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28 août 2017
- doi: 10.4000/books.aaccademia.1981
- eisbn: 9788899982553
https://creativecommons.org/licenses/by-nc-nd/4.0/ , info:eu-repo/semantics/openAccess
Mots-clés
linguistica computazionale riconoscimento telefonico articolare annotazione fattualità degli eventi entità chiamata rEcognition e collegamenti nei tweet italiani etichettare per messaggi social media classificazione polarità sentimenti linguistique computationelle reconnaissance téléphonique articulatoire annotation de facturation de l'événement entité appelée rEcognition et liens dans le tweets italien étiqueter les messages des médias sociaux classement polarité sentiments computational linguistics articulatory phone recognition event factuality annotation named entity rEcognition and linking in italian tweets tagging for italian social media texts sentiment polarity classification LAN009000 Linguistics CFSujets proches
PE ratio Earnings multiple Earnings-price ratio Stocks--Price-earnings ratios Pension plans Employee pension trusts Pension funds Mass communication Media, The Media, Mass Mass media Medios de comunicación de masas Price-earnings ratio Ratio C/B Coefficient de capitalisation des résultats CCR Coefficient de capitalisation des bénéfices RCB PER Multiple décapitalisation des résultats Multiple cours-bénéfice Régimes privés de retraite par capitalisation Plans d'épargne en vue de la retraite Plan d'épargne-retraite Comptes d'épargne-retraite Fonds de pension Régimes de retraite par capitalisation PER Retraite-épargne Media Techniques de diffusion collective Moyens de communication de masse Mass media Communication de masse Médias d'informationCiter ce document
Erick R. Fonseca et al., « Tweaking Word Embeddings for FAQ Ranking », Accademia University Press, ID : 10.4000/books.aaccademia.1981
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Résumé
We present the system developed at FBK for the EVALITA 2016 Shared Task “QA4FAQ – Question Answering for Frequently Asked Questions”. A peculiar characteristic of this task is the total absence of training data, so we created a meaningful representation of the data using only word embeddings. We present the system as well as the results of the two submitted runs, and a qualitative analysis of them.