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Found 10 papers, 5 papers with code
Graph-based Active Learning for Entity Cluster Repair
Cluster repair methods aim to determine errors in clusters and modify them so that each cluster consists of records representing the same entity.
Generating Synthetic Health Sensor Data for Privacy-Preserving Wearable Stress Detection
Smartwatch health sensor data is increasingly utilized in smart health applications and patient monitoring, including stress detection.
Construction of Knowledge Graphs: State and Challenges
With knowledge graphs (KGs) at the center of numerous applications such as recommender systems and question answering, the need for generalized pipelines to construct and continuously update such KGs is increasing.
Privacy in Practice: Private COVID-19 Detection in X-Ray Images (Extended Version)
The introduced DP should help limit leakage threats posed by MIAs, and our practical analysis is the first to test this hypothesis on the COVID-19 classification task.
EAGER: Embedding-Assisted Entity Resolution for Knowledge Graphs
Entity Resolution (ER) is a constitutional part for integrating different knowledge graphs in order to identify entities referring to the same real-world object.
ErGAN: Generative Adversarial Networks for Entity Resolution
Entity resolution targets at identifying records that represent the same real-world entity from one or more datasets.
LEAPME: Learning-based Property Matching with Embeddings
Data integration tasks such as the creation and extension of knowledge graphs involve the fusion of heterogeneous entities from many sources.
Graph Sampling with Distributed In-Memory Dataflow Systems
Given a large graph, a graph sample determines a subgraph with similar characteristics for certain metrics of the original graph.
Distributed, Parallel, and Cluster Computing
Scalable Matching and Clustering of Entities with FAMER
For the latter purpose, FAMER includes multiple clustering schemes that group matching entities from different sources within clusters.
Ranked #2 on
Entity Resolution
on MusicBrainz20K
DIMSpan - Transactional Frequent Subgraph Mining with Distributed In-Memory Dataflow Systems
Transactional frequent subgraph mining identifies frequent subgraphs in a collection of graphs.
Databases
