D
Denilson Barbosa
Researcher at University of Alberta
Publications - 99
Citations - 2318
Denilson Barbosa is an academic researcher from University of Alberta. The author has contributed to research in topics: Information extraction & Relationship extraction. The author has an hindex of 24, co-authored 91 publications receiving 1897 citations. Previous affiliations of Denilson Barbosa include University of Toronto & Roma Tre University.
Papers
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Journal ArticleDOI
Knowledge Graph Embedding for Link Prediction: A Comparative Analysis
TL;DR: In this paper, a comprehensive comparison of embedding-based link prediction methods is provided, extending the dimensions of analysis beyond what is commonly available in the literature, and the authors experimentally compare the effectiveness and efficiency of 18 state-of-the-art methods, consider a rule-based baseline, and report detailed analysis over the most popular benchmarks.
Proceedings ArticleDOI
The XML web: a first study
TL;DR: This paper is the first attempt at describing the XML Web and the documents contained in it and shows that, despite its short history, XML already permeates the Web, both in terms of generic domains and geographically.
Journal ArticleDOI
Knowledge Graph Embedding for Link Prediction: A Comparative Analysis
TL;DR: This analysis provides a comprehensive comparison of embedding-based LP methods, extending the dimensions of analysis beyond what is commonly available in the literature.
Proceedings ArticleDOI
ToXgene: a template-based data generator for XML
TL;DR: ToXgene is a template-based tool for facilitating the generation of large, consistent collections of synthetic XML documents and is intended for the cases when the user knows the structure of the data she wants and requires the data to conform to this structure.
Journal ArticleDOI
Robust named entity disambiguation with random walks
Zhaochen Guo,Denilson Barbosa +1 more
TL;DR: This article presents two novel approaches guided by a natural notion of semantic similarity for the collective disambiguation of all entities mentioned in a document at the same time based on learning-to-rank.