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Found 32 papers, 4 papers with code
Creation of an Evaluation Corpus and Baseline Evaluation Scores for Welsh Text Summarisation
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.
AraSAS: The Open Source Arabic Semantic Tagger
This paper presents (AraSAS) the first open-source Arabic semantic analysis tagging system.
The Financial Causality Extraction Shared Task (FinCausal 2022)
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.
The Financial Document Structure Extraction Shared Task (FinTOC 2022)
This paper describes the FinTOC-2022 Shared Task on the structure extraction from financial documents, its participants results and their findings.
Financial Narrative Summarisation Using a Hybrid TF-IDF and Clustering Summariser: AO-Lancs System at FNS 2022
This paper describes the HTAC system submitted to the Financial Narrative Summarization Shared Task (FNS-2022).
The Financial Narrative Summarisation Shared Task (FNS 2022)
This paper presents the results and findings of the Financial Narrative Summarisation Shared Task on summarising UK, Greek and Spanish annual reports.
IgboBERT Models: Building and Training Transformer Models for the Igbo Language
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.
CoFiF Plus: A French Financial Narrative Summarisation Corpus
Natural Language Processing is increasingly being applied in the finance and business industry to analyse the text of many different types of financial documents.
The Financial Document Causality Detection Shared Task (FinCausal 2020)
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.
The Financial Document Structure Extraction Shared task (FinToc 2020)
This paper presents the FinTOC-2020 Shared Task on structure extraction from financial documents, its participants results and their findings.
The Financial Narrative Summarisation Shared Task (FNS 2020)
This paper presents the results and findings of the Financial Narrative Summarisation shared task (FNS 2020) on summarising UK annual reports.
A Data-driven Latent Semantic Analysis for Automatic Text Summarization using LDA Topic Modelling
The topic modelling result shows prevalence within topics 1 and 2.
Introducing the Welsh Text Summarisation Dataset and Baseline Systems
Welsh is an official language in Wales and is spoken by an estimated 884, 300 people (29. 2% of the population of Wales).
Financial Document Causality Detection Shared Task (FinCausal 2020)
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.
Habibi - a multi Dialect multi National Arabic Song Lyrics Corpus
This was achieved using a word-based Convolutional Neural Network (CNN) utilising a Continuous Bag of Words (CBOW) word embeddings model.
Infrastructure for Semantic Annotation in the Genomics Domain
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.
MultiLing 2019: Financial Narrative Summarisation
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.
In Search of Meaning: Lessons, Resources and Next Steps for Computational Analysis of Financial Discourse
We critically assess mainstream accounting and finance research applying methods from computational linguistics (CL) to study financial discourse.
Creating and Validating Multilingual Semantic Representations for Six Languages: Expert versus Non-Expert Crowds
Creating high-quality wide-coverage multilingual semantic lexicons to support knowledge-based approaches is a challenging time-consuming manual task.
Lexical Coverage Evaluation of Large-scale Multilingual Semantic Lexicons for Twelve Languages
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.
OSMAN ― A Novel Arabic Readability Metric
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
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.
Detecting Document Structure in a Very Large Corpus of UK Financial Reports
In this paper we present the evaluation of our automatic methods for detecting and extracting document structure in annual financial reports.
Assessing Crowdsourcing Quality through Objective Tasks
For each run we assessed the results provided by 25 workers on a set of 10 tasks.
