Publications de Alberto Garcia Duran

A Critical Re-evaluation of Neural Methods for Entity Alignment

Robert West, Akhil Arora, Manuel Leone, Alberto Garcia Duran, Stefano Huber

Neural methods have become the de-facto choice for the vast majority of data analysis tasks, and entity alignment (EA) is no exception. Not surprisingly, more than 50 different neural EA methods have been published since 2017. However, surprisingly, an ana ...

ASSOC COMPUTING MACHINERY2022

Efficient Entity Candidate Generation for Low-Resource Languages

Robert West, Akhil Arora, Alberto Garcia Duran

Candidate generation is a crucial module in entity linking. It also plays a key role in multiple NLP tasks that have been proven to beneficially leverage knowledge bases. Nevertheless, it has often been overlooked in the monolingual English entity linking ...

EUROPEAN LANGUAGE RESOURCES ASSOC-ELRA2022

Wikipedia Reader Navigation: When Synthetic Data Is Enough

Tiziano Piccardi, Robert West, Akhil Arora, Alberto Garcia Duran

Every day millions of people read Wikipedia. When navigating the vast space of available topics using hyperlinks, readers describe trajectories on the article network. Understanding these navigation patterns is crucial to better serve readers' needs and ad ...

ASSOC COMPUTING MACHINERY2022

Low-Rank Subspaces for Unsupervised Entity Linking

Robert West, Akhil Arora, Alberto Garcia Duran

Entity linking is an important problem with many applications. Most previous solutions were designed for settings where annotated training data is available, which is, however, not the case in numerous domains. We propose a light-weight and scalable entity ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2021

Node Attribute Completion in Knowledge Graphs with Multi-Relational Propagation

Eda Bayram, Robert West, Alberto Garcia Duran

The existing literature on knowledge graph completion mostly focuses on the link prediction task. However, knowledge graphs have an additional incompleteness problem: their nodes possess numerical attributes, whose values are often missing. Our approach, d ...

2021

Recursive Input And State Estimation: A General Framework For Learning From Time Series With Missing Data

Robert West, Alberto Garcia Duran

Time series with missing data are signals encountered in important settings for machine learning. Some of the most successful prior approaches for modeling such time series are based on recurrent neural networks that transform the input and previous state ...

IEEE2021

Transrev: Modeling Reviews as Translations From Users to Items

Alberto Garcia Duran

The text of a review expresses the sentiment a customer has towards a particular product. This is exploited in sentiment analysis where machine learning models are used to predict the review score from the text of the review. Furthermore, the products cost ...

Springer Nature2020

MMKG: Multi-modal Knowledge Graphs

Hongyu Li, Alberto Garcia Duran, Ye Liu

We present Mmkg, a collection of three knowledge graphs that contain both numerical features and (links to) images for all entities as well as entity alignments between pairs of KGs. Therefore, multi-relational link prediction and entity matching communiti ...

SPRINGER INTERNATIONAL PUBLISHING AG2019