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Found 16 papers, 2 papers with code
Exploratory Analysis of News Sentiment Using Subgroup Discovery
In this study, we present an exploratory analysis of a Slovenian news corpus, in which we investigate the association between named entities and sentiment in the news.
Leveraging BERT Language Models for Multi-Lingual ESG Issue Identification
Environmental, Social, and Governance (ESG) has been used as a metric to measure the negative impacts and enhance positive outcomes of companies in areas such as the environment, society, and governance.
Using contextual sentence analysis models to recognize ESG concepts
For the second sub-task, we combine the RoBERTa model with a feed-forward multi-layer perceptron in order to extract the context of sentences and classify them.
Contextual Sentence Analysis for the Sentiment Prediction on Financial Data
Indeed, the combination of contextual sentence analysis with the financial and general sentiment dictionaries provided useful information to our model and allowed it to generate more reliable sentiment scores.
Named Entity Recognition and Classification on Historical Documents: A Survey
After decades of massive digitisation, an unprecedented amount of historical documents is available in digital format, along with their machine-readable texts.
CTLR@WiC-TSV: Target Sense Verification using Marked Inputs andPre-trained Models
This paper describes the CTRL participation in the Target Sense Verification of the Words in Context challenge (WiC-TSV) at SemDeep6.
Ranked #2 on
Entity Linking
on WiC-TSV
Alleviating Digitization Errors in Named Entity Recognition for Historical Documents
This paper tackles the task of named entity recognition (NER) applied to digitized historical texts obtained from processing digital images of newspapers using optical character recognition (OCR) techniques.
A Multilingual Study of Multi-Sentence Compression using Word Vertex-Labeled Graphs and Integer Linear Programming
Multi-Sentence Compression (MSC) aims to generate a short sentence with the key information from a cluster of similar sentences.
TLR at BSNLP2019: A Multilingual Named Entity Recognition System
This paper presents our participation at the shared task on multilingual named entity recognition at BSNLP2019.
Multilingual Named Entity Recognition
named-entity-recognition
+1
Predicting the Semantic Textual Similarity with Siamese CNN and LSTM
Semantic Textual Similarity (STS) is the basis of many applications in Natural Language Processing (NLP).
A Multilingual Study of Compressive Cross-Language Text Summarization
Cross-Language Text Summarization (CLTS) generates summaries in a language different from the language of the source documents.
Multi-Sentence Compression with Word Vertex-Labeled Graphs and Integer Linear Programming
Multi-Sentence Compression (MSC) aims to generate a short sentence with key information from a cluster of closely related sentences.
Métodos de Otimização Combinatória Aplicados ao Problema de Compressão MultiFrases
The Internet has led to a dramatic increase in the amount of available information.
Utilização de Grafos e Matriz de Similaridade na Sumarização Automática de Documentos Baseada em Extração de Frases
The internet increased the amount of information available.
LIA-RAG: a system based on graphs and divergence of probabilities applied to Speech-To-Text Summarization
This paper aims to introduces a new algorithm for automatic speech-to-text summarization based on statistical divergences of probabilities and graphs.
