8 citations · 18 across the 4 of their papers we have counts for
5 papers
Learning MR-Sort Models from Non-Monotone Data
Pegdwende Minoungou, Vincent Mousseau, Wassila Ouerdane +1
The Majority Rule Sorting (MR-Sort) method assigns alternatives evaluated on multiple criteria to one of the predefined ordered categories. The Inverse MR-Sort problem (Inv-MR-Sort…
Business Entity Matching with Siamese Graph Convolutional Networks
Evgeny Krivosheev, Mattia Atzeni, Katsiaryna Mirylenka +3
Data integration has been studied extensively for decades and approached from different angles. However, this domain still remains largely rule-driven and lacks universal automatio…
Knowledge Graph Embedding using Graph Convolutional Networks with Relation-Aware Attention
Nasrullah Sheikh, Xiao Qin, Berthold Reinwald +3
Knowledge graph embedding methods learn embeddings of entities and relations in a low dimensional space which can be used for various downstream machine learning tasks such as link…
Siamese Graph Neural Networks for Data Integration
Evgeny Krivosheev, Mattia Atzeni, Katsiaryna Mirylenka +2
Data integration has been studied extensively for decades and approached from different angles. However, this domain still remains largely rule-driven and lacks universal automatio…
Fast Record Linkage for Company Entities
Thomas Gschwind, Christoph Miksovic, Julian Minder +2
Record linkage is an essential part of nearly all real-world systems that consume structured and unstructured data coming from different sources. Typically no common key is availab…