activity
20172019
most citedNeural Machine Translation for Query Construction and Composition

18 citations · 49 across the 10 of their papers we have counts for

collaborators

12 papers

cs.CL2019★ 3 cited

Open-domain Event Extraction and Embedding for Natural Gas Market Prediction

Minh Triet Chau, Diego Esteves, Jens Lehmann

We propose an approach to predict the natural gas price in several days using historical price data and events extracted from news headlines. Most previous methods treats price as…

cs.IR2018

Named Entity Recognition on Noisy Data using Images and Text (1-page abstract)

Diego Esteves

Named Entity Recognition (NER) is an important subtask of information extraction that seeks to locate and recognise named entities. Despite recent achievements, we still face limit…

cs.AI2018

DeFactoNLP: Fact Verification using Entity Recognition, TFIDF Vector Comparison and Decomposable Attention

Aniketh Janardhan Reddy, Gil Rocha, Diego Esteves

In this paper, we describe DeFactoNLP, the system we designed for the FEVER 2018 Shared Task. The aim of this task was to conceive a system that can not only automatically assess t…

cs.IR2018★ 3 cited

Belittling the Source: Trustworthiness Indicators to Obfuscate Fake News on the Web

Diego Esteves, Aniketh Janardhan Reddy, Piyush Chawla +1

With the growth of the internet, the number of fake-news online has been proliferating every year. The consequences of such phenomena are manifold, ranging from lousy decision-maki…

cs.LG2018★ 11 cited

ML-Schema: Exposing the Semantics of Machine Learning with Schemas and Ontologies

Gustavo Correa Publio, Diego Esteves, Agnieszka Ławrynowicz +5

The ML-Schema, proposed by the W3C Machine Learning Schema Community Group, is a top-level ontology that provides a set of classes, properties, and restrictions for representing an…

cs.CL2018★ 18 cited

Neural Machine Translation for Query Construction and Composition

Tommaso Soru, Edgard Marx, André Valdestilhas +3

Research on question answering with knowledge base has recently seen an increasing use of deep architectures. In this extended abstract, we study the application of the neural mach…

cs.CL2018★ 2 cited

Expeditious Generation of Knowledge Graph Embeddings

Tommaso Soru, Stefano Ruberto, Diego Moussallem +4

Knowledge Graph Embedding methods aim at representing entities and relations in a knowledge base as points or vectors in a continuous vector space. Several approaches using embeddi…

cs.CL2018★ 5 cited

LIDIOMS: A Multilingual Linked Idioms Data Set

Diego Moussallem, Mohamed Ahmed Sherif, Diego Esteves +2

In this paper, we describe the LIDIOMS data set, a multilingual RDF representation of idioms currently containing five languages: English, German, Italian, Portuguese, and Russian.…

cs.DB2017

Mandolin: A Knowledge Discovery Framework for the Web of Data

Tommaso Soru, Diego Esteves, Edgard Marx +1

Markov Logic Networks join probabilistic modeling with first-order logic and have been shown to integrate well with the Semantic Web foundations. While several approaches have been…

cs.IR2017

Named Entity Recognition in Twitter using Images and Text

Diego Esteves, Rafael Peres, Jens Lehmann +1

Named Entity Recognition (NER) is an important subtask of information extraction that seeks to locate and recognise named entities. Despite recent achievements, we still face limit…

cs.CL2017

TANKER: Distributed Architecture for Named Entity Recognition and Disambiguation

Sandro A. Coelho, Diego Moussallem, Gustavo C. Publio +1

Named Entity Recognition and Disambiguation (NERD) systems have recently been widely researched to deal with the significant growth of the Web. NERD systems are crucial for several…

cs.CL2017★ 7 cited

SPARQL as a Foreign Language

Tommaso Soru, Edgard Marx, Diego Moussallem +4

In the last years, the Linked Data Cloud has achieved a size of more than 100 billion facts pertaining to a multitude of domains. However, accessing this information has been signi…