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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 401–431 of 431 papers

TitleStatusHype
Disambiguate Entity Matching using Large Language Models through Relation Discovery—0
Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction—0
DREIFLUSS: A Minimalist Approach for Table Matching—0
Driving Digital Engineering Integration and Interoperability Through Semantic Integration of Models with Ontologies—0
Drug response prediction by inferring pathway-response associations with Kernelized Bayesian Matrix Factorization—0
Dynamical models for metabolomics data integration—0
Dynamic Basis Function Interpolation for Adaptive In Situ Data Integration in Ocean Modeling—0
Easy Semantification of Bioassays—0
Efficient Joinable Table Discovery in Data Lakes: A High-Dimensional Similarity-Based Approach—0
Embedding-based Multimodal Learning on Pan-Squamous Cell Carcinomas for Improved Survival Outcomes—0
Empowering Cognitive Digital Twins with Generative Foundation Models: Developing a Low-Carbon Integrated Freight Transportation System—0
Empowering Digital Agriculture: A Privacy-Preserving Framework for Data Sharing and Collaborative Research—0
Enhancing Bagging Ensemble Regression with Data Integration for Time Series-Based Diabetes Prediction—0
Enhancing End Stage Renal Disease Outcome Prediction: A Multi-Sourced Data-Driven Approach—0
Enhancing Function-Calling Capabilities in LLMs: Strategies for Prompt Formats, Data Integration, and Multilingual Translation—0
Enhancing streamflow forecast and extracting insights using long-short term memory networks with data integration at continental scales—0
EquiNMF: Graph Regularized Multiview Nonnegative Matrix Factorization—0
EraW-Net: Enhance-Refine-Align W-Net for Scene-Associated Driver Attention Estimation—0
EUR-USD Exchange Rate Forecasting Based on Information Fusion with Large Language Models and Deep Learning Methods—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
FadMan: Federated Anomaly Detection across Multiple Attributed Networks—0
Causal Feature Selection for Algorithmic Fairness—0
Fast Record Linkage for Company Entities—0
Feature Selection for Data Integration with Mixed Multi-view Data—0
Federated Learning: A new frontier in the exploration of multi-institutional medical imaging data—0
Federated Learning for Coronary Artery Plaque Detection in Atherosclerosis Using IVUS Imaging: A Multi-Hospital Collaboration—0
Federated Learning over Harmonized Data Silos—0
Federated Multi-View Learning for Private Medical Data Integration and Analysis—0
Deep Learning and NLP in Cryptocurrency Forecasting: Integrating Financial, Blockchain, and Social Media Data—0
From Automation to Autonomy in Smart Manufacturing: A Bayesian Optimization Framework for Modeling Multi-Objective Experimentation and Sequential Decision Making—0
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