Search Results for author: Mahmoud El-Haj

Found 28 papers, 4 papers with code

Lexical Coverage Evaluation of Large-scale Multilingual Semantic Lexicons for Twelve Languages

1 code implementation LREC 2016 Scott Piao, Paul Rayson, Dawn Archer, Francesca Bianchi, Carmen Dayrell, Mahmoud El-Haj, Ricardo-Mar{\'\i}a Jim{\'e}nez, Dawn Knight, Michal K{\v{r}}en, Laura L{\"o}fberg, Rao Muhammad Adeel Nawab, Jawad Shafi, Phoey Lee Teh, Olga Mudraya

Lexical coverage is an important factor concerning the quality of the lexicons and the performance of the corpus annotation tools, and in this experiment we focus on evaluating the lexical coverage achieved by the multilingual lexicons and semantic annotation tools based on them.

Introducing the Welsh Text Summarisation Dataset and Baseline Systems

1 code implementation LREC 2022 Ignatius Ezeani, Mahmoud El-Haj, Jonathan Morris, Dawn Knight

Welsh is an official language in Wales and is spoken by an estimated 884, 300 people (29. 2% of the population of Wales).

Text Summarization

Detecting Document Structure in a Very Large Corpus of UK Financial Reports

no code implementations LREC 2014 Mahmoud El-Haj, Paul Rayson, Steve Young, Martin Walker

In this paper we present the evaluation of our automatic methods for detecting and extracting document structure in annual financial reports.

Text Generation

OSMAN ― A Novel Arabic Readability Metric

no code implementations LREC 2016 Mahmoud El-Haj, Paul Rayson

The Arabic sentences were written with the absence of diacritics and in order to count the number of syllables we added the diacritics in using an open source tool called Mishkal.

Learning Tone and Attribution for Financial Text Mining

no code implementations LREC 2016 Mahmoud El-Haj, Paul Rayson, Steve Young, Andrew Moore, Martin Walker, Thomas Schleicher, Vasiliki Athanasakou

Previous studies have only applied manual content analysis on a small scale to reveal such a bias in the narrative section of annual financial reports.

Attribute BIG-bench Machine Learning

MultiLing 2019: Financial Narrative Summarisation

no code implementations RANLP 2019 Mahmoud El-Haj

The Financial Narrative Summarisation task at MultiLing 2019 aims to demonstrate the value and challenges of applying automatic text summarisation to financial text written in English, usually referred to as financial narrative disclosures.

Habibi - a multi Dialect multi National Arabic Song Lyrics Corpus

no code implementations LREC 2020 Mahmoud El-Haj

This was achieved using a word-based Convolutional Neural Network (CNN) utilising a Continuous Bag of Words (CBOW) word embeddings model.

Dialect Identification Word Embeddings

Infrastructure for Semantic Annotation in the Genomics Domain

no code implementations LREC 2020 Mahmoud El-Haj, Nathan Rutherford, Matthew Coole, Ignatius Ezeani, Sheryl Prentice, Nancy Ide, Jo Knight, Scott Piao, John Mariani, Paul Rayson, Keith Suderman

The corpus database is distributed to permit fast indexing, and provides a simple web front-end with corpus linguistics methods for sub-corpus comparison and retrieval.

Retrieval

Financial Document Causality Detection Shared Task (FinCausal 2020)

no code implementations4 Dec 2020 Dominique Mariko, Hanna Abi Akl, Estelle Labidurie, Stéphane Durfort, Hugues de Mazancourt, Mahmoud El-Haj

We present the FinCausal 2020 Shared Task on Causality Detection in Financial Documents and the associated FinCausal dataset, and discuss the participating systems and results.

Binary Classification Relation Extraction +1

The Financial Narrative Summarisation Shared Task (FNS 2020)

no code implementations FNP (COLING) 2020 Mahmoud El-Haj, Ahmed Abura’Ed, Marina Litvak, Nikiforos Pittaras, George Giannakopoulos

This paper presents the results and findings of the Financial Narrative Summarisation shared task (FNS 2020) on summarising UK annual reports.

The Financial Document Structure Extraction Shared task (FinToc 2020)

no code implementations FNP (COLING) 2020 Najah-Imane Bentabet, Rémi Juge, Ismail El Maarouf, Virginie Mouilleron, Dialekti Valsamou-Stanislawski, Mahmoud El-Haj

This paper presents the FinTOC-2020 Shared Task on structure extraction from financial documents, its participants results and their findings.

The Financial Document Causality Detection Shared Task (FinCausal 2020)

no code implementations FNP (COLING) 2020 Dominique Mariko, Hanna Abi-Akl, Estelle Labidurie, Stephane Durfort, Hugues de Mazancourt, Mahmoud El-Haj

We present the FinCausal 2020 Shared Task on Causality Detection in Financial Documents and the associated FinCausal dataset, and discuss the participating systems and results.

Binary Classification Relation Extraction +1

IgboBERT Models: Building and Training Transformer Models for the Igbo Language

1 code implementation LREC 2022 Chiamaka Chukwuneke, Ignatius Ezeani, Paul Rayson, Mahmoud El-Haj

Our results show that, although the IgboNER task benefited hugely from fine-tuning large transformer model, fine-tuning a transformer model built from scratch with comparatively little Igbo text data seems to yield quite decent results for the IgboNER task.

Language Modelling named-entity-recognition +2

The Financial Causality Extraction Shared Task (FinCausal 2022)

no code implementations FNP (LREC) 2022 Dominique Mariko, Hanna Abi-Akl, Kim Trottier, Mahmoud El-Haj

We present the FinCausal 2020 Shared Task on Causality Detection in Financial Documents and the associated FinCausal dataset, and discuss the participating systems and results.

Creation of an Evaluation Corpus and Baseline Evaluation Scores for Welsh Text Summarisation

no code implementations CLTW (LREC) 2022 Mahmoud El-Haj, Ignatius Ezeani, Jonathan Morris, Dawn Knight

As part of the effort to increase the availability of Welsh digital technology, this paper introduces the first human vs metrics Welsh summarisation evaluation results and dataset, which we provide freely for research purposes to help advance the work on Welsh summarisation.

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