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496 results on '"Messina Enza"'

1. Graph Learning in 4D: a Quaternion-valued Laplacian to Enhance Spectral GCNs

Author

Fiorini, Stefano, Coniglio, Stefano, Ciavotta, Michele, and Messina, Enza

Subjects
Computer Science - Machine Learning
Abstract

We introduce QuaterGCN, a spectral Graph Convolutional Network (GCN) with quaternion-valued weights at whose core lies the Quaternionic Laplacian, a quaternion-valued Laplacian matrix by whose proposal we generalize two widely-used Laplacian matrices: the classical Laplacian (defined for undirected graphs) and the complex-valued Sign-Magnetic Laplacian (proposed to handle digraphs with weights of arbitrary sign). In addition to its generality, our Quaternionic Laplacian is the only Laplacian to completely preserve the topology of a digraph, as it can handle graphs and digraphs containing antiparallel pairs of edges (digons) of different weights without reducing them to a single (directed or undirected) edge as done with other Laplacians. Experimental results show the superior performance of QuaterGCN compared to other state-of-the-art GCNs, particularly in scenarios where the information the digons carry is crucial to successfully address the task at hand.

Published
2023

2. The Internet of Responsibilities-Connecting Human Responsibilities using Big Data and Blockchain

Author

Tang, Xuejiao, Qiu, Jiong, Zhang, Wenbin, Toure, Ibrahim, Zhang, Mingli, Messina, Enza, Xie, Xueping, Wang, Xuebing, and Yu, Sheng

Subjects
Computer Science - Computers and Society, Computer Science - Artificial Intelligence, Computer Science - Cryptography and Security
Abstract

Accountability in the workplace is critically important and remains a challenging problem, especially with respect to workplace safety management. In this paper, we introduce a novel notion, the Internet of Responsibilities, for accountability management. Our method sorts through the list of responsibilities with respect to hazardous positions. The positions are interconnected using directed acyclic graphs (DAGs) indicating the hierarchy of responsibilities in the organization. In addition, the system detects and collects responsibilities, and represents risk areas in terms of the positions of the responsibility nodes. Finally, an automatic reminder and assignment system is used to enforce a strict responsibility control without human intervention. Using blockchain technology, we further extend our system with the capability to store, recover and encrypt responsibility data. We show that through the application of the Internet of Responsibility network model driven by Big Data, enterprise and government agencies can attain a highly secured and safe workplace. Therefore, our model offers a combination of interconnected responsibilities, accountability, monitoring, and safety which is crucial for the protection of employees and the success of organizations.

Published
2023

4. Generating Informative Scenarios via Active Learning

Author

Candelieri, Antonio, Chou, Xiaochen, Archetti, Francesco A., Messina, Enza, Vigo, Daniele, Editor-in-Chief, Agnetis, Alessandro, Series Editor, Amaldi, Edoardo, Series Editor, Guerriero, Francesca, Series Editor, Lucidi, Stefano, Series Editor, Messina, Enza, Series Editor, Sforza, Antonio, Series Editor, Bruglieri, Maurizio, editor, Festa, Paola, editor, Macrina, Giusy, editor, and Pisacane, Ornella, editor

Published
2024
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5. Named Entity Recognition: Resource Constrained Maximum Path

Author

Di Puglia Pugliese Luigi, Fersini Elisabetta, Guerriero Francesca, and Messina Enza

Subjects
Information technology, T58.5-58.64
Abstract

Information Extraction (IE) is a process focused on automatic extraction of structured information from unstructured text sources. One open research field of IE relates to Named Entity Recognition (NER), aimed at identifying and associating atomic elements in a given text to a predefined category such as names of persons, organizations, locations and so on. This problem can be formalized as the assignment of a finite sequence of semantic labels to a set of interdependent variables associated with text fragments, and can modelled through a stochastic process involving both hidden variables (semantic labels) and observed variables (textual cues). In this work we investigate one of the most promising model for NER based on Conditional Random Fields (CRFs). CRFs are enhanced in a two stages approach to include in the decision process logic rules that can be either extracted from data or defined by domain experts. The problem is defined as a Resource Constrained Maximum Path Problem (RCMPP) associating a resource with each logic rule. Proper resource Extension Functions (REFs) and upper bound on the resource consumptions are defined in order to model the logic rules as knapsack-like constraints. A well-tailored dynamic programming procedure is defined to address the RCMPP.

Published
2017
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6. SigMaNet: One Laplacian to Rule Them All

Author

Fiorini, Stefano, Coniglio, Stefano, Ciavotta, Michele, and Messina, Enza

Subjects
Computer Science - Machine Learning
Abstract

This paper introduces SigMaNet, a generalized Graph Convolutional Network (GCN) capable of handling both undirected and directed graphs with weights not restricted in sign nor magnitude. The cornerstone of SigMaNet is the Sign-Magnetic Laplacian ($L^{\sigma}$), a new Laplacian matrix that we introduce ex novo in this work. $L^{\sigma}$ allows us to bridge a gap in the current literature by extending the theory of spectral GCNs to (directed) graphs with both positive and negative weights. $L^{\sigma}$ exhibits several desirable properties not enjoyed by other Laplacian matrices on which several state-of-the-art architectures are based, among which encoding the edge direction and weight in a clear and natural way that is not negatively affected by the weight magnitude. $L^{\sigma}$ is also completely parameter-free, which is not the case of other Laplacian operators such as, e.g., the Magnetic Laplacian. The versatility and the performance of our proposed approach is amply demonstrated via computational experiments. Indeed, our results show that, for at least a metric, SigMaNet achieves the best performance in 15 out of 21 cases and either the first- or second-best performance in 21 cases out of 21, even when compared to architectures that are either more complex or that, due to being designed for a narrower class of graphs, should -- but do not -- achieve a better performance., Comment: 22 pages, 6 tables

Published
2022

9. Using Machine Learning to Automate Mammogram Images Analysis

Author

Tang, Xuejiao, Zhang, Liuhua, Zhang, Wenbin, Huang, Xin, Iosifidis, Vasileios, Liu, Zhen, Zhang, Mingli, Messina, Enza, and Zhang, Ji

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Machine Learning
Abstract

Breast cancer is the second leading cause of cancer-related death after lung cancer in women. Early detection of breast cancer in X-ray mammography is believed to have effectively reduced the mortality rate. However, a relatively high false positive rate and a low specificity in mammography technology still exist. In this work, a computer-aided automatic mammogram analysis system is proposed to process the mammogram images and automatically discriminate them as either normal or cancerous, consisting of three consecutive image processing, feature selection, and image classification stages. In designing the system, the discrete wavelet transforms (Daubechies 2, Daubechies 4, and Biorthogonal 6.8) and the Fourier cosine transform were first used to parse the mammogram images and extract statistical features. Then, an entropy-based feature selection method was implemented to reduce the number of features. Finally, different pattern recognition methods (including the Back-propagation Network, the Linear Discriminant Analysis, and the Naive Bayes Classifier) and a voting classification scheme were employed. The performance of each classification strategy was evaluated for sensitivity, specificity, and accuracy and for general performance using the Receiver Operating Curve. Our method is validated on the dataset from the Eastern Health in Newfoundland and Labrador of Canada. The experimental results demonstrated that the proposed automatic mammogram analysis system could effectively improve the classification performances.

Published
2020

10. Efficient Kernel-based Subsequence Search for User Identification from Walking Activity

Author

Candelieri, Antonio, Fedorov, Stanislav, and Messina, Enza

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

This paper presents an efficient approach for subsequence search in data streams. The problem consists in identifying coherent repetitions of a given reference time-series, eventually multi-variate, within a longer data stream. Dynamic Time Warping (DTW) is the metric most widely used to implement pattern query, but its computational complexity is a well-known issue. In this paper we present an approach aimed at learning a kernel able to approximate DTW to be used for efficiently analyse streaming data collected from wearable sensors, reducing the burden of computation. Contrary to kernel, DTW allows for comparing time series with different length. Thus, to use a kernel, a feature embedding is used to represent a time-series as a fixed length vector. Each vector component is the DTW between the given time-series and a set of 'basis' series, usually randomly chosen. The vector size is the number of basis series used for the feature embedding. Searching for the portion of the data stream minimizing the DTW with the reference subsequence leads to a global optimization problem. The proposed approach has been validated on a benchmark dataset related to the identification of users depending on their walking activity. A comparison with a traditional DTW implementation is also provided., Comment: Keywords: Subsequence Search on Streaming Data, Dynamic Time Warping, Kernel

Published
2019

11. Deep Attributed Graph Embeddings

Author

Fersini, Elisabetta, Mottadelli, Simone, Carbonera, Michele, Messina, Enza, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Torra, Vicenç, editor, and Narukawa, Yasuo, editor

Published
2022
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12. A Decision Model for Enhancing Driving Security

Author

Baldi, Mauro Maria, Cilli, Nicola, Messina, Enza, Tango, Fabio, Vigo, Daniele, Editor-in-Chief, Agnetis, Alessandro, Series Editor, Amaldi, Edoardo, Series Editor, Guerriero, Francesca, Series Editor, Lucidi, Stefano, Series Editor, Messina, Enza, Series Editor, Sforza, Antonio, Series Editor, Cerulli, Raffaele, editor, Dell'Amico, Mauro, editor, and Pacciarelli, Dario, editor

Published
2021
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13. Smart Tourism System in Calabria

Author

De Maio, Annarita, Ferone, Daniele, Fersini, Elisabetta, Messina, Enza, Santoro, Francesco, Violi, Antonio, Gaul, Wolfgang, Managing Editor, Vichi, Maurizio, Managing Editor, Weihs, Claus, Managing Editor, Baier, Daniel, Editorial Board Member, Critchley, Frank, Editorial Board Member, Decker, Reinhold, Editorial Board Member, Diday, Edwin, Editorial Board Member, Greenacre, Michael, Editorial Board Member, Lauro, Carlo Natale, Editorial Board Member, Meulman, Jacqueline, Editorial Board Member, Monari, Paola, Editorial Board Member, Nishisato, Shizuhiko, Editorial Board Member, Ohsumi, Noboru, Editorial Board Member, Opitz, Otto, Editorial Board Member, Ritter, Gunter, Editorial Board Member, Schader, Martin, Editorial Board Member, Mariani, Paolo, editor, and Zenga, Mariangela, editor

Published
2021
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14. Word Embedding-Based Topic Similarity Measures

Author

Terragni, Silvia, Fersini, Elisabetta, Messina, Enza, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Métais, Elisabeth, editor, Meziane, Farid, editor, Horacek, Helmut, editor, and Kapetanios, Epaminondas, editor

Published
2021
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15. Optimal Scenario-Tree Selection for Multistage Stochastic Programming

Author

Galuzzi, Bruno G., Messina, Enza, Candelieri, Antonio, Archetti, Francesco, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Nicosia, Giuseppe, editor, Ojha, Varun, editor, La Malfa, Emanuele, editor, Jansen, Giorgio, editor, Sciacca, Vincenzo, editor, Pardalos, Panos, editor, Giuffrida, Giovanni, editor, and Umeton, Renato, editor

Published
2020
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16. Relational Bayesian Model Averaging for Sentiment Analysis in Social Networks

Author

Baldi, Mauro Maria, Fersini, Elisabetta, Messina, Enza, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Nicosia, Giuseppe, editor, Ojha, Varun, editor, La Malfa, Emanuele, editor, Jansen, Giorgio, editor, Sciacca, Vincenzo, editor, Pardalos, Panos, editor, Giuffrida, Giovanni, editor, and Umeton, Renato, editor

Published
2020
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20. Word Embeddings for Unsupervised Named Entity Linking

Author

Nozza, Debora, Sas, Cezar, Fersini, Elisabetta, Messina, Enza, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Douligeris, Christos, editor, Karagiannis, Dimitris, editor, and Apostolou, Dimitris, editor

Published
2019
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24. Adapting Named Entity Types to New Ontologies in a Microblogging Environment

Author

Fersini, Elisabetta, Manchanda, Pikakshi, Messina, Enza, Nozza, Debora, Palmonari, Matteo, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Mouhoub, Malek, editor, Sadaoui, Samira, editor, Ait Mohamed, Otmane, editor, and Ali, Moonis, editor

Published
2018
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26. Facing multidimensional poverty in older adults: An artificial intelligence approach that reveals the variable relevance

Author

Olearo, Lorenzo, D’Adda, Fabio, Messina, Enza, Cremaschi, Marco, Bandini, Stefania, and Gasparini, Francesca

Abstract

Despite the rapid development in very recent years of Artificial Intelligence models to predict poverty risk, this problem still remains an unsolved open challenge, especially from a multidimensional perspective. One of the main challenges is related to the scarcity of labelled and high-quality data for training models coupled with the lack of a general reference model to build good predictors. This results in the proposal of a variety of approaches tailored to specific contexts. This paper presents our proposal to address multidimensional poverty prediction, starting from an unlabelled dataset. We focus on the case of a fragile population, the older adults; our approach is highly flexible and can be easily adapted to various scenarios. Firstly, starting from expert knowledge, we apply a stochastic method for estimating the probability of an individual being poor, and we use this probability to identify three levels of risk. Then, we train an XGBoost classification model and exploit its tree structure to define a ranking of feature relevance. This information is used to create a new set of aggregated features representative of different poverty dimensions. An explainable novel Naive Bayes model is then trained for predicting individuals’ deprivation level in our particular domain. The capacity to identify which variables are predominantly associated with poverty among older adults offers valuable insights for policymakers and decision-makers to address poverty effectively.

Published
2024
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29. Smart Tourism System in Calabria

Author

De Maio, Annarita, primary, Ferone, Daniele, additional, Fersini, Elisabetta, additional, Messina, Enza, additional, Santoro, Francesco, additional, and Violi, Antonio, additional

Published
2020
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33. A Latent Representation Model for Sentiment Analysis in Heterogeneous Social Networks

Author

Nozza, Debora, Maccagnola, Daniele, Guigue, Vincent, Messina, Enza, Gallinari, Patrick, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Canal, Carlos, editor, and Idani, Akram, editor

Published
2015
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36. Safe Optimal Control of Dynamic Systems: Learning from Experts and Safely Exploring New Policies.

Author

Candelieri, Antonio, Ponti, Andrea, Fersini, Elisabetta, Messina, Enza, and Archetti, Francesco

Subjects
DYNAMICAL systems, KRIGING, GAUSSIAN processes, REINFORCEMENT learning, DIGITAL twins, STATISTICAL learning, SYSTEM dynamics
Abstract

Many real-life systems are usually controlled through policies replicating experts' knowledge, typically favouring "safety" at the expense of optimality. Indeed, these control policies are usually aimed at avoiding a system's disruptions or deviations from a target behaviour, leading to suboptimal performances. This paper proposes a statistical learning approach to exploit the historical safe experience—collected through the application of a safe control policy based on experts' knowledge— to "safely explore" new and more efficient policies. The basic idea is that performances can be improved by facing a reasonable and quantifiable risk in terms of safety. The proposed approach relies on Gaussian Process regression to obtain a probabilistic model of both a system's dynamics and performances, depending on the historical safe experience. The new policy consists of solving a constrained optimization problem, with two Gaussian Processes modelling, respectively, the safety constraints and the performance metric (i.e., objective function). As a probabilistic model, Gaussian Process regression provides an estimate of the target variable and the associated uncertainty; this property is crucial for dealing with uncertainty while new policies are safely explored. Another important benefit is that the proposed approach does not require any implementation of an expensive digital twin of the original system. Results on two real-life systems are presented, empirically proving the ability of the approach to improve performances with respect to the initial safe policy without significantly affecting safety. [ABSTRACT FROM AUTHOR]

Published
2023
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37. Bayesian Model Averaging and Model Selection for Polarity Classification

Author

Pozzi, Federico Alberto, Fersini, Elisabetta, Messina, Enza, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Métais, Elisabeth, editor, Meziane, Farid, editor, Saraee, Mohamad, editor, Sugumaran, Vijayan, editor, and Vadera, Sunil, editor

Published
2013
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38. Named Entities in Judicial Transcriptions: Extended Conditional Random Fields

Author

Fersini, Elisabetta, Messina, Enza, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, and Gelbukh, Alexander, editor

Published
2013
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39. Enhance User-Level Sentiment Analysis on Microblogs with Approval Relations

Author

Pozzi, Federico Alberto, Maccagnola, Daniele, Fersini, Elisabetta, Messina, Enza, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Baldoni, Matteo, editor, Baroglio, Cristina, editor, Boella, Guido, editor, and Micalizio, Roberto, editor

Published
2013
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42. Proceedings of the Eighth Italian Conference on Computational Linguistics CliC-it 2021

Author

Achena, Flavia, Aggarwal, Akshay, Albanesi, Davide, Albertin, Giorgia, Alzetta, Chiara, Anselma, Luca, Aparaschivei, Lavinia, Archetti, Francesco, Barattieri di San Pietro, Chiara, Barrón-Cedeño, Alberto, Basile, Pierpaolo, Basile, Valerio, Basili, Roberto, Bellandi, Andrea, Bosco, Cristina, Bosque-Gil, Julia, Brunato, Dominique, Brutti, Alessio, Budeanu, Ancuta, Cabrio, Elena, Canazza, Sergio, Candelieri, Antonio, Caselli, Tommaso, Casola, Silvia, Cassotti, Pierluigi, Cattoni, Roldano, Cecchini, Flavio Massimiliano, Celli, Fabio, Cerulli, Aldo, Cettolo, Mauro, Chesi, Cristiano, Cignarella, Alessandra Teresa, Cimiano, Philipp, Cimino, Andrea, Colella, Annalisa, Croce, Danilo, Cutugno, Francesco, Dall’Acqua, Anna, Dangelo, Paolo, Dei Rossi, Stefano, Dell’Orletta, Felice, Demartini, Silvia, De Gemmis, Marco, De Mattei, Lorenzo, Dini, Irene, Di Bratto, Martina, di Buono, Maria Pia, Di Caro, Luigi, Di Liello, Luca, Di Maro, Maria, Dufaux, Alain, Duzha, Armend, Elahi, Mohammad Fazleh, Ell, Basil, Ernandes, Marco, Fabrizi, Samuel, Fallucchi, Francesca, Fantoli, Margherita, Fernández, Raquel, Ferrari, Pier Luigi, Ferrero, Dario, Ferri, Fabio, Fersini, Elisabetta, Florio, Komal, Flouris, Giorgos, Frenda, Simona, Frey, Jennifer-Carmen, Gattero, Valerio, Gemelli, Sara, Gemmis, Marco de, Giovannetti, Emiliano, Gismondi, Biancamaria, Grasso, Francesca, Grotto, Francesco, Iacono, Maria, Iovine, Andrea, Jansen, Lennert, Jezek, Elisabetta, Kaplan, Frédéric, Labruna, Tiziano, Lai, Mirko, Lavelli, Alberto, Lenci, Alessandro, Litta, Eleonora, Lombardi, Agnese, Lops, Pasquale, Louvan, Samuel, Luzietti, Roberta Bianca, Maffia, Marta, Magnini, Bernardo, Mahed Mousavi, Seyed, Mambrini, Francesco, Marchi, Simone, Marelli, Marco, Marra, Andrea, Martino, Maria De, Marziano, Giuseppe, Masini, Francesca, Mastromattei, Michele, Mattiola, Simone, Mazzei, Alessandro, Messina, Enza, Miaschi, Alessio, Minnema, Gosse, Montemagni, Simonetta, Moretti, Giovanni, Moschitti, Alessandro, Negri, Matteo, Negro, Roberto, Nicolas, Lionel, Nissim, Malvina, Nolano, Gennaro, Ògúnrẹ̀mí, Tolúlọpẹ, Onorati, Dario, Origlia, Antonio, Orrico, Riccardo, Paccosi, Teresa, Palmero Aprosio, Alessio, Papadakos, Panagiotis, Papantoniou, Katerina, Papi, Sara, Papini, Mafalda, Passaro, Lucia C., Passarotti, Marco, Patti, Viviana, Pezzelle, Sandro, Plank, Barbara, Plexousakis, Dimitris, Pretto, Niccolò, Puccinelli, Daniele, Ranaldi, Leonardo, Ravelli, Andrea Amelio, Reverberi, Carlo, Riccardi, Giuseppe, Rocchietti, Guido, Romani, Emma, Rosato, Luca, Rossi, Laura, Roth, Dan, Ruffolo, Paolo, Ruzzetti, Elena Sofia, Sabri, Nazanin, Salaris, Sara, Sanguinetti, Manuela, Schettino, Loredana, Schmalz, Veronica Juliana, Sciolette, Flavia, Semeraro, Giovanni, Siciliani, Lucia, Simi, Maria, Sinclair, Arabella, Sprugnoli, Rachele, Stemle, Egon W., Stranisci, Marco Antonio, Tamburini, Fabio, Terragni, Silvia, Tesei, Andrea, Tonelli, Sara, Tripodi, Rocco, Turchi, Marco, Uryupina, Olga, van der Goot, Margot J., Ventura, Viviana, Venturi, Giulia, Villata, Serena, Vorakitphan, Vorakit, Zanchi, Chiara, Zanzotto, Fabio Massimo, Zeman, Daniel, Zugarini, Andrea, Fersini, Elisabetta, Passarotti, Marco, and Patti, Viviana

Subjects
Computational Linguistics, linguistica, linguistique computationelle, Linguistics, LAN009000, CF, linguistica computazionale, linguistique, Language
Abstract

The eighth edition of the Italian Conference on Computational Linguistics (CLiC-it 2021) was held at Università degli Studi di Milano-Bicocca from 26th to 28th January 2022. After the edition of 2020, which was held in fully virtual mode due to the health emergency related to Covid-19, CLiC-it 2021 represented the first moment for the Italian research community of Computational Linguistics to meet in person after more than one year of full/partial lockdown.

Published
2022

43. Deep Learning Representations in Automatic Misogyny Identification: What Do We Gain and What Do We Miss?

Author

Fersini, Elisabetta, Rosato, Luca, Candelieri, Antonio, Archetti, Francesco, and Messina, Enza

Subjects
Computational Linguistics, linguistica, linguistique computationelle, Linguistics, linguistica computazionale, linguistique, Language
Abstract

In this paper, we address the problem of automatic misogyny identification focusing on understanding the representation capabilities of widely adopted embeddings and addressing the problem of unintended bias. The proposed framework, grounded on Sentence Embeddings and Multi-Objective Bayesian Optimization, has been validated on an Italian dataset. We highlight capabilities and weaknesses related to the use of pre-trained language, as well as the contribution of Bayesian Optimization for mitigating the problem of biased predictions.

Published
2022

45. Web Page Classification: A Probabilistic Model with Relational Uncertainty

Author

Fersini, Elisabetta, Messina, Enza, Archetti, Francesco, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Hüllermeier, Eyke, editor, Kruse, Rudolf, editor, and Hoffmann, Frank, editor

Published
2010
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46. Relational Dynamic Bayesian Networks to Improve Multi-target Tracking

Author

Manfredotti, Cristina, Messina, Enza, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Blanc-Talon, Jacques, editor, Philips, Wilfried, editor, Popescu, Dan, editor, and Scheunders, Paul, editor

Published
2009
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47. Genetic Programming and Other Machine Learning Approaches to Predict Median Oral Lethal Dose (LD50) and Plasma Protein Binding Levels (%PPB) of Drugs

Author

Archetti, Francesco, Lanzeni, Stefano, Messina, Enza, Vanneschi, Leonardo, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Rangan, C. Pandu, editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Marchiori, Elena, editor, Moore, Jason H., editor, and Rajapakse, Jagath C., editor

Published
2007
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48. UP-DRES User Profiling for a Dynamic REcommendation System

Author

Messina, Enza, Toscani, Daniele, Archetti, Francesco, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, and Perner, Petra, editor

Published
2006
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49. Classifying and Counting Vehicles in Traffic Control Applications

Author

Archetti, Francesco, Messina, Enza, Toscani, Daniele, Vanneschi, Leonardo, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Rothlauf, Franz, editor, Branke, Jürgen, editor, Cagnoni, Stefano, editor, Costa, Ernesto, editor, Cotta, Carlos, editor, Drechsler, Rolf, editor, Lutton, Evelyne, editor, Machado, Penousal, editor, Moore, Jason H., editor, Romero, Juan, editor, Smith, George D., editor, Squillero, Giovanni, editor, and Takagi, Hideyuki, editor

Published
2006
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