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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
BayReL: Bayesian Relational Learning for Multi-omics Data IntegrationCode1
A Variational Information Bottleneck Approach to Multi-Omics Data IntegrationCode1
MSMA: Multi-agent Trajectory Prediction in Connected and Autonomous Vehicle Environment with Multi-source Data IntegrationCode1
Domain Adaptation for Deep Entity Resolution: A Design Space ExplorationCode1
Data Integration for Toxic Comment Classification: Making More Than 40 Datasets Easily Accessible in One Unified FormatCode1
Column Property Annotation using Large Language ModelsCode1
Dual-Objective Fine-Tuning of BERT for Entity MatchingCode1
Cost-Effective In-Context Learning for Entity Resolution: A Design Space ExplorationCode1
Fine-tuning Large Language Models for Entity MatchingCode1
Conformal Trajectory Prediction with Multi-View Data Integration in Cooperative DrivingCode1
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