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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 51–75 of 431 papers

TitleStatusHype
BayReL: Bayesian Relational Learning for Multi-omics Data IntegrationCode1
SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph SummarizationCode1
From Classical Machine Learning to Emerging Foundation Models: Review on Multimodal Data Integration for Cancer ResearchCode0
Empowering Digital Agriculture: A Privacy-Preserving Framework for Data Sharing and Collaborative Research—0
Intelligent Operation and Maintenance and Prediction Model Optimization for Improving Wind Power Generation Efficiency—0
Ring-lite: Scalable Reasoning via C3PO-Stabilized Reinforcement Learning for LLMs—0
Brain Imaging Foundation Models, Are We There Yet? A Systematic Review of Foundation Models for Brain Imaging and Biomedical Research—0
Leveraging MIMIC Datasets for Better Digital Health: A Review on Open Problems, Progress Highlights, and Future Promises—0
Enhancing Bagging Ensemble Regression with Data Integration for Time Series-Based Diabetes Prediction—0
The Cell Ontology in the age of single-cell omicsCode0
From Swath to Full-Disc: Advancing Precipitation Retrieval with Multimodal Knowledge ExpansionCode0
Towards Scalable Schema Mapping using Large Language Models—0
Towards Unified Neural Decoding with Brain Functional Network Modeling—0
Multi-task Learning for Heterogeneous Data via Integrating Shared and Task-Specific Encodings—0
Evaluating AI capabilities in detecting conspiracy theories on YouTubeCode0
Streamlining Knowledge Graph Creation with PyRML—0
Towards a Spatiotemporal Fusion Approach to Precipitation NowcastingCode0
Control of Renewable Energy Communities using AI and Real-World Data—0
Multimodal Generative AI for Story Point Estimation in Software Development—0
A Cautionary Tale on Integrating Studies with Disparate Outcome Measures for Causal Inference—0
Urban Representation Learning for Fine-grained Economic Mapping: A Semi-supervised Graph-based Approach—0
TUM2TWIN: Introducing the Large-Scale Multimodal Urban Digital Twin Benchmark Dataset—0
CrashSage: A Large Language Model-Centered Framework for Contextual and Interpretable Traffic Crash Analysis—0
CDE-Mapper: Using Retrieval-Augmented Language Models for Linking Clinical Data Elements to Controlled Vocabularies—0
Interpretable graph-based models on multimodal biomedical data integration: A technical review and benchmarking—0
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