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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 171–180 of 431 papers

TitleStatusHype
Address-Specific Sustainable Accommodation Choice Through Real-World Data Integration—0
Deep Learning and NLP in Cryptocurrency Forecasting: Integrating Financial, Blockchain, and Social Media Data—0
Exploring Artificial Intelligence Methods for Energy Prediction in Healthcare Facilities: An In-Depth Extended Systematic Review—0
Exploring LLM Agents for Cleaning Tabular Machine Learning Datasets—0
Disambiguate Entity Matching using Large Language Models through Relation Discovery—0
DINGO: an ontology for projects and grants linked data—0
Diffusion Transport Alignment—0
Fast Record Linkage for Company Entities—0
Feature Selection for Data Integration with Mixed Multi-view Data—0
Beyond designer's knowledge: Generating materials design hypotheses via large language models—0
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