Topological Data Analysis and Graph-Based Learning for Multimodal Recommendation by Khalil Bachiri, Ali Yahyaouy, Maria Malek, Nicoleta Rogovschi

“…However, current multimodal methods face challenges such as modality heterogeneity, data sparsity, and feature redundancy, which can result in less effective performance when dealing with complex, high-dimensional datasets. In this study, we present a new framework that combines Topological Data Analysis (TDA) with graph-based learning to improve multimodal recommendations (TDA-MMRec). …”
Get full text

Machine learning via DARTS-Optimized MobileViT models for pancreatic Cancer diagnosis with graph-based deep learning by Yusuf Alaca

“…This study presents a novel approach combining graph-based data representation with DARTS-optimised MobileViT models, with the objective of enhancing diagnostic accuracy and reliability. …”
Get full text

Efficient Visual-Aware Fashion Recommendation Using Compressed Node Features and Graph-Based Learning by Umar Subhan Malhi, Junfeng Zhou, Abdur Rasool, Shahbaz Siddeeq

“…Current recommendation systems often struggle to incorporate high-dimensional visual data into graph-based learning models effectively. This limitation presents a substantial opportunity to enhance the precision and effectiveness of fashion recommendations. …”
Get full text

Advanced cloud intrusion detection framework using graph based features transformers and contrastive learning by Vijay Govindarajan, Junaid Hussain Muzamal

“…Abstract This paper presents a modular and scalable intrusion detection framework that combines graph-based feature extraction, Transformer-based autoencoding, and contrastive learning to improve detection accuracy in cloud environments. …”
Get full text

PRCFX-DT: a new graph-based approach for feature selection and classification of genomic sequences by Amin Khodaei, Sania Eskandari, Hadi Sharifi, Behzad Mozaffari-Tazehkand

“…The analysis of viral genomic sequences can be efficacious in evaluating the present and potentially forthcoming condition of viruses. …”
Get full text

Discovering Breach Patterns on the Internet of Health Things: A Graph and Machine Learning Anomaly Analysis by Prabin B Lamichhane, Hannah Mannering, William Eberle

“…In this work, we analyze the performance of traditional statistical, machine learning, and graph-based anomaly detection approaches in response to this problem. …”
Get full text

The algebraic extended atom-type graph-based model for precise ligand–receptor binding affinity prediction by Farjana Tasnim Mukta, Md Masud Rana, Avery Meyer, Sally Ellingson, Duc D. Nguyen

“…Scientific Contribution The AGL-EAT-Score presents an algebraic graph-based framework that predicts ligand-receptor binding affinity by constructing multiscale weighted colored subgraphs from the 3D structure of protein-ligand complexes. …”
Get full text

Evading control flow graph based GNN malware detectors via active opcode insertion method with maliciousness preserving by Hao Peng, Zehao Yu, Dandan Zhao, Zhiguo Ding, Jieshuai Yang, Bo Zhang, Jianming Han, Xuhong Zhang, Shouling Ji, Ming Zhong

Get full text

Not seeing the trees for the forest. The impact of neighbours on graph-based configurations in histopathology by Olga Fourkioti, Matt De Vries, Reed Naidoo, Chris Bakal

“…The model learns from these broad labels to extract more detailed, instance-level insights. …”
Get full text

Graph-Based Extractive Text Summarization Models: A Systematic Review by Abdulkadir Bichi, Pantea Keikhosrokiani, Rohayanti Hassan, Khalil Almekhlafi

“…This paper presents a novel systematic review of various graph-based automatic text summarization models.…”
Get full text

Knowledge graph based entity selection framework for ad-hoc retrieval by Pankaj Singh, Plaban Kumar Bhowmick

Get full text

PathoGraph: A Graph-Based Method for Standardized Representation of Pathology Knowledge by Peiliang Lou, Yuxin Dong, Caixia Ding, Chunbao Wang, Ruifeng Guo, XiaoBo Pang, Chen Wang, Chen Li

“…Furthermore, we validate its computational utility by demonstrating the feasibility of large-scale automated PathoGraph construction, showing performance improvements in downstream deep learning tasks, and presenting two illustrative use cases that highlight its clinical potential. …”
Get full text

Graph-Based Prediction of Spatio-Temporal Vaccine Hesitancy From Insurance Claims Data by Sifat Afroj Moon, Rituparna Datta, Tanvir Ferdousi, Hannah Baek, Abhijin Adiga, Achla Marathe, Anil Vullikanti

Get full text

GNODEVAE: a graph-based ODE-VAE enhances clustering for single-cell data by Zeyu Fu, Chunlin Chen, Song Wang, Junping Wang, Shilei Chen

“…Extensive comparison across 50 diverse single cell datasets against 18 existing methods demonstrates that GNODEVAE consistently outperforms three major categories of benchmark methods: 8 machine learning dimensionality reduction techniques, 7 deep generative VAE variants, and 3 graph-based and contrastive learning deep predictive models. …”
Get full text

Graph-based adaptive feature fusion neural network model for person-job fit by Xia Xue, Feilong Wang, Jingwen Wang, Bo Ma, Yuyang Yu, Shuling Gao, Jing Chen, Baoli Wang

“…Previous studies on person-job fit fail to explore job seekers’ resume information from a multi-perspective approach, and neglect the sustainable learning of resume features. To address this, the present paper proposes a Graph-based Person-Job Fit Neural Network Fusion (GPJFNNF) model. …”
Get full text

Using Hybrid Neural Networks to Improve Traffic Prediction and Congestion Management by Ali Abd Samir

“…The proposed Materials and methods integrates Diffusion Convolutional Recurrent Neural Network (DCRNN) with graph-based models, allowing information to be shared among related sensors over large distances. …”
Get full text

Multi-view mixture-of-experts for predicting molecular properties using SMILES, SELFIES, and graph-based representations by Eduardo Soares, Victor Yukio Shirasuna, Emilio Vital Brazil, Indra Priyadarsini, Seiji Takeda

Get full text

Multi-Label Feature Selection with Graph-based Ant Colony Optimization and Generalized Jaccard Similarity by Sabah Robitan Mahmood, Tahsin Ali Mohammed Amin, Khalid Hassan Ahmed, Rebar Dara Mohammed, Pshtiwan Jabar Karim

Get full text

From sound to story: GAS-Saudi’s graph-based solution for audio summarization in the deaf community by Raed Alharbi, Khalid Almalki

“…This paper presents GAS-Saudi, a proof-of-concept novel graph-based framework designed to enhance summarization for the deaf community by leveraging complex relationships within acoustic signals. …”
Get full text

Visual explainable artificial intelligence for graph-based visual question answering and scene graph curation by Sebastian Künzel, Tanja Munz-Körner, Pascal Tilli, Noel Schäfer, Sandeep Vidyapu, Ngoc Thang Vu, Daniel Weiskopf

“…Abstract This study presents a novel visualization approach to explainable artificial intelligence for graph-based visual question answering (VQA) systems. …”
Get full text