Search results for " informazioni"

showing 10 items of 838 documents

Inducing the Lyndon Array

2019

In this paper we propose a variant of the induced suffix sorting algorithm by Nong (TOIS, 2013) that computes simultaneously the Lyndon array and the suffix array of a text in $O(n)$ time using $\sigma + O(1)$ words of working space, where $n$ is the length of the text and $\sigma$ is the alphabet size. Our result improves the previous best space requirement for linear time computation of the Lyndon array. In fact, all the known linear algorithms for Lyndon array computation use suffix sorting as a preprocessing step and use $O(n)$ words of working space in addition to the Lyndon array and suffix array. Experimental results with real and synthetic datasets show that our algorithm is not onl…

FOS: Computer and information sciences050101 languages & linguisticsComputer scienceComputationInduced suffix sorting02 engineering and technologySpace (mathematics)law.inventionSuffix sortinglawSuffix arrayComputer Science - Data Structures and Algorithms0202 electrical engineering electronic engineering information engineeringData_FILESPreprocessorData Structures and Algorithms (cs.DS)0501 psychology and cognitive sciencesComputer Science::Data Structures and AlgorithmsTime complexitySettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informatica05 social sciencesLightweight algorithmSuffix arraySigmaComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)Induced suffix sorting; Lightweight algorithms; Lyndon array; Suffix arrayWorking spaceLyndon arrayLightweight algorithms020201 artificial intelligence & image processingAlgorithmComputer Science::Formal Languages and Automata Theory
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SIFT Matching by Context Exposed

2023

This paper investigates how to step up local image descriptor matching by exploiting matching context information. Two main contexts are identified, originated respectively from the descriptor space and from the keypoint space. The former is generally used to design the actual matching strategy while the latter to filter matches according to the local spatial consistency. On this basis, a new matching strategy and a novel local spatial filter, named respectively blob matching and Delaunay Triangulation Matching (DTM) are devised. Blob matching provides a general matching framework by merging together several strategies, including rank-based pre-filtering as well as many-to-many and symmetri…

FOS: Computer and information sciencesArtificial neural networkSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniBenchmark testingRANSAClocal image descriptorSettore INF/01 - InformaticaApplied MathematicsComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionTransformDetectorDelaunay triangulationMerginglocal spatial filterimage contextComputational Theory and MathematicsArtificial IntelligenceKeypoint matchingSIFTPipelineTrainingComputer Vision and Pattern RecognitionSoftware
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FIRST

2018

Thanks to the collective action of participating smartphone users, mobile crowdsensing allows data collection at a scale and pace that was once impossible. The biggest challenge to overcome in mobile crowdsensing is that participants may exhibit malicious or unreliable behavior, thus compromising the accuracy of the data collection process. Therefore, it becomes imperative to design algorithms to accurately classify between reliable and unreliable sensing reports. To address this crucial issue, we propose a novel Framework for optimizing Information Reliability in Smartphone-based participaTory sensing (FIRST) that leverages mobile trusted participants (MTPs) to securely assess the reliabil…

FOS: Computer and information sciencesComputer Networks and CommunicationsComputer scienceDistributed computingFrameworkCrowdsensing02 engineering and technologyTrustMobileComputer Science - Networking and Internet ArchitectureThe National MapInformation020204 information systems0202 electrical engineering electronic engineering information engineeringAndroid (operating system)ReputationPaceSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniNetworking and Internet Architecture (cs.NI)Data collectionParticipatory sensingInformation quality020206 networking & telecommunicationsQualitySoftware deploymentWireless sensor networkACM Transactions on Sensor Networks
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Using Hankel matrices for dynamics-based facial emotion recognition and pain detection

2015

This paper proposes a new approach to model the temporal dynamics of a sequence of facial expressions. To this purpose, a sequence of Face Image Descriptors (FID) is regarded as the output of a Linear Time Invariant (LTI) system. The temporal dynamics of such sequence of descriptors are represented by means of a Hankel matrix. The paper presents different strategies to compute dynamics-based representation of a sequence of FID, and reports classification accuracy values of the proposed representations within different standard classification frameworks. The representations have been validated in two very challenging application domains: emotion recognition and pain detection. Experiments on…

FOS: Computer and information sciencesComputer Science - Artificial IntelligenceComputer Vision and Pattern Recognition (cs.CV)Speech recognitionFeature extractionComputer Science - Computer Vision and Pattern RecognitionPainLTI system theoryComputer Science - RoboticsLinear time invariant systemRepresentation (mathematics)Hidden Markov modelMathematicsEmotionSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSequencebusiness.industryPattern recognitiondynamicsClassificationSupport vector machineArtificial Intelligence (cs.AI)Face (geometry)Artificial intelligencebusinessRobotics (cs.RO)Hankel matrix2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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Conceptual Spaces for Cognitive Architectures: A lingua franca for different levels of representation

2017

During the last decades, many cognitive architectures (CAs) have been realized adopting different assumptions about the organization and the representation of their knowledge level. Some of them (e.g. SOAR [Laird (2012)]) adopt a classical symbolic approach, some (e.g. LEABRA [O'Reilly and Munakata (2000)]) are based on a purely connectionist model, while others (e.g. CLARION [Sun (2006)] adopt a hybrid approach combining connectionist and symbolic representational levels. Additionally, some attempts (e.g. biSOAR) trying to extend the representational capacities of CAs by integrating diagrammatical representations and reasoning are also available [Kurup and Chandrasekaran (2007)]. In this p…

FOS: Computer and information sciencesConceptual SpaceCognitive Architectures; Cognitive modeling; Conceptual Spaces; Knowledge representation; Experimental and Cognitive Psychology; Cognitive Neuroscience; Artificial IntelligenceComputer Science - Artificial IntelligenceComputer scienceCognitive NeuroscienceExperimental and Cognitive Psychology02 engineering and technology050105 experimental psychologyCognitive modelingCognitive ArchitecturesConnectionismArtificial IntelligenceConceptual Spaces0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesSoarCognitive ArchitectureRepresentation (mathematics)Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniCognitive scienceKnowledge level05 social sciencesCommon groundCognitionCLARIONDiagrammatic reasoningArtificial Intelligence (cs.AI)Knowledge representation020201 artificial intelligence & image processingThe SymbolicBiologically Inspired Cognitive Architectures
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IncentMe: Effective Mechanism Design to Stimulate Crowdsensing Participants with Uncertain Mobility

2018

Mobile crowdsensing harnesses the sensing power of modern smartphones to collect and analyze data beyond the scale of what was previously possible with traditional sensor networks. Given the participatory nature of mobile crowdsensing, it is imperative to incentivize mobile users to provide sensing services in a timely and reliable manner. Most importantly, given sensed information is often valid for a limited period of time, the capability of smartphone users to execute sensing tasks largely depends on their mobility pattern, which is often uncertain. For this reason, in this paper, we propose IncentMe, a framework that solves this core issue by leveraging game-theoretical reverse auction …

FOS: Computer and information sciencesOptimizationMonitoringComputer Networks and CommunicationsComputer scienceDistributed computingMobile computingCrowdsensing02 engineering and technologyComputer Science - Networking and Internet ArchitectureReverse auctionSmart phoneCrowdsensingGame Theory0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringSensorNetworking and Internet Architecture (cs.NI)Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMechanism designMobile computing020206 networking & telecommunicationsAuctionNavigationCore (game theory)RoadComputer Networks and CommunicationSensingTask analysisTask analysiParticipatoryState (computer science)MechanismSmartphoneWireless sensor networkIncentiveSoftware
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Minimal forbidden factors of circular words

2017

Minimal forbidden factors are a useful tool for investigating properties of words and languages. Two factorial languages are distinct if and only if they have different (antifactorial) sets of minimal forbidden factors. There exist algorithms for computing the minimal forbidden factors of a word, as well as of a regular factorial language. Conversely, Crochemore et al. [IPL, 1998] gave an algorithm that, given the trie recognizing a finite antifactorial language $M$, computes a DFA recognizing the language whose set of minimal forbidden factors is $M$. In the same paper, they showed that the obtained DFA is minimal if the input trie recognizes the minimal forbidden factors of a single word.…

FOS: Computer and information sciencesSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniGeneral Computer ScienceDiscrete Mathematics (cs.DM)Finite automatonSettore INF/01 - InformaticaFormal Languages and Automata Theory (cs.FL)Factor automatonComputer Science - Formal Languages and Automata TheoryComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)Circular wordFibonacci wordMinimal forbidden factorTheoretical Computer ScienceComputer Science::Formal Languages and Automata TheoryComputer Science - Discrete Mathematics
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Constructing Antidictionaries in Output-Sensitive Space

2021

A word $x$ that is absent from a word $y$ is called minimal if all its proper factors occur in $y$. Given a collection of $k$ words $y_1,y_2,\ldots,y_k$ over an alphabet $\Sigma$, we are asked to compute the set $\mathrm{M}^{\ell}_{y_{1}\#\ldots\#y_{k}}$ of minimal absent words of length at most $\ell$ of word $y=y_1\#y_2\#\ldots\#y_k$, $\#\notin\Sigma$. In data compression, this corresponds to computing the antidictionary of $k$ documents. In bioinformatics, it corresponds to computing words that are absent from a genome of $k$ chromosomes. This computation generally requires $\Omega(n)$ space for $n=|y|$ using any of the plenty available $\mathcal{O}(n)$-time algorithms. This is because a…

FOS: Computer and information sciencesSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniOutput sensitive algorithmsString algorithmsPhysicsAntidictionarieSettore INF/01 - InformaticaOutput sensitive algorithm0102 computer and information sciencesAbsent wordsSpace (mathematics)01 natural sciencesAntidictionariesCombinatorics010201 computation theory & mathematicsTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYData compressionComputer Science - Data Structures and AlgorithmsData Structures and Algorithms (cs.DS)Computer Science::Symbolic Computation[INFO]Computer Science [cs]Absent wordAlphabetWord (group theory)2019 Data Compression Conference (DCC)
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String attractors and combinatorics on words

2019

The notion of \emph{string attractor} has recently been introduced in [Prezza, 2017] and studied in [Kempa and Prezza, 2018] to provide a unifying framework for known dictionary-based compressors. A string attractor for a word $w=w[1]w[2]\cdots w[n]$ is a subset $\Gamma$ of the positions $\{1,\ldots,n\}$, such that all distinct factors of $w$ have an occurrence crossing at least one of the elements of $\Gamma$. While finding the smallest string attractor for a word is a NP-complete problem, it has been proved in [Kempa and Prezza, 2018] that dictionary compressors can be interpreted as algorithms approximating the smallest string attractor for a given word. In this paper we explore the noti…

FOS: Computer and information sciencesSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - InformaticaFormal Languages and Automata Theory (cs.FL)De Brujin wordComputer Science - Formal Languages and Automata TheoryBurrows-Wheeler transformString attractorComputer Science - Data Structures and AlgorithmsThue-Morse wordLempel-Ziv encodingBurrows-Wheeler transform; De Brujin word; Lempel-Ziv encoding; Run-length encoding; String attractor; Thue-Morse wordData Structures and Algorithms (cs.DS)Run-length encoding
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Quasi conjunction, quasi disjunction, t-norms and t-conorms: Probabilistic aspects

2013

We make a probabilistic analysis related to some inference rules which play an important role in nonmonotonic reasoning. In a coherence-based setting, we study the extensions of a probability assessment defined on $n$ conditional events to their quasi conjunction, and by exploiting duality, to their quasi disjunction. The lower and upper bounds coincide with some well known t-norms and t-conorms: minimum, product, Lukasiewicz, and Hamacher t-norms and their dual t-conorms. On this basis we obtain Quasi And and Quasi Or rules. These are rules for which any finite family of conditional events p-entails the associated quasi conjunction and quasi disjunction. We examine some cases of logical de…

FOS: Computer and information sciencesSettore MAT/06 - Probabilita' E Statistica MatematicaInformation Systems and ManagementComputer Science - Artificial Intelligencet-Norms/conormDuality (mathematics)goodman-nguyen inclusion relation; lower/upper probability bounds; t-norms/conorms; generalized loop rule; coherence; quasi conjunction/disjunctionComputer Science::Artificial IntelligenceTheoretical Computer ScienceArtificial IntelligenceFOS: MathematicsProbabilistic analysis of algorithmsNon-monotonic logicRule of inferenceLower/upper probability boundGoodman–Nguyen inclusion relationMathematicsEvent (probability theory)Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniDiscrete mathematicsInterpretation (logic)Probability (math.PR)Probabilistic logicCoherence (philosophical gambling strategy)Generalized Loop ruleComputer Science ApplicationsAlgebraArtificial Intelligence (cs.AI)Control and Systems EngineeringQuasi conjunction/disjunctionCoherenceMathematics - ProbabilitySoftwareInformation Sciences
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