Search results for "NETWORKS"
showing 10 items of 3260 documents
Graph-based exploration and clustering analysis of semantic spaces
2019
Abstract The goal of this study is to demonstrate how network science and graph theory tools and concepts can be effectively used for exploring and comparing semantic spaces of word embeddings and lexical databases. Specifically, we construct semantic networks based on word2vec representation of words, which is “learnt” from large text corpora (Google news, Amazon reviews), and “human built” word networks derived from the well-known lexical databases: WordNet and Moby Thesaurus. We compare “global” (e.g., degrees, distances, clustering coefficients) and “local” (e.g., most central nodes and community-type dense clusters) characteristics of considered networks. Our observations suggest that …
A Controllable Text Simplification System for the Italian Language
2021
Text simplification is a non-trivial task that aims at reducing the linguistic complexity of written texts. Researchers have studied the problem by proposing new methodologies for addressing the English language, but other languages, like the Italian one, are almost unexplored. In this paper, we give a contribution to the enhancement of the Automated Text Simplification research by presenting a deep learning-based system, inspired by a state of the art system for the English language, capable of simplifying Italian texts. The system has been trained and tested by leveraging the Italian version of Newsela; it has shown promising results by achieving a SARI value of 30.17.
Assessment of the impacts of an oil spill on the populations of common guillemot (Uria aalge) and long-tailed duck (Clangula hyemalis) - an expert kn…
2012
The amount of operated oil transports continues to increase in the Gulf of Finland and in the case of an accident hazardous amounts of oil may be spilled into the sea. The oil accident may be harmful for the common guillemot and long-tailed duck populations. In this study expert knowledge regarding the behaviour and population dynamics of common guillemot and long-tailed duck in the Gulf of Finland was used to build a model to assess the impacts of an oil spill on the mortality and population size of these species. The Bayesian networks were used in the modelling. Based on the results the breeding colony of guillemots in Aspskär may survive in the consequence of recolonization. In conclusio…
Distributed Data Clustering via Opinion Dynamics
2015
We provide a distributed method to partition a large set of data in clusters, characterized by small in-group and large out-group distances. We assume a wireless sensors network in which each sensor is given a large set of data and the objective is to provide a way to group the sensors in homogeneous clusters by information type. In previous literature, the desired number of clusters must be specified a priori by the user. In our approach, the clusters are constrained to have centroids with a distance at least ε between them and the number of desired clusters is not specified. Although traditional algorithms fail to solve the problem with this constraint, it can help obtain a better cluste…
Work Partitioning on Parallel and Distributed Agent-Based Simulation
2017
Work partitioning is a key challenge with ap- plications in many scientific and technological fields. The problem is very well studied with a rich literature on both distributed and parallel computing architectures. In this paper we deal with the work partitioning problem for parallel and distributed agent-based simulations which aims at (i) balancing the overall load distribution, (ii) minimizing, at the same time, the communication overhead due to agents' inter-dependencies. We introduce a classification taxonomy of work partitioning strategies and present a space-based work partitioning ap- proach, based on a Quad-tree data structure, which enables to: identify a good space partitioning …
Movie Script Similarity Using Multilayer Network Portrait Divergence
2020
International audience; This paper addresses the question of movie similarity through multilayer graph similarity measures. Recent work has shown how to construct multilayer networks using movie scripts, and how they capture different aspects of the stories. Based on this modeling, we propose to rely on the multilayer structure and compute different similarities, so we may compare movies, not from their visual content, summary, or actors, but actually from their own storyboard. We propose to do so using “portrait divergence”, which has been recently introduced to compute graph distances from summarizing graph characteristics. We illustrate our approach on the series of six Star Wars movies.
Statistically validated networks in bipartite complex systems.
2011
Many complex systems present an intrinsic bipartite nature and are often described and modeled in terms of networks [1-5]. Examples include movies and actors [1, 2, 4], authors and scientific papers [6-9], email accounts and emails [10], plants and animals that pollinate them [11, 12]. Bipartite networks are often very heterogeneous in the number of relationships that the elements of one set establish with the elements of the other set. When one constructs a projected network with nodes from only one set, the system heterogeneity makes it very difficult to identify preferential links between the elements. Here we introduce an unsupervised method to statistically validate each link of the pr…
Gl-learning
2016
In this paper, we present a new open-source software library, Gl-learning, for grammatical inference. The rise of new application scenarios in recent years has required optimized methods to address knowledge extraction from huge amounts of data and to model highly complex systems. Our library implements the main state-of-the-art algorithms in the grammatical inference field (RPNI, EDSM, L*), redesigned through the OpenMP library for a parallel execution that drastically decreases execution times. To our best knowledge, it is also the first comprehensive library including a noise tolerance learning algorithm, such as Blue*, that significantly broadens the range of the potential application s…
A Logical Key Hierarchy Based approach to preserve content privacy in Decentralized Online Social Networks
2020
Distributed Online Social Networks (DOSNs) have been proposed to shift the control over user data from a unique entity, the online social network provider, to the users of the DOSN themselves. In this paper we focus on the problem of preserving the privacy of the contents shared to large groups of users. In general, content privacy is enforced by encrypting the content, having only authorized parties being able to decrypt it. When efficiency has to be taken into account, new solutions have to be devised that: i) minimize the re-encryption of the contents published in a group when the composition of the group changes; and, ii) enable a fast distribution of the cryptographic keys to all the m…
The Hierarchical Continuous Pursuit Learning Automation: A Novel Scheme for Environments With Large Numbers of Actions.
2019
Although the field of learning automata (LA) has made significant progress in the past four decades, the LA-based methods to tackle problems involving environments with a large number of actions is, in reality, relatively unresolved. The extension of the traditional LA to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and so, most components of the vector will soon have values that are smaller than the machine accuracy permits, implying that they will never be chosen . This paper presents a solution that extends the continuous pursuit paradigm to …