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A Data Analysis Privacy Regulation Compliance Scheme for Lakehouse
To meet the diverse data storage and analysis needs in the Internet of Things era, businesses embrace the lakehouse approach, a hybrid deployment of data lakes and data warehouses on a single platform. Data consumers leverage data mining techniques ...
How ground-truth label helps link prediction in heterogeneous graphs
Link prediction is one of the most essential tasks in data mining. A lot of studies have shown great progress in homogeneous graph. However, besides recommendation system and knowledge graph, little research solves the problem of link prediction in ...
Graph Encoder Ensemble for Simultaneous Vertex Embedding and Community Detection
In this paper, we introduce a novel and computationally efficient method for vertex embedding, community detection, and community size determination. Our approach leverages a normalized one-hot graph encoder and a rank-based cluster size measure. Through ...
Enhancing Few-Shot Object Detection with Modified Faster R-CNN and Transfer Learning
Few-shot object detection, which aims to improve the generalization ability of the object detection model with limited data, has gained significant attention. Many existing methods use standard Faster R-CNN as the basic model and add modules to assist ...
Water Meter Reading Recognition Based on Deep Learning
The widespread and large-scale distribution of water meter users in China poses a significant challenge to the traditional manual meter reading method in most regions of the country. Rapid and accurate meter reading for a large number of water meters ...
MBCA:Identification of high-value patents using deep learning based language understanding
Aiming at the problem that the existing high-value patent recognition methods rely on experts' subjective experience judgment and the patent recognition model cannot fully extract the feature information of the patent text, which leads to the ...
Enabling Accurate Tuberculosis Diagnosis through Deep Learning on Patient CXR Images
Tuberculosis stands out as a severe and deadly infectious disease globally, characterized by a high incidence rate and mortality. While common tuberculosis screening methods involve diagnosing through CXR images, this approach carries a significant risk ...
Ensemble Model for Predicting Alzheimer's Disease and Disease Stages with CNN and Transformer Models
Alzheimer’s disease, a prevalent form of dementia, is a progressive, long-term and irreversible neurological disorder. With the growing elderly population, there has been a significant rise in the number of individuals affected by Alzheimer’s disease, ...
An ensemble pneumonia prediction and classification model including InceptionNeXtPneumonia prediction and classification
Pneumonia is an important threat to human health, and different types of pneumonia have different treatment options, so the prediction and classification of pneumonia are important health issues. In this paper, chest X-ray images are used as data, and ...
Enhancing Automatic Gastrointestinal Endoscopy Image Classification via Advanced Model and Adversarial Training Strategy
The present study elucidates the innovative application of automatic CMT model in gastrointestinal endoscopic image classification tasks, which is an advanced hybrid network based on Transformer.The training process of the CMT model effectively ...
Preoperative MR Image prediction of breast cancer based on self-supervised learning
Breast cancer is a prevalent cancer type among women worldwide, which contributes to significant mortality and morbidity rates. Early detection of breast cancer plays a crucial role in improving patients’ chances of survival. In this study, we utilized ...
Contrastive Learning based Item Representation with Asymmetric Augmentation for Sequential Recommendation
Contrastive learning has been widely applied in sequential recommendation to improve the recommendation performance. Existing contrastive learning methods focus on adjusting the views number of positive and negative samples to enhance the item ...
An Effective Reversible Data Hiding Scheme Used in Compressible Encryption Which Can Prevent Loss
This paper introduces a novel approach that combines reversible data hiding (RDH) and encryption-then-compression (ETC) for images. The proposed method involves encrypting the image first, followed by hiding secret information within it. The encrypted ...
Research on Parameter Correlation and Regression Modeling of Shear Strength Indicators
Aiming at the problem that cohesion force and internal friction Angle are difficult to be measured as shear strength indexes, correlation analysis and principal component analysis are used to explore the relationship between these two indexes and the ...
Multi-scale Fusion Dynamic Graph Neural Network For Traffic Flow Prediction
As a cornerstone of intelligent transportation systems, traffic flow prediction has garnered extensive research attention. However, traffic flow data exhibits pronounced spatio-temporal dynamics, rendering accurate traffic flow prediction a challenging ...
Motion trajectory planning of coal filling tamping mechanism based on improved DE algorithm
The filling and solidification method is employed in underground mines to backfill waste materials such as coal gangue, fly ash, and slag into the goaf, aiming to control strata movement and surface subsidence while addressing environmental pollution ...
A Classification Approach Using Improved Neighborhood Rough Set Feature Selection and Fuzzy K-Nearest Neighbor Method
This paper proposes a classification methodology that combines neighborhood rough set feature selection with the fuzzy k-nearest neighbor algorithm. The method enhances the accuracy by integrating the fuzzy k-nearest neighbor classifier into the well-...
Two-Stage Feature Attention Fusion for Radar-Camera 3D Object Detection
Multi-sensor fusion is essential for 3D object detection in intelligent transportation due to it makes best use of cross-modality information, in which feature-level fusion of millimeter-wave radar and camera has been a hot topic. Existing research ...
Text Sentiment Classification Model based on Fusion of DualChannel Features of CNN and BiLSTM
Text sentiment analysis is an important task in natural language processing (NLP), which aims to determine people's emotional tendency towards a certain topic or event by analyzing the language and emotion in the text. Aiming at the traditional emotion ...
6Community: An active IPv6 address detection method based on community discovery algorithm
Network management such as topology discovery and network diagnosis needs to be scanned based on the Internet, and the IPV6 address space is huge and it is difficult to perform global scanning. The existing IPV6 target generation method has a low hit ...
Multi-view deep subspace clustering with multilevel self-representation matrix fusion
Currently, multi-view deep subspace clustering algorithms have achieved remarkable success. However, existing methods have not yet focused on comprehensive information mining within the deep encoder for clustering performance improvement. To this end, ...
Y-index: An effective method to measure the importance of nodes in a directed weighted network
This paper proposes Y-index as the basic index of directed weighted network to measure the importance of nodes in the network. Considering the large number of nodes in most real networks, in order to improve the computing speed, we introduce the Y-index ...
Multi-objective UAV Trajectory Planning Based on Improved Wolf Pack Algorithm Improved Wolf Pack Algorithm
For multi-objective trajectory planning problem of an unmanned aerial vehicle(UAV) in complex environment, a problem model is constructed based on flight environment information, mission objectives, and flight performance constraints. A multi-objective ...
Chaotic Particle Swarm Optimization with Spiral-shaped Update Mechanism
Particle swarm optimization (PSO), as one of the metaheuristic optimization methods, has the merits of fast convergence, few adjustable parameters and simple searching process, but it also has the disadvantages of easily falling into local optimal and ...
Advancing Pulmonary Nodule Classification: A Novel Multi-Scale Fusion and Joint Upsampling Strategy using 3D Convolutional Neural Networks
Lung cancer, renowned for having the highest global incidence and mortality rates among all cancers, presents a promising avenue for improving survival rates through early detection and precise diagnosis. However, current diagnostic methods relying on ...
Stock Prediction Based on Multi-Factor Model
In the face of the information age, the integration of popular financial and computer fields has become a hotspot. Traditional stock prediction algorithms often rely on the experience and skills of financial experts, with unsatisfactory results. To ...
What's Your Next Guess?——A predictive model for Wordle user gaming based on ARIMA and Bi-LSTM
Wordle is a popular puzzle game offered by The New York Times every day, in which players need to guess a five-letter word in six or fewer attempts to solve the puzzle and receive feedback after each guess. Due to its simple and fun rules, it quickly ...
An improved chaotic-map based two-factor authentication and key agreement protocol for WSNs
The widespread use of wireless sensor networks has led to an increasing focus on their security. Although access control and other technologies are used to prevent the data from being revealed, many existing authentication key agreement protocols are ...
Time-Sensitive Data Processing Strategy for Enhancing the Performance of BFT Consensus Mechanism in IoT Edge Computing Environment
Applying the BFT consensus mechanism in the IoT edge computing environment effectively solves the problem of data consistency and trustworthiness. However, the existing BFT consensus mechanism needs to pay attention to the impact of the data processing ...
Enhanced Semantic Matching with Topic-aware and Fine-grained User Modeling for News Recommendation
Online news articles contain representative textual content including title, abstract, category and entities, and the clicked news articles by users indicate their interests. Fully exploiting these features is critical for accurate matching between ...
Index Terms
- Proceedings of the 2023 2nd International Conference on Algorithms, Data Mining, and Information Technology