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Entity Resolution

Data Integration › Entity Resolution 93 평가 기록 16 datasets

Entity resolution (also known as entity matching, record linkage, or duplicate detection) is the task of finding records that refer to the same real-world entity across different data sources (e.g., data files, books, websites, and databases). (Source: Wikipedia)

Surveys on entity resolution:

The task of entity resolution is closely related to the task of entity alignment which focuses on matching entities between knowledge bases. The task of entity linking differs from entity resolution as entity linking focuses on identifying entity mentions in free text.

Entity Resolution

논문

Fine-tuning Large Language Models for Entity Matching

WDC Products: A Multi-Dimensional Entity Matching Benchmark

Entity Matching using Large Language Models

Deduplication Over Heterogeneous Attribute Types (D-HAT)

Deep Entity Matching with Pre-Trained Language Models

Deep Learning for Entity Matching: A Design Space Exploration

Domain Adaptation for Deep Entity Resolution: A Design Space Exploration

Dual-Objective Fine-Tuning of BERT for Entity Matching

Entity Resolution with Hierarchical Graph Attention Networks

Probing the Robustness of Pre-trained Language Models for Entity Matching

Profiling Entity Matching Benchmark Tasks

Supervised Contrastive Learning for Product Matching