Search results for " Network"
showing 10 items of 6428 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…
Challenging aspects in Consensus protocols for networks
2008
Results on consensus protocols for networks are presented. The basic tools and the main contribution available in the literature are considered, together with some of the related challenging aspects: estimation in networks and how to deal with disturbances is considered. Motivated by applications to sensor, peer-to- peer, and ad hoc networks, many papers have considered the problem of estimation in a consensus fashion. Here, the unknown but bounded (UBB) noise affecting the network is addressed in details. Because of the presence of UBB disturbances convergence to equilibria with all equal components is, in general, not possible. The solution of the epsiv-consensus problem, where the states…
"Master-Slave" Biological Network Alignment
2010
Performing global alignment between protein-protein interaction (PPI) networks of different organisms is important to infer knowledge about conservation across species. Known methods that perform this task operate symmetrically, that is to say, they do not assign a distinct role to the input PPI networks. However, in most cases, the input networks are indeed distinguishable on the basis of how well the corresponding organism is biologically well-characterized. For well-characterized organisms the associated PPI network supposedly encode in a sound manner all the information about their proteins and associated interactions, which is far from being the case for not well characterized ones. He…
High precision quantum query algorithm for computing AND-based boolean functions
2010
Quantum algorithms can be analyzed in a query model to compute Boolean functions. Function input is provided in a black box, and the aim is to compute the function value using as few queries to the black box as possible. The complexity of the algorithm is measured by the number of queries on the worst-case input. In this paper we consider computing AND Boolean function. First, we present a quantum algorithm for AND of two bits. Our algorithm uses one quantum query and correct result is obtained with a probability p=4/5, that improves previous results. The main result is generalization of our approach to design efficient quantum algorithms for computing composite function AND(f1,f2) where fi…
Network Centralities and Node Ranking
2017
An important problem in network analysis is understanding how much nodes are important in order to “propagate” the information across the input network. To this aim, many centrality measures have been proposed in the literature and our main goal here is that of providing an overview of the most important of them. In particular, we distinguish centrality measures based on walks computation from those based on shortest-paths computation. We also provide some examples in order to clarify how these measures can be calculated, with special attention to Degree Centrality, Closeness Centrality and Betweennes Centrality.
Problems and Techniques
2017
When biological networks are considered, the extraction of interesting knowledge often involves subgraphs isomorphism check that is known to be NP-complete. For this reason, many approaches try to simplify the problem under consideration by considering structures simpler than graphs, such as trees or paths. Furthermore, the number of existing approximate techniques is notably greater than the number of exact methods. In this chapter, we provide an overview of three important problems defined on biological networks: network alignment, network clustering, and motifs extraction from biological networks. For each of these problems, we also describe some of the most important techniques proposed…
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 …