Search Results for author: Davide Buscaldi

Found 21 papers, 2 papers with code

Word Sense Induction with Hierarchical Clustering and Mutual Information Maximization

no code implementations11 Oct 2022 Hadi Abdine, Moussa Kamal Eddine, Michalis Vazirgiannis, Davide Buscaldi

In this paper, we propose a novel unsupervised method based on hierarchical clustering and invariant information clustering (IIC).

Clustering Language Modelling +1

A Benchmark Corpus for the Detection of Automatically Generated Text in Academic Publications

1 code implementation LREC 2022 Vijini Liyanage, Davide Buscaldi, Adeline Nazarenko

We evaluate the quality of the datasets comparing the generated texts to aligned original texts using fluency metrics such as BLEU and ROUGE.

Text Generation

Generating Knowledge Graphs by Employing Natural Language Processing and Machine Learning Techniques within the Scholarly Domain

1 code implementation28 Oct 2020 Danilo Dessì, Francesco Osborne, Diego Reforgiato Recupero, Davide Buscaldi, Enrico Motta

As such, in this paper, we present a new architecture that takes advantage of Natural Language Processing and Machine Learning methods for extracting entities and relationships from research publications and integrates them in a large-scale knowledge graph.

BIG-bench Machine Learning Knowledge Graphs +1

Calcul de similarit\'e entre phrases : quelles mesures et quels descripteurs ? (Sentence Similarity : a study on similarity metrics with words and character strings )

no code implementations JEPTALNRECITAL 2020 Davide Buscaldi, Ghazi Felhi, Dhaou Ghoul, Joseph Le Roux, Ga{\"e}l Lejeune, Xu-Dong Zhang

Dans notre travail nous nous sommes int{\'e}ress{\'e} {\`a} deux questions : celle du choix de la mesure du similarit{\'e} d{'}une part et celle du choix des op{\'e}randes sur lesquelles se porte la mesure de similarit{\'e}.

Sentence Sentence Similarity

TexTrolls: Identifying Russian Trolls on Twitter from a Textual Perspective

no code implementations3 Oct 2019 Bilal Ghanem, Davide Buscaldi, Paolo Rosso

Our approach is mainly based on textual features which utilize thematic information, and profiling features to identify the accounts from their way of writing tweets.

Indexation et appariements de documents cliniques pour le Deft 2019 (Indexing and pairing texts of the medical domain )

no code implementations JEPTALNRECITAL 2019 Davide Buscaldi, Dhaou Ghoul, Joseph Le Roux, Ga{\"e}l Lejeune

Pour la ta{\^c}he d{'}indexation nous avons test{\'e} deux m{\'e}thodes, une fond{\'e}e sur l{'}appariemetn pr{\'e}alable des documents du jeu de tset avec les documents du jeu d{'}entra{\^\i}nement et une autre m{\'e}thode fond{\'e}e sur l{'}annotation terminologique.

Mod\`eles en Caract\`eres pour la D\'etection de Polarit\'e dans les Tweets (Character-level Models for Polarity Detection in Tweets )

no code implementations JEPTALNRECITAL 2018 Davide Buscaldi, Joseph Le Roux, Ga{\"e}l Lejeune

Notre premi{\`e}re m{\'e}thode est fond{\'e}e sur des lexiques (mots et emojis), les n-grammes de caract{\`e}res et un classificateur {\`a} vaste marge (ou SVM).

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