Search Results for author: Daniel Daza

Found 10 papers, 5 papers with code

SlotGAN: Detecting Mentions in Text via Adversarial Distant Learning

no code implementations spnlp (ACL) 2022 Daniel Daza, Michael Cochez, Paul Groth

We present SlotGAN, a framework for training a mention detection model that only requires unlabeled text and a gazetteer.

Sentence valid

A Neuro-Symbolic Framework for Answering Graph Pattern Queries in Knowledge Graphs

no code implementations6 Oct 2023 Tamara Cucumides, Daniel Daza, Pablo Barceló, Michael Cochez, Floris Geerts, Juan L Reutter, Miguel Romero

We introduce a framework for answering arbitrary graph pattern queries over incomplete knowledge graphs, encompassing both cyclic queries and tree-like queries with existentially quantified leaves.

Knowledge Graphs

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks

1 code implementation5 Oct 2023 Taraneh Younesian, Daniel Daza, Emile van Krieken, Thiviyan Thanapalasingam, Peter Bloem

To this end, we introduce GRAPES, an adaptive sampling method that learns to identify the set of nodes crucial for training a GNN.

Graph Sampling Node Classification

Approximate Answering of Graph Queries

no code implementations12 Aug 2023 Michael Cochez, Dimitrios Alivanistos, Erik Arakelyan, Max Berrendorf, Daniel Daza, Mikhail Galkin, Pasquale Minervini, Mathias Niepert, Hongyu Ren

We will first provide an overview of the different query types which can be supported by these methods and datasets typically used for evaluation, as well as an insight into their limitations.

Knowledge Graphs World Knowledge

Harnessing the Web and Knowledge Graphs for Automated Impact Investing Scoring

no code implementations4 Aug 2023 Qingzhi Hu, Daniel Daza, Laurens Swinkels, Kristina Ūsaitė, Robbert-Jan 't Hoen, Paul Groth

The Sustainable Development Goals (SDGs) were introduced by the United Nations in order to encourage policies and activities that help guarantee human prosperity and sustainability.

Knowledge Graphs

BioBLP: A Modular Framework for Learning on Multimodal Biomedical Knowledge Graphs

1 code implementation6 Jun 2023 Daniel Daza, Dimitrios Alivanistos, Payal Mitra, Thom Pijnenburg, Michael Cochez, Paul Groth

We train models using a biomedical KG containing approximately 2 million triples, and evaluate the performance of the resulting entity embeddings on the tasks of link prediction, and drug-protein interaction prediction, comparing against methods that do not take attribute data into account.

Attribute Entity Embeddings +2

Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification

no code implementations22 Feb 2021 Ruud van Bakel, Teodor Aleksiev, Daniel Daza, Dimitrios Alivanistos, Michael Cochez

Structured querying on such incomplete graphs will result in incomplete sets of answers, even if the correct entities exist in the graph, since one or more edges needed to match the pattern are missing.

Binary Classification Classification +4

Complex Query Answering with Neural Link Predictors

3 code implementations ICLR 2021 Erik Arakelyan, Daniel Daza, Pasquale Minervini, Michael Cochez

Finally, we demonstrate that it is possible to explain the outcome of our model in terms of the intermediate solutions identified for each of the complex query atoms.

Complex Query Answering

Message Passing Query Embedding

1 code implementation6 Feb 2020 Daniel Daza, Michael Cochez

The generality of our method allows it to encode a more diverse set of query types in comparison to previous work.

Entity Embeddings Graph Neural Network +3

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