Papers with Code 아카이브
Data Integration
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 3
- 평가표
- 0
- 보존된 평가 기록
- 0
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:
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
PulmoFusion: Advancing Pulmonary Health with Efficient Multi-Modal Fusion
A technical review of multi-omics data integration methods: from classical statistical to deep generative approaches
Replacing the Gallium Oxide Shell with Conductive Ag: Toward a Printable and Recyclable Composite for Highly Stretchable Electronics, Electromagnetic Shielding, and Thermal Interfaces
Foundation for unbiased cross-validation of spatio-temporal models for species distribution modeling
CAMEO: Autocorrelation-Preserving Line Simplification for Lossy Time Series Compression
Hybrid Parallel Collaborative Simulation Framework Integrating Device Physics with Circuit Dynamics for PDAE-Modeled Power Electronic Equipment
Fuzzy Integration of Data Lake Tables
Broadband measurements and analysis of human blocking in a 60 GHz indoor radio channel
Gandalf the Red: Adaptive Security for LLMs
Transforming Social Science Research with Transfer Learning: Social Science Survey Data Integration with AI
Network Diffuser for Placing-Scheduling Service Function Chains with Inverse Demonstration
RecKG: Knowledge Graph for Recommender Systems
mFabric: An Efficient and Scalable Fabric for Mixture-of-Experts Training
Graph-based Retrieval Augmented Generation for Dynamic Few-shot Text Classification
IAM: Enhancing RGB-D Instance Segmentation with New Benchmarks
Real-time Cross-modal Cybersickness Prediction in Virtual Reality
Mind the Data Gap: Bridging LLMs to Enterprise Data Integration
Semantic Web: Past, Present, and Future
ABACUS: A FinOps Service for Cloud Cost Optimization
Learn2Mix: Training Neural Networks Using Adaptive Data Integration
GraphSeqLM: A Unified Graph Language Framework for Omic Graph Learning
Federated Learning for Coronary Artery Plaque Detection in Atherosclerosis Using IVUS Imaging: A Multi-Hospital Collaboration
Clinical Trials Ontology Engineering with Large Language Models
Knowledge Graphs: The Future of Data Integration and Insightful Discovery
Block-Based Multi-Scale Image Rescaling
Leveraging User-Generated Metadata of Online Videos for Cover Song Identification
Demonstrating Data-to-Knowledge Pipelines for Connecting Production Sites in the World Wide Lab
BlockDoor: Blocking Backdoor Based Watermarks in Deep Neural Networks
Precision-Enhanced Human-Object Contact Detection via Depth-Aware Perspective Interaction and Object Texture Restoration
Data Integration with Fusion Searchlight: Classifying Brain States from Resting-state fMRI
Knowledge Graph Guided Evaluation of Abstention Techniques
Advancements in Machine Learning and Deep Learning for Early Detection and Management of Mental Health Disorder
MISFEAT: Feature Selection for Subgroups with Systematic Missing Data
LLM-Align: Utilizing Large Language Models for Entity Alignment in Knowledge Graphs
Unifying Dual-Space Embedding for Entity Alignment via Contrastive Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.