This paper presents an original WSD method, based on a mixture of three algorithms working on the local context of target units. The results on the task Multilingual lexical sample (MLS) of Senseval 3 were 60.3% of pr...
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The proceedings contain 29 papers. The topics discussed include: randomized disposal of unknown and implicity enforced bounds on parameters;algorithmic graph minors and bidimensionality;parameterized complexity of the...
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ISBN:
(纸本)354079722X
The proceedings contain 29 papers. The topics discussed include: randomized disposal of unknown and implicity enforced bounds on parameters;algorithmic graph minors and bidimensionality;parameterized complexity of the smallest degree-constrained subgraph problem;fixed structure complexity;an improved fixed-parameter algorithm for minimum-flip consensus trees;new fixed-parameter algorithms for the minimum quartet inconsistency problem;some fixed-parameter tractable classes of hypergraph duality and related problems;parameterized complexity and approximability of the SLCS problem;parameterized dramatization;a linear kernel for planer feedback vertex set;parameterized chess;the time complexity of constraint satisfaction;a tighter bound for counting max-weight solutions to 2SAT instances;and exact algorithms for edge domination.
The 3rdinternationalworkshop on Cross-lingual Event-centric Open Analytics (CLEOPATRA 2022) is co-located with The Web Conference (WWW) and held on the 25th of April, 20221. Modern society faces an unprecedented num...
ISBN:
(纸本)9781450391306
The 3rdinternationalworkshop on Cross-lingual Event-centric Open Analytics (CLEOPATRA 2022) is co-located with The Web Conference (WWW) and held on the 25th of April, 20221. Modern society faces an unprecedented number of events that impact countries, communities and economies around the globe across language, country and community borders. Recent examples include sudden or unexpected events such as terrorist attacks and political shake-ups such as Brexit, events related to the ongoing COVID-19 pandemic, as well as longer ongoing and evolving topics such as the migration crisis in Europe that regularly spawn events of global importance affecting local communities. These developments result in a vast amount of event-centric, multilingual information available from heterogeneous sources on the Web, on the Web of Data, within Knowledge Graphs, in social media, inside Web archives and in news sources. Such event-centric information differs across sources, languages and communities, potentially reflecting community-specific aspects, opinions, sentiments and bias. The theme of the workshop includes a variety of interdisciplinary challenges related to analysis, interaction with and interpretation of vast amounts of event-centric textual, semantic and visual information in multiple languages originating from different communities. The goal of the interdisciplinary CLEOPATRA workshop is to bring together researchers and practitioners from the fields of Semantic Web, the Web, NLP, IR, Human computation, Visual Analytics and Digital Humanities to discuss and evaluate methods and solutions for effective and efficient analytics of event-centric multilingual information spread across heterogeneous sources. This will support the delivery of analytical results in ways meaningful to users, helping them to cross language barriers and better understand event representations and their context in other languages. The workshop features advanced methods for extracting event-centric info
Based on the analysis of the characteristics and requirements of the virtual workshop and the multi-agent system, this paper proposes the scheduling unit model of the multi-agent virtual workshop. According to this mo...
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The computation of autocorrelation matrix is used heavily in several areas including signal and image processing, where parallel and application-specific architectures are also being increasingly used. Therefore, an e...
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ISBN:
(纸本)0818682596
The computation of autocorrelation matrix is used heavily in several areas including signal and image processing, where parallel and application-specific architectures are also being increasingly used. Therefore, an efficient scheme to compute autocorrelation matrix on parallel architectures has tremendous benefits. In this paper, a parallel algorithm for the computation of autocorrelation matrix on 2-D mesh is presented. The computation requirements for the elements of the autocorrelation matrix is highly skewed and the proposed algorithm attempts to balance the computation load, without requiring an external load balancing algorithm or processor. In this sense, the load balancing is embedded within the algorithm. The exact number of computation steps are derived. The time complexity of the proposed algorithm is shown to be within twice the optimal (or lower bound). It is also shown to have twice the speedup of a straight-forward parallel algorithm.
The proceedings contain 10 papers. The topics discussed include: computation offloading from mobile devices: can edge devices perform better than the cloud?;performance of approximate causal consistency for partially-...
ISBN:
(纸本)9781450342278
The proceedings contain 10 papers. The topics discussed include: computation offloading from mobile devices: can edge devices perform better than the cloud?;performance of approximate causal consistency for partially-replicated systems;modeling the scalability of real-time online interactive applications on clouds;the impact on the performance of co-running virtual machines in a virtualized environment;a gossip-based dynamic virtual machine consolidation strategy for large-scale cloud data centers;data management of sensor signals for high bandwidth data streaming to the cloud;cloud elasticity: going beyond demand as user load;and cloud live streaming system based on auto-adaptive overlay for cyber physical infrastructure.
The threshold theorem states that quantum computations can scale robustly in the presence of certain types of noise processes (e.g., Markovian) as long as the probability of error for each physical component remains b...
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The threshold theorem states that quantum computations can scale robustly in the presence of certain types of noise processes (e.g., Markovian) as long as the probability of error for each physical component remains below a critical threshold. To satisfy this threshold a theoretical circuit requiring O(s) idealized noiseless gates can be implemented with O(s polylog s) gates to maintain an error rate that is constant with increasing s. In this paper, we argue that maintaining a fixed error rate is necessary but not sufficient to preserve complexity results obtained under an assumption of noiseless gates. Specifically, we show that nontrivial quantum algorithms exhibit nonlinear sensitivity to any circuit error and that this sensitivity affects algorithmic complexity. The joint effects of circuit error and quantum-algorithmic iteration are examined for the case of quantum search, and more complete complexity results are derived. (c) 2011 Elsevier Inc. All rights reserved.
The proceedings contain 7 papers. The topics discussed include: recovering C++ objects from binaries;formal analysis of CRT-RSA vigilant's countermeasure against BellCoRe attacks;DroidLegacy: automated familial cl...
ISBN:
(纸本)9781450326490
The proceedings contain 7 papers. The topics discussed include: recovering C++ objects from binaries;formal analysis of CRT-RSA vigilant's countermeasure against BellCoRe attacks;DroidLegacy: automated familial classification of Android malware;TDVMP: improved virtual machine-based software protection with time diversity;hardware-enforced protection against software reverse-engineering based on an instruction set encoding;analyzing program dependencies for malware detection;and the GDSL toolkit: generating frontends for the analysis of machine code.
The contribution of this work is to enable time-sensitive, computation intensive applications on wearable interactive devices. To achieve this goal, this work developed an elastic computation middle-ware to federate c...
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ISBN:
(纸本)9781467377850
The contribution of this work is to enable time-sensitive, computation intensive applications on wearable interactive devices. To achieve this goal, this work developed an elastic computation middle-ware to federate computation resources on wearable devices, mobile devices and the connected devices that can be connected via local-and wide-area networks. With the middle-ware, the mobile applications receive mandatory/critical results before individual deadlines and optional/ noncritical results when computation resources are available on either local or connected devices. Compared with multi-tier and resource-aware mobile computation frameworks, the elastic computation middle-ware does not only offload computation workloads to connected devices but also make use of the computation and storage resources on connected devices to enhance the computation results. In addition, the mobility of the devices are taken into account to avoid deny of service attack and fruitless workloads, whose requesters are disconnected at the time of completion. Our evaluation shows that the costperformance ratio of the middle-ware is the best among all the compared algorithms. To be specific, the cost-performance of the developed algorithm can be at least two times better than that of compared algorithms.
The classical portfolio problem is a problem of distributing capital to a set of securities. By generalizing the set of securities to a set of investment strategies (or security-rule pairs), this study proposes an inv...
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ISBN:
(纸本)0769528759
The classical portfolio problem is a problem of distributing capital to a set of securities. By generalizing the set of securities to a set of investment strategies (or security-rule pairs), this study proposes an investment strategy portfolio problem, which becomes a problem of distributing capital to a set of investment strategies. Since the investment strategy portfolio problem can be formulated as a combination optimization problem, a new combination genetic algorithm is proposed for solving the new investment strategy portfolio problem. Experimental results show that the idea of investment strategy portfolios is feasible and the combination genetic algorithm is effective on the investment strategy portfolio problem.
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