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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 1120 of 431 papers

TitleStatusHype
KramaBench: A Benchmark for AI Systems on Data-to-Insight Pipelines over Data LakesCode1
Towards Unified Neural Decoding with Brain Functional Network Modeling0
Multi-task Learning for Heterogeneous Data via Integrating Shared and Task-Specific Encodings0
Towards Scalable Schema Mapping using Large Language Models0
Evaluating AI capabilities in detecting conspiracy theories on YouTubeCode0
Streamlining Knowledge Graph Creation with PyRML0
Towards a Spatiotemporal Fusion Approach to Precipitation NowcastingCode0
Control of Renewable Energy Communities using AI and Real-World Data0
Multimodal Generative AI for Story Point Estimation in Software Development0
Urban Representation Learning for Fine-grained Economic Mapping: A Semi-supervised Graph-based Approach0
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