Search results for "Named entity recognition"

showing 2 items of 2 documents

ChiLab4It system in the QA4FAQ competition

2017

ChiLab4It is the Question Answering system (QA) for Frequently Asked Questions (FAQ) developed by the Computer-Human Interaction Laboratory (ChiLab) at the University of Palermo for participating to the QA4FAQ task at EVALITA 2016 competition. The system is the versioning of the QuASIt framework developed by the same authors, which has been customized to address the particular task. This technical report describes the strategies that have been imported from QuASIt for implementing ChiLab4It, the actual system implementation, and the comparative evaluations with the results of the other participant tools, as provided by the organizers of the task. ChiLab4It was the only system whose score re…

Computer scienceentité appelée rEcognition et liens dans le tweets italiensentiment polarity classificationevent factuality annotationetichettare per messaggi social mediaclassificazione polarità sentimentitagging for italian social media textsCompetition (economics)computational linguisticsLAN009000linguistica computazionaleSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionireconnaissance téléphonique articulatoireQuestion answering FCG Cognitive systemarticulatory phone recognitionLinguisticsCFInternational economicsannotazione fattualità degli eventiriconoscimento telefonico articolarenamed entity rEcognition and linking in italian tweetslinguistique computationelleclassement polarité sentimentsentità chiamata rEcognition e collegamenti nei tweet italianiétiqueter les messages des médias sociauxannotation de facturation de l'événement
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Implementing sentiment analysis to an open-ended questionnaire: Case study of digitalization in elderly care during COVID-19

2022

[EN] The rise of digital technology has enabled us to utilize even more integrated systems for social and health care, but these systems are often complex and time-consuming to learn for the end users without relevant training or experience. We aim to perform Named Entity Recognition based sentiment analysis using the answers of eldercare workers that have taken a survey about the effects of digitalization on their work. The collection of the panel survey data was carried out in two waves: in 2019 and 2021. For the sentiment analysis we compare these two waves to determine the effects of COVID-19 on the work of eldercare workers. The research questions we ask are the following: “Has technol…

sosiaalipalvelutnamed entity recognitionCOVID-19Eldercare workDigitalizationvanhustyöntekijätdigitalizationvanhustenhuoltoeldercare workNamed entity recognitionSentiment analysistunteetsentiment analysiskokemuksetdigitalisaatiodigitaaliset taidotBERT
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