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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 21–30 of 431 papers

TitleStatusHype
AnyMatch -- Efficient Zero-Shot Entity Matching with a Small Language ModelCode1
Conformal Trajectory Prediction with Multi-View Data Integration in Cooperative DrivingCode1
MSMA: Multi-agent Trajectory Prediction in Connected and Autonomous Vehicle Environment with Multi-source Data IntegrationCode1
LLM See, LLM Do: Guiding Data Generation to Target Non-Differentiable ObjectivesCode1
WeatherQA: Can Multimodal Language Models Reason about Severe Weather?Code1
iMD4GC: Incomplete Multimodal Data Integration to Advance Precise Treatment Response Prediction and Survival Analysis for Gastric CancerCode1
eipy: An Open-Source Python Package for Multi-modal Data Integration using Heterogeneous EnsemblesCode1
Cost-Effective In-Context Learning for Entity Resolution: A Design Space ExplorationCode1
Transformer-based Entity Legal Form ClassificationCode1
Entity Matching using Large Language ModelsCode1
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