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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 131–140 of 431 papers

TitleStatusHype
Contextual Data Integration for Bike-sharing Demand Prediction with Graph Neural Networks in Degraded Weather Conditions—0
Enhancing Function-Calling Capabilities in LLMs: Strategies for Prompt Formats, Data Integration, and Multilingual Translation—0
Skeleton Detection Using Dual Radars with Integration of Dual-View CNN Models and mmPose—0
Optimal Estimation of Shared Singular Subspaces across Multiple Noisy Matrices—0
Multimodal Alignment and Fusion: A Survey—0
Federated Learning in Chemical Engineering: A Tutorial on a Framework for Privacy-Preserving Collaboration Across Distributed Data SourcesCode0
Unlocking Historical Clinical Trial Data with ALIGN: A Compositional Large Language Model System for Medical Coding—0
IoT-Based 3D Pose Estimation and Motion Optimization for Athletes: Application of C3D and OpenPose—0
Benchmarking pre-trained text embedding models in aligning built asset informationCode0
Multi-layer matrix factorization for cancer subtyping using full and partial multi-omics dataset—0
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