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48
Statistical approaches to computerassisted translation,” Computational Linguistics, p
, 2008
"... Current machine translation (MT) systems are still not perfect. In practice, the output from these systems needs to be edited to correct errors. A way of increasing the productivity of the whole translation process (MT plus human work) is to incorporate the human correction activities within the tra ..."
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Cited by 35 (14 self)
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Current machine translation (MT) systems are still not perfect. In practice, the output from these systems needs to be edited to correct errors. A way of increasing the productivity of the whole translation process (MT plus human work) is to incorporate the human correction activities within the translation process itself, thereby shifting the MT paradigm to that of computerassisted translation. This model entails an iterative process in which the human translator activity is included in the loop: In each iteration, a prefix of the translation is validated (accepted or amended) by the human and the system computes its best (or nbest) translation suffix hypothesis to complete this prefix. A successful framework for MT is the socalled statistical (or pattern recognition) framework. Interestingly, within this framework, the adaptation of MT systems to the interactive scenario affects mainly the search process, allowing a great reuse of successful techniques and models. In this article, alignment templates, phrasebased models, and stochastic finitestate transducers are used to develop computerassisted translation systems. These systems were assessed in a European project (TransType2) in two real tasks: The translation of printer manuals; manuals and the translation of the Bulletin of the European Union. In each task, the following three pairs of languages were involved (in both translation
B.: Counterexample generation in probabilistic model checking
 IEEE Trans. on Software Engineering
"... Abstract—Providing evidence for the refutation of a property is an essential, if not the most important, feature of model checking. This paper considers algorithms for counterexample generation for probabilistic CTL formulas in discretetime Markov chains. Finding the strongest evidence (i.e., the m ..."
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Abstract—Providing evidence for the refutation of a property is an essential, if not the most important, feature of model checking. This paper considers algorithms for counterexample generation for probabilistic CTL formulas in discretetime Markov chains. Finding the strongest evidence (i.e., the most probable path) violating a (bounded) untilformula is shown to be reducible to a singlesource (hopconstrained) shortest path problem. Counterexamples of smallest size that deviate most from the required probability bound can be obtained by applying (small amendments to) kshortest (hopconstrained) paths algorithms. These results can be extended to Markov chains with rewards, to LTL model checking, and are useful for Markov decision processes. Experimental results show that, typically, the size of a counterexample is excessive. To obtain much more compact representations, we present a simple algorithm to generate (minimal) regular expressions that can act as counterexamples. The feasibility of our approach is illustrated by means of two communication protocols: leader election in an anonymous ring network and the Crowds protocol. Index Terms—Diagnostic feedback, Markov chain, model checking, regular expression, shortest path. Ç 1
J.P.: Counterexamples in probabilistic model checking
 In: Tools and Algorithms for the Construction and Analysis of Systems (TACAS), 13th International Conference. (2007
"... ..."
Provisioning virtual private networks under traffic uncertainty
 Networks
, 2004
"... We investigate a network design problem under traffic uncertainty which arises when provisioning Virtual Private Networks (VPNs): given a set of terminals that must communicate with one another, and a set of possible traffic matrices, sufficient capacity has to be reserved on the links of the large ..."
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We investigate a network design problem under traffic uncertainty which arises when provisioning Virtual Private Networks (VPNs): given a set of terminals that must communicate with one another, and a set of possible traffic matrices, sufficient capacity has to be reserved on the links of the large underlying public network so as to support all possible traffic matrices while minimizing the total reservation cost. The problem admits several variants depending on the desired topology of the reserved links, and the nature of the traffic data uncertainty. We present compact linear mixedinteger programming formulations for the problem with the classical hose traffic model and for a new, less conservative, robust variant relying on the traffic statistics that are often available. These flowbased formulations allow to solve optimally mediumtolargesize instances with commercial MIP solvers. We also propose a combined branchandprice and cutting plane algorithm to tackle larger instances. Computational results obtained for several classes of instances are reported and discussed. Key words: Virtual private networks, network design, traffic uncertainty, robust optimization, linear mixedinteger programs, branchandprice, cutting planes. 1
NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways
 Nucleic Acids Res
, 2008
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Finding the k shortest hyperpaths
"... The K shortest paths problem has been extensively studied for many years. Efficient methods have been devised, and many practical applications are known. Shortest hyperpath models have been proposed for several problems in different areas, for example in relation with routing in dynamic networks. Ho ..."
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Cited by 19 (3 self)
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The K shortest paths problem has been extensively studied for many years. Efficient methods have been devised, and many practical applications are known. Shortest hyperpath models have been proposed for several problems in different areas, for example in relation with routing in dynamic networks. However, the K shortest hyperpaths problem has not yet been investigated. In this paper we present procedures for finding the K shortest hyperpaths in a directed hypergraph. This is done by extending existing algorithms for K shortest loopless paths. Computational experiments on the proposed procedures are performed, and applications in transportation, planning and combinatorial optimization are discussed.
From machine translation to computer assisted translation using finitestate models
 In Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing (EMNLP04
, 2004
"... Stateoftheart machine translation techniques are still far from producing high quality translations. This drawback leads us to introduce an alternative approach to the translation problem that brings human expertise into the machine translation scenario. In this framework, namely Computer Assiste ..."
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Stateoftheart machine translation techniques are still far from producing high quality translations. This drawback leads us to introduce an alternative approach to the translation problem that brings human expertise into the machine translation scenario. In this framework, namely Computer Assisted Translation (CAT), human translators interact with a translation system, as an assistance tool, that dinamically offers, a list of translations that best completes the part of the sentence already translated. In this paper, finite state transducers are presented as a candidate technology in the CAT paradigm. The appropriateness of this technique is evaluated on a printer manual corpus and results from preliminary experiments confirm that human translators would reduce to less than 25 % the amount of work to be done for the same task. 1
A lazy version of eppstein’s k shortest paths algorithm
 In: WEA
, 2003
"... Abstract. We consider the problem ofenumerating, in order ofincreasing length, the K shortest paths between a given pair ofnodes in a weighted digraph G with n nodes and m arcs. To solve this problem, Eppstein’s algorithm first computes the shortest path tree and then builds a graph D(G) representin ..."
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Abstract. We consider the problem ofenumerating, in order ofincreasing length, the K shortest paths between a given pair ofnodes in a weighted digraph G with n nodes and m arcs. To solve this problem, Eppstein’s algorithm first computes the shortest path tree and then builds a graph D(G) representing all possible deviations from the shortest path. Building D(G) takesO(m+n log n) time in the basic version ofthe algorithm. Once it has been built, the K shortest paths can be obtained in order ofincreasing length in O(K log K) time. However, experimental results show that the time required to build D(G) is considerable, thereby reducing the practical interest ofthe algorithm. In this paper, we propose a modified version ofEppstein’s algorithm in which only the parts of D(G) which are necessary for the selection of the K shortest paths are built. This version maintains Eppstein’s worstcase running time and entails an important improvement in practical performance, according to experimental results that are also reported here. 1
K : A heuristic search algorithm for finding the k shortest paths
 Artificial Intelligence
"... We present a directed search algorithm, called K ∗ , for finding the k shortest paths between a designated pair of vertices in a given directed weighted graph. K ∗ has two advantages compared to current kshortestpaths algorithms. First, K ∗ operates onthefly, which means that it does not require ..."
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We present a directed search algorithm, called K ∗ , for finding the k shortest paths between a designated pair of vertices in a given directed weighted graph. K ∗ has two advantages compared to current kshortestpaths algorithms. First, K ∗ operates onthefly, which means that it does not require the graph to be explicitly available and stored in main memory. Portions of the graph will be generated as needed. Second, K ∗ can be guided using heuristic functions. We prove the correctness of K ∗ and determine its asymptotic worstcase complexity when using a consistent heuristic to be the same as the state of the art, O(m + n log n + k), with respect to both runtime and space, where n is the number of vertices and m is the number of edges of the graph. We present an experimental evaluation of K ∗ by applying it to route planning problems as well as counterexample generation for stochastic model checking. The experimental results illustrate that due to the use of heuristic, onthefly search K ∗ can use less time and memory compared to the most efficient kshortestpaths algorithms known so far. Key words: kshortestpaths problem; K ∗ ; heuristic search; onthefly search 1.
D.: Finding nexttoshortest paths in a graph
 Inf. Process. Lett
, 2004
"... We study the problem of finding the nexttoshortest paths in a graph. A nexttoshortest (u, v)path is a shortest (u, v)path amongst (u, v)paths with length strictly greater than the length of the shortest (u, v)path. In constrast to the situation in directed graphs, where the problem has been ..."
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We study the problem of finding the nexttoshortest paths in a graph. A nexttoshortest (u, v)path is a shortest (u, v)path amongst (u, v)paths with length strictly greater than the length of the shortest (u, v)path. In constrast to the situation in directed graphs, where the problem has been shown to be NPhard, providing edges of length zero are allowed, we prove the somewhat surprising result that there is a polynomial time algorithm for the undirected version of the problem.