph convolution neural network by DONG Lingrui, WU Binyuan

“…Based on GCN, the forecasting problem is transformed into the regression problem of point characteristics on the graph. Through the message transmission process on the graph, the response characteristics of different clusters could be shared, and both the historical data of the targeted node and other nodes are effectively used to improve the prediction accuracy from both spatial and temporal aspects. …”
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Multiple Solutions of Fractional Kazdan–Warner Equation for Negative Case on Finite Graphs by Liang Shan, Yang Liu

“…We derive the solvability characteristics of the above equation with the help of variational theory and the upper and lower solutions method.…”
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Regional Heatwave Prediction Using Graph Neural Network and Weather Station Data by Peiyuan Li, Yin Yu, Daning Huang, Zhi‐Hua Wang, Ashish Sharma

“…In addition, its interpretable structure unravels the spatiotemporal patterns of regional heatwaves and helps to enrich our understanding of the general climate dynamics and the causal influences between locations. …”
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Dynamic Graph-Based Clustering for Non-Stationary Spatio-Temporal Event Prediction by Vasavi M., Murugan A., Sharma K. Venkatesh

“…Representation of Graph gives us the crime data analysis with location wise and helps us to predict the next occurrence instance. …”
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Exploration of Word Embeddings with Graph-Based Context Adaptation for Enhanced Word Vectors by Tanvi Sandhu, Ziad Kobti

“…Arranging words that are similar in meaning close to each other in the vectorized representation helps improve how well the system performs in different Natural Language Processing related tasks. …”
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YOLO-Type Neural Networks in the Process of Adapting Mathematical Graphs to the Needs of the Blind by Mateusz Kawulok, Michał Maćkowski

“…It also helped to point out further potential developments in adapting graphs to accessible forms for blind people. …”
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Overlapping Community Detection in Vehicular Social Networks Based on Graph Attention Autoencoder by Xiang Gu, Qiwei Huang, Jie Yang

“…Community detection is particularly important in vehicular social networks because it helps identify closely connected groups of vehicles within the network. …”
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Tourist attraction recommendation method combining graph attention network and clustering algorithm by Jiahua Xiang, Ziyan Xiang

“…Research has shown that tourist attraction recommendation methods based on graph attention networks can accurately recommend attractions based on user interests. …”
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Research on the construction and application of problem-method-oriented academic graph empowered by LLM by Qigang Liu, Yinfan Wang, Lifeng Mu, Jun Li

“…The Q&A system supported by the proposed graph demonstrates that our graph is really helpful for conducting literature review.…”
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An Explainable Graph Neural Framework to Identify Cancer‐Associated Intratumoral Microbial Communities by Zhaoqian Liu, Yuhan Sun, Yingjie Li, Anjun Ma, Nyelia F. Willaims, Shiva Jahanbahkshi, Rebecca Hoyd, Xiaoying Wang, Shiqi Zhang, Jiangjiang Zhu, Dong Xu, Daniel Spakowicz, Qin Ma, Bingqiang Liu

“…Source tracking analysis reveals that the primary known contributor to a cancer‐associated microbial community is the organs affected by the type of cancer. Overall, this graph neural network framework refines the number of microbes that can be used for follow‐up experimental validation from thousands to tens, thereby helping to accelerate the understanding of the relationship between tumors and intratumoral microbiomes.…”
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A clustering-based approach for classifying data streams using graph matching by Yuxin Du, Mingshu He, Xiaojuan Wang

“…Next, the correlation between clusters from the same network is used to construct a similarity graph. Finally, a graph matching algorithm is proposed, which combines graph neural networks and graph matching networks to reveal reliable correspondences between different network relationships. …”
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A graph-based optimization framework for firebreak planning in wildfire-prone landscapes by Denys Yemshanov, Ning Liu, Eric W. Neilson, Daniel Thompson, Frank H. Koch

“…The firebreak solutions were effectively able to reduce both the potential burn area and the connectivity between locations with fuel. The graph-based depiction of the uncertain wildfire spread helped assess the landscape-level impacts of local firebreak allocation decisions and uncover the tradeoffs between different firebreak planning strategies. …”
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A Study on m-Polar Interval-Valued Intuitionistic Fuzzy Graphs with Application in Management by Lian Chen, Aysha Khan, Maryam Akhoundi, A. A. Talebi, G. Muhiuddin, S. H. Sadati

“…Interval-valued intuitionistic fuzzy graphs (IVIFGs) have many fields of work in other sciences, including psychology, life sciences, medicine, and social studies, and can help researchers with optimization and save time and money. …”
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Data Checking of Asymmetric Catalysis Literature Using a Graph Neural Network Approach by Eduardo Aguilar-Bejarano, Viraj Deorukhkar, Simon Woodward

“…The size of chemical databases can make manual data curation/checking of such sets time consuming; thus, automated tools to help this process are highly desirable. Herein, we propose the use of Graph Neural Networks (GNNs) to identifying potential stereochemical misassignments in the primary asymmetric catalysis literature. …”
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