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Found 11 papers, 6 papers with code
Bio-JOIE: Joint Representation Learning of Biological Knowledge Bases
Leveraging a wide-range of biological knowledge, such as gene ontology and protein-protein interaction (PPI) networks from other closely related species presents a vital approach to infer the molecular impact of a new species.
Multilingual Knowledge Graph Completion via Ensemble Knowledge Transfer
Predicting missing facts in a knowledge graph (KG) is a crucial task in knowledge base construction and reasoning, and it has been the subject of much research in recent works using KG embeddings.
Ranked #2 on
Knowledge Graph Completion
on DPB-5L (French)
BigData Applications from Graph Analytics to Machine Learning by Aggregates in Recursion
In the past, the semantic issues raised by the non-monotonic nature of aggregates often prevented their use in the recursive statements of logic programs and deductive databases.
Quantification and Analysis of Scientific Language Variation Across Research Fields
Quantifying differences in terminologies from various academic domains has been a longstanding problem yet to be solved.
Embedding Uncertain Knowledge Graphs
However, there are many KGs that model uncertain knowledge, which typically model the inherent uncertainty of relations facts with a confidence score, and embedding such uncertain knowledge represents an unresolved challenge.
On2Vec: Embedding-based Relation Prediction for Ontology Population
Recent advances in translation-based graph embedding methods for populating instance-level knowledge graphs lead to promising new approaching for the ontology population problem.
Learning to Represent Bilingual Dictionaries
Bilingual word embeddings have been widely used to capture the similarity of lexical semantics in different human languages.
Neural Article Pair Modeling for Wikipedia Sub-article Matching
Nowadays, editors tend to separate different subtopics of a long Wiki-pedia article into multiple sub-articles.
Co-training Embeddings of Knowledge Graphs and Entity Descriptions for Cross-lingual Entity Alignment
Since many multilingual KGs also provide literal descriptions of entities, in this paper, we introduce an embedding-based approach which leverages a weakly aligned multilingual KG for semi-supervised cross-lingual learning using entity descriptions.
How Much Are You Willing to Share? A "Poker-Styled" Selective Privacy Preserving Framework for Recommender Systems
Most industrial recommender systems rely on the popular collaborative filtering (CF) technique for providing personalized recommendations to its users.
Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment
Many recent works have demonstrated the benefits of knowledge graph embeddings in completing monolingual knowledge graphs.
Ranked #38 on
Entity Alignment
on DBP15k zh-en
