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Found 18 papers, 9 papers with code
Cross-Lingual Link Discovery for Under-Resourced Languages
In this paper, we provide an overview of current technologies for cross-lingual link discovery, and we discuss challenges, experiences and prospects of their application to under-resourced languages.
ISO-based Annotated Multilingual Parallel Corpus for Discourse Markers
In order to represent the meaning of the discourse markers, we propose an annotation scheme of discourse relations from ISO 24617-8 with a plug-in to ISO 24617-2 for communicative functions.
Modelling Frequency, Attestation, and Corpus-Based Information with OntoLex-FrAC
OntoLex-Lemon has become a de facto standard for lexical resources in the web of data.
Advancements in eHealth Data Analytics through Natural Language Processing and Deep Learning
The healthcare environment is commonly referred to as "information-rich" but also "knowledge poor".
Efficient Machine Learning Ensemble Methods for Detecting Gravitational Wave Glitches in LIGO Time Series
The phenomenon of Gravitational Wave (GW) analysis has grown in popularity as technology has advanced and the process of observing gravitational waves has become more precise.
Semantic Change Detection for the Romanian Language
Automatic semantic change methods try to identify the changes that appear over time in the meaning of words by analyzing their usage in diachronic corpora.
ATESA-BÆRT: A Heterogeneous Ensemble Learning Model for Aspect-Based Sentiment Analysis
The increasing volume of online reviews has made possible the development of sentiment analysis models for determining the opinion of customers regarding different products and services.
A Distributed Automatic Domain-Specific Multi-Word Term Recognition Architecture using Spark Ecosystem
Automatic Term Recognition is used to extract domain-specific terms that belong to a given domain.
Advanced Medical Image Representation for Efficient Processing and Transfer in Multisite Clouds
We test our solution for image representation and efficient data transfer in a multisite cloud environment.
It's All in the Embedding! Fake News Detection Using Document Embeddings
Models that use the context of textual data are essential for resolving the fake news detection problem, as they manage to encode linguistic features within the vector representation of words.
MisRoBÆRTa: Transformers versus Misinformation
We also benchmarked and evaluated the performances of multiple transformers on the task of misinformation detection.
SimpLex: a lexical text simplification architecture
Thus, the main contributions of this paper are: (1) We propose a new Word Embedding and Transformer based algorithm for text simplification; (2) We design \textsc{SimpLex} -- a modular novel text simplification system -- that can provide a baseline for further research; and (3) We perform an in-depth analysis of our solution and compare our results with two state-of-the-art models, i. e., LightLS [19] and NTS-w2v [44].
CONTAIN: A Community-based Algorithm for Network Immunization
Within the network analysis field, network immunization refers to the task of protecting a network from some arbitrary diffusion that tries to infect it.
MCWDST: a Minimum-Cost Weighted Directed Spanning Tree Algorithm for Real-Time Fake News Mitigation in Social Media
The widespread availability of internet access and handheld devices confers to social media a power similar to the one newspapers used to have.
DANES: Deep Neural Network Ensemble Architecture for Social and Textual Context-aware Fake News Detection
The growing popularity of social media platforms has simplified the creation and distribution of news articles but also creates a conduit for spreading fake news.
EDSA-Ensemble: an Event Detection Sentiment Analysis Ensemble Architecture
In this context, we propose a new ensemble architecture, EDSA-Ensemble (Event Detection Sentiment Analysis Ensemble), that uses Event Detection and Sentiment Analysis to improve the detection of the polarity for current events from Social Media.
ContCommRTD: A Distributed Content-based Misinformation-aware Community Detection System for Real-Time Disaster Reporting
We use content similarity and the proximity of nodes to create a new model for geolocation-content based communities.
Neural Approaches for Natural Language Interfaces to Databases: A Survey
A natural language interface to databases (NLIDB) enables users without technical expertise to easily access information from relational databases.
