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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

Showing 61–70 of 431 papers

TitleStatusHype
From Swath to Full-Disc: Advancing Precipitation Retrieval with Multimodal Knowledge ExpansionCode0
Multi-task Learning for Heterogeneous Data via Integrating Shared and Task-Specific Encodings—0
Towards Unified Neural Decoding with Brain Functional Network Modeling—0
Towards Scalable Schema Mapping using Large Language Models—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
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