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Found 29 papers, 2 papers with code
A Survey of Automatic Text Summarization Using Graph Neural Networks
Although automatic text summarization (ATS) has been researched for several decades, the application of graph neural networks (GNNs) to this task started relatively recently.
Fine-tuning de modèles de langues pour la veille épidémiologique multilingue avec peu de ressources (Fine-tuning Language Models for Low-resource Multilingual Epidemic Surveillance)
Dans cet article, nous explorons plusieurs hypothèses concernant les facteurs qui pourraient avoir une influence sur les performances d’un système d’extraction d’événements épidémiologiques dans un scénario multilingue à faibles ressources : le type de modèle pré-entraîné, la qualité du tokenizer ainsi que les caractéristiques des entités à extraire.
MAKED: Multi-lingual Automatic Keyword Extraction Dataset
Keyword extraction is an integral task for many downstream problems like clustering, recommendation, search and classification.
Archive TimeLine Summarization (ATLS): Conceptual Framework for Timeline Generation over Historical Document Collections
Archive collections are nowadays mostly available through search engines interfaces, which allow a user to retrieve documents by issuing queries.
A Survey on Medical Document Summarization
The internet has had a dramatic effect on the healthcare industry, allowing documents to be saved, shared, and managed digitally.
Predicting Companies' ESG Ratings from News Articles Using Multivariate Timeseries Analysis
Environmental, social and governance (ESG) engagement of companies moved into the focus of public attention over recent years.
TimeBERT: Extending Pre-Trained Language Representations with Temporal Information
Time is an important aspect of documents and is used in a range of NLP and IR tasks.
A Survey on Multi-hop Question Answering and Generation
This implies that different datasets and models differ significantly which makes the field challenging to generalize and survey.
Change Summarization of Diachronic Scholarly Paper Collections by Semantic Evolution Analysis
The amount of scholarly data has been increasing dramatically over the last years.
A Survey on Multi-modal Summarization
The new era of technology has brought us to the point where it is convenient for people to share their opinions over an abundance of platforms.
ArchivalQA: A Large-scale Benchmark Dataset for Open Domain Question Answering over Historical News Collections
In the last few years, open-domain question answering (ODQA) has advanced rapidly due to the development of deep learning techniques and the availability of large-scale QA datasets.
A Neural Conversation Generation Model via Equivalent Shared Memory Investigation
Nevertheless, few works utilized the knowledge extracted from similar conversations for utterance generation.
Fact-Tree Reasoning for N-ary Question Answering over Knowledge Graphs
In the question answering(QA) task, multi-hop reasoning framework has been extensively studied in recent years to perform more efficient and interpretable answer reasoning on the Knowledge Graph(KG).
Multi-TimeLine Summarization (MTLS): Improving Timeline Summarization by Generating Multiple Summaries
In this paper, we address a novel task, Multiple TimeLine Summarization (MTLS), which extends the flexibility and versatility of Time-Line Summarization (TLS).
Generalized Relation Learning with Semantic Correlation Awareness for Link Prediction
The current methods for the link prediction taskhavetwonaturalproblems:1)the relation distributions in KGs are usually unbalanced, and 2) there are many unseen relations that occur in practical situations.
Multilingual Epidemiological Text Classification: A Comparative Study
We conduct a comparative study of different machine and deep learning text classification models using a dataset comprising news articles related to epidemic outbreaks from six languages, four low-resourced and two high-resourced, in order to analyze the influence of the nature of the language, the structure of the document, and the size of the data.
GMH: A General Multi-hop Reasoning Model for KG Completion
To the best of our knowledge, there lacks a general framework that approaches multi-hop reasoning in mixed long-short distance reasoning scenarios.
Multi-Modal Summary Generation using Multi-Objective Optimization
Significant development of communication technology over the past few years has motivated research in multi-modal summarization techniques.
ECIR 2020 Workshops: Assessing the Impact of Going Online
In this report, we describe the experience of organizing the ECIR 2020 Workshops in this scenario from two perspectives: the workshop organizers and the workshop participants.
Annotating and Analyzing Biased Sentences in News Articles using Crowdsourcing
In this paper, we propose a novel news bias dataset which facilitates the development and evaluation of approaches for detecting subtle bias in news articles and for understanding the characteristics of biased sentences.
Dataset for Temporal Analysis of English-French Cognates
Languages change over time and, thanks to the abundance of digital corpora, their evolutionary analysis using computational techniques has recently gained much research attention.
Joint Event Extraction along Shortest Dependency Paths using Graph Convolutional Networks
Also, an attention-based graph convolutional network is proposed, to carry syntactically related information along the shortest paths between argument candidates that captures and aggregates the latent associations between arguments; a problem that has been overlooked by most of the literature.
Citation Recommendation: Approaches and Datasets
In recent years, several approaches and evaluation data sets have been presented.
Spatio-Temporal Prediction of Dialectal Variant Usage
With the assumption of the {`}contact effect{'}, i. e. contact possibility (contact and isolation) between speaker communities being responsible for language change, and the apparent time hypothesis, we aim to predict the usage of dialectal variants.
Survey of Computational Approaches to Lexical Semantic Change
In this article we focus on diachronic conceptual change as an extension of semantic change.
A Multi-Attention based Neural Network with External Knowledge for Story Ending Predicting Task
Enabling a mechanism to understand a temporal story and predict its ending is an interesting issue that has attracted considerable attention, as in case of the ROC Story Cloze Task (SCT).
HistoryComparator: Interactive Across-Time Comparison in Document Archives
Recent years have witnessed significant increase in the number of large scale digital collections of archival documents such as news articles, books, etc.
