发布求助
文献互助 智能选刊 最新文献

Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020最新文献

筛选
英文 中文
Creativity Embedding: A Vector to Characterise and Classify Plausible Triples in Deep Learning NLP Models 创造力嵌入:深度学习NLP模型中表征和分类似然三元组的向量
Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020 Pub Date : 1900-01-01 DOI: 10.4000/books.aaccademia.8768
Isabeau Oliveri, Luca Ardito, Giuseppe Rizzo, M. Morisio
{"title":"Creativity Embedding: A Vector to Characterise and Classify Plausible Triples in Deep Learning NLP Models","authors":"Isabeau Oliveri, Luca Ardito, Giuseppe Rizzo, M. Morisio","doi":"10.4000/books.aaccademia.8768","DOIUrl":"https://doi.org/10.4000/books.aaccademia.8768","url":null,"abstract":"English. In this paper we define the creativity embedding of a text based on four self-assessment creativity metrics, namely diversity, novelty, serendipity and magnitude, knowledge graphs, and neural networks. We use as basic unit the notion of triple (head, relation, tail). We investigate if additional information about creativity improves natural language processing tasks. In this work, we focus on triple plausibility task, exploiting BERT model and a WordNet11 dataset sample. Contrary to our hypothesis, we do not detect increase in the performance.","PeriodicalId":300279,"journal":{"name":"Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114518887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
L'impatto emotivo della comunicazione istituzionale durante la pandemia di COVID-19: uno studio di Twitter Sentiment Analysis covi -19大流行期间机构交流的情感影响:Twitter上的一项感官分析研究
Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020 Pub Date : 1900-01-01 DOI: 10.4000/books.aaccademia.8575
Gloria Gagliardi, Lorenzo Gregori, Alice Suozzi
{"title":"L'impatto emotivo della comunicazione istituzionale durante la pandemia di COVID-19: uno studio di Twitter Sentiment Analysis","authors":"Gloria Gagliardi, Lorenzo Gregori, Alice Suozzi","doi":"10.4000/books.aaccademia.8575","DOIUrl":"https://doi.org/10.4000/books.aaccademia.8575","url":null,"abstract":"This paper aims at investigating the impact of institutional communications during the health crisis due to Covid-19 pandemic in Italy, through the analysis of micro-blogging activities on Twitter by means of NLP techniques We performed a Sentiment Analysis on the TWITA corpus, to pinpoint potential correlations between opinion polarity (positive or negative) of the users and public speeches during the outbreak Our findings show changes in sentiment polarity related to three institutional speeches delivered by the Italian Prime Minister Giuseppe Conte on March, 4th, March, 9th, and April, 26th 2020 Copyright © 2020 for this paper by its authors","PeriodicalId":300279,"journal":{"name":"Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128286944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Predicting Movie-elicited Emotions from Dialogue in Screenplay Text: A Study on "Forrest Gump" 从剧本文本对话中预测电影情感——以《阿甘正传》为例
Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020 Pub Date : 1900-01-01 DOI: 10.4000/books.aaccademia.8610
Benedetta Iavarone, F. Dell’Orletta
{"title":"Predicting Movie-elicited Emotions from Dialogue in Screenplay Text: A Study on \"Forrest Gump\"","authors":"Benedetta Iavarone, F. Dell’Orletta","doi":"10.4000/books.aaccademia.8610","DOIUrl":"https://doi.org/10.4000/books.aaccademia.8610","url":null,"abstract":"We present a new dataset of sentences1 extracted from the movie Forrest Gump, annotated with the emotions perceived by a group of subjects while watching the movie. We run experiments to predict these emotions using two classifiers, one based on a Support Vector Machine with linguistic and lexical features, the other based on BERT. The experiments showed that contextual embeddings are effective in predicting human-perceived emotions. Copyright c ©2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).","PeriodicalId":300279,"journal":{"name":"Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130715529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Hate Speech Detection with Machine-Translated Data: The Role of Annotation Scheme, Class Imbalance and Undersampling 基于机器翻译数据的仇恨语音检测:标注方案、类不平衡和欠采样的作用
Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020 Pub Date : 1900-01-01 DOI: 10.4000/books.aaccademia.8345
Camilla Casula, Sara Tonelli
{"title":"Hate Speech Detection with Machine-Translated Data: The Role of Annotation Scheme, Class Imbalance and Undersampling","authors":"Camilla Casula, Sara Tonelli","doi":"10.4000/books.aaccademia.8345","DOIUrl":"https://doi.org/10.4000/books.aaccademia.8345","url":null,"abstract":"While using machine-translated data for supervised training can alleviate data sparseness problems when dealing with less-resourced languages, it is important that the source data are not only correctly translated, but also follow the same annotation scheme and possibly class balance as the smaller dataset in the target language. We therefore present an evaluation of hate speech detection in Italian using machine-translated data from English and comparing three settings, in order to understand the impact of training size, class distribution and annotation scheme.1","PeriodicalId":300279,"journal":{"name":"Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130934947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Automatic Induction of FrameNet lexical units in Italian 意大利语框架词汇单元的自动归纳
Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020 Pub Date : 1900-01-01 DOI: 10.4000/books.aaccademia.8300
Silvia Brambilla, D. Croce, F. Tamburini, R. Basili
{"title":"Automatic Induction of FrameNet lexical units in Italian","authors":"Silvia Brambilla, D. Croce, F. Tamburini, R. Basili","doi":"10.4000/books.aaccademia.8300","DOIUrl":"https://doi.org/10.4000/books.aaccademia.8300","url":null,"abstract":"In this paper we investigate the applicability of automatic methods for frame induction to improve the coverage of IFrameNet, a novel lexical resource based on Frame Semantics in Italian. The experimental evaluations show that the adopted methods based on neural word embeddings pave the way for the assisted development of a large scale lexical resource for","PeriodicalId":300279,"journal":{"name":"Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131322863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
UDante: First Steps Towards the Universal Dependencies Treebank of Dante's Latin Works 乌丹特:迈向但丁拉丁作品普遍依赖树库的第一步
Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020 Pub Date : 1900-01-01 DOI: 10.4000/books.aaccademia.8653
F. M. Cecchini, R. Sprugnoli, Giovanni Moretti, M. Passarotti
{"title":"UDante: First Steps Towards the Universal Dependencies Treebank of Dante's Latin Works","authors":"F. M. Cecchini, R. Sprugnoli, Giovanni Moretti, M. Passarotti","doi":"10.4000/books.aaccademia.8653","DOIUrl":"https://doi.org/10.4000/books.aaccademia.8653","url":null,"abstract":"English. This paper1 presents the early stages of the development of a new treebank containing all of Dante Alighieri’s Latin works. In particular, it describes the conversion of the original TEI-XML files to CoNLL-U, the creation of a gold standard, the process of training four annotators and the evaluation of the syntactic annotation in terms of inter-annotator agreement and LA, UAS and LAS. The aim is to release a new resource, in view of the celebrations for the 700th anniversary of Dante’s death, which can support the development of the Vocabolario Dantesco.","PeriodicalId":300279,"journal":{"name":"Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020","volume":"39 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123272858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 18
Valutazione umana di DeepL a livello di frase per le traduzioni di testi specialistici dall'inglese verso l'italiano 迪普对从英语翻译成意大利语的专家文本的句子级别的人类评价
Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020 Pub Date : 1900-01-01 DOI: 10.4000/books.aaccademia.8924
Mirko Tavosanis, S. Papa
{"title":"Valutazione umana di DeepL a livello di frase per le traduzioni di testi specialistici dall'inglese verso l'italiano","authors":"Mirko Tavosanis, S. Papa","doi":"10.4000/books.aaccademia.8924","DOIUrl":"https://doi.org/10.4000/books.aaccademia.8924","url":null,"abstract":"The paper presents an evaluation of the performance of DeepL in the translation of specialized texts from English to Italian. The evaluation was carried out at sentence level, on a sample of 108 sentences 1 Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). Il testo è stato concepito unitariamente dagli autori, ma ai fini della ripartizione del lavoro si dichiara che sono opera di Sirio Papa i paragrafi 4, 7 e 8 e di Mirko Tavosanis i restanti paragrafi. taken from texts relating to the environment, energy, bio-medicine and drug science, and the translations produced were evaluated by translators in training, with disciplinary skills. The translation by DeepL was statistically rated at the same level of human translation in terms of adequacy and slightly lower in terms of fluency. Machine translation of the texts also received a higher score than that obtained in another analysis, carried out in a similar way, by machine translation of journalistic texts.","PeriodicalId":300279,"journal":{"name":"Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127792477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
The AEREST Reading Database AEREST阅读数据库
Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020 Pub Date : 1900-01-01 DOI: 10.4000/books.aaccademia.8558
Marcello Ferro, Sara Giulivi, Claudia Cappa
{"title":"The AEREST Reading Database","authors":"Marcello Ferro, Sara Giulivi, Claudia Cappa","doi":"10.4000/books.aaccademia.8558","DOIUrl":"https://doi.org/10.4000/books.aaccademia.8558","url":null,"abstract":"Aerest is a reading assessment protocol for the concurrent evaluation of a child’s decoding and comprehension skills. Reading data complying with the Aerest protocol were automatically collected and structured with the ReadLet web-based platform in a pilot study, to form the Aerest Reading Database. The content, structure and potential of the database are described here, together with the main directions of current and future developments. Aerest è un protocollo di valutazione della lettura che misura in parallelo la capacità di decodifica e quella di comprensione del testo. Il protocollo è stato applicato in uno studio pilota i cui dati sono stati raccolti attraverso la piattaforma web ReadLet. L’articolo descrive il contenuto, la strutture e le potenzialità del data set risultante, insieme a future direzioni di sviluppo.","PeriodicalId":300279,"journal":{"name":"Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133503911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Multiword Expressions We Live by: A Validated Usage-based Dataset from Corpora of Written Italian 我们赖以生存的多词表达:来自书面意大利语语料库的基于用法的验证数据集
Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020 Pub Date : 1900-01-01 DOI: 10.4000/books.aaccademia.8710
F. Masini, M. Micheli, Andrea Zaninello, S. Castagnoli, M. Nissim
{"title":"Multiword Expressions We Live by: A Validated Usage-based Dataset from Corpora of Written Italian","authors":"F. Masini, M. Micheli, Andrea Zaninello, S. Castagnoli, M. Nissim","doi":"10.4000/books.aaccademia.8710","DOIUrl":"https://doi.org/10.4000/books.aaccademia.8710","url":null,"abstract":"The paper describes the creation of a manually validated dataset of Italian multiword expressions, building on candidates automatically extracted from corpora of written Italian. The main features of the resource, such as POS-pattern and lemma distribution, are also discussed, together with possible applications.","PeriodicalId":300279,"journal":{"name":"Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020","volume":"64 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132187094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Distributional Semantics: Yesterday, Today, and Tomorrow 分布语义:昨天、今天和明天
Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020 Pub Date : 1900-01-01 DOI: 10.4000/books.aaccademia.9030
Alessandro Lenci
{"title":"Distributional Semantics: Yesterday, Today, and Tomorrow","authors":"Alessandro Lenci","doi":"10.4000/books.aaccademia.9030","DOIUrl":"https://doi.org/10.4000/books.aaccademia.9030","url":null,"abstract":"Distributional semantics is undoubtedly the mainstream approach to meaning representation in computational linguistics today. It has also become an important paradigm of semantic analysis in cognitive science, and even linguists have started looking at it with growing interest. The popularity of distributional semantics has literally boomed in the era of Deep Learning, when “word embeddings” have become the basic ingredient to “cook” any NLP task. The era of BERT & co. has brought new types of contextualized representations that have often generated hasty claims of incredible breakthroughs in the natural language understanding capability of deep learning models. Unfortunately, these claims are not always supported by the improved semantic abilities of the last generation of embeddings. Models like BERT are still rooted in the principles of distributional learning, but at the same time their goal is more ambitious than generating corpus-based representations of meaning. On the one hand, the embeddings they produce encode much more than lexical meaning, but on the other hand we are still largely uncertain about what semantic properties of natural language they actually capture. Distributional semantics has surely benefited from the successes of the deep learning, but this might even jeopardize the very essence of distributional models of meaning, by making their goals and foundations unclear.","PeriodicalId":300279,"journal":{"name":"Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134520385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信