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Data Integration

Data integration (also called information integration) is the process of consolidating data from a set of heterogeneous data sources into a single uniform data set (materialized integration) or view on the data (virtual integration). Data integration pipelines involve subtasks such as schema matching, table annotation, entity resolution, value normalization, data cleansing, and data fusion. Application domains of data integration include data warehousing, data lakes, and knowledge base consolidation. Surveys on Data integration:

Papers

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Showing 401–431 of 431 papers

TitleStatusHype
Integrating Weather Station Data and Radar for Precipitation Nowcasting: SmaAt-fUsion and SmaAt-Krige-GNetCode0
A Unified Joint Matrix Factorization Framework for Data IntegrationCode0
ReMatch: Retrieval Enhanced Schema Matching with LLMsCode0
Alternative Telescopic Displacement: An Efficient Multimodal Alignment MethodCode0
RetSTA: An LLM-Based Approach for Standardizing Clinical Fundus Image ReportsCode0
CAVACHON: a hierarchical variational autoencoder to integrate multi-modal single-cell dataCode0
Intermediate triple table: A general architecture for virtual knowledge graphsCode0
Multimodal Contextualized Semantic Parsing from SpeechCode0
Building Flexible, Scalable, and Machine Learning-ready Multimodal Oncology DatasetsCode0
Scalable Randomized Kernel Methods for Multiview Data Integration and PredictionCode0
Data Integration with Fusion Searchlight: Classifying Brain States from Resting-state fMRICode0
Supervised Multiple Kernel Learning approaches for multi-omics data integrationCode0
Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical ModelsCode0
The scalable Birth-Death MCMC Algorithm for Mixed Graphical Model Learning with Application to Genomic Data IntegrationCode0
Kernel learning approaches for summarising and combining posterior similarity matricesCode0
DANAE: a denoising autoencoder for underwater attitude estimationCode0
A Systematic Approach to Featurization for Cancer Drug Sensitivity Predictions with Deep LearningCode0
Weakly-Supervised Multimodal Learning on MIMIC-CXRCode0
PoWareMatch: a Quality-aware Deep Learning Approach to Improve Human Schema MatchingCode0
Multimodal Quantum Natural Language Processing: A Novel Framework for using Quantum Methods to Analyse Real DataCode0
DALL-M: Context-Aware Clinical Data Augmentation with LLMsCode0
Comparative Analysis of Multi-Omics Integration Using Advanced Graph Neural Networks for Cancer ClassificationCode0
LLMs in Software Security: A Survey of Vulnerability Detection Techniques and InsightsCode0
An Empirical Meta-analysis of the Life Sciences (Linked?) Open Data on the WebCode0
Multi-Omic Data Integration and Feature Selection for Survival-based Patient Stratification via Supervised Concrete AutoencodersCode0
Learn2Mix: Training Neural Networks Using Adaptive Data IntegrationCode0
preon: Fast and accurate entity normalization for drug names and cancer types in precision oncologyCode0
Learning to Characterize Matching ExpertsCode0
Benchmarking pre-trained text embedding models in aligning built asset informationCode0
Multi-Task Adversarial Variational Autoencoder for Estimating Biological Brain Age with Multimodal NeuroimagingCode0
A deep learning pipeline for cross-sectional and longitudinal multiview data integrationCode0
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