2,005 research outputs found

    Citation Counts and Evaluation of Researchers in the Internet Age

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    Bibliometric measures derived from citation counts are increasingly being used as a research evaluation tool. Their strengths and weaknesses have been widely analyzed in the literature and are often subject of vigorous debate. We believe there are a few fundamental issues related to the impact of the web that are not taken into account with the importance they deserve. We focus on evaluation of researchers, but several of our arguments may be applied also to evaluation of research institutions as well as of journals and conferences.Comment: 4 pages, 2 figures, 3 table

    A Faster Distributed Single-Source Shortest Paths Algorithm

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    We devise new algorithms for the single-source shortest paths (SSSP) problem with non-negative edge weights in the CONGEST model of distributed computing. While close-to-optimal solutions, in terms of the number of rounds spent by the algorithm, have recently been developed for computing SSSP approximately, the fastest known exact algorithms are still far away from matching the lower bound of Ω~(n+D) \tilde \Omega (\sqrt{n} + D) rounds by Peleg and Rubinovich [SIAM Journal on Computing 2000], where n n is the number of nodes in the network and D D is its diameter. The state of the art is Elkin's randomized algorithm [STOC 2017] that performs O~(n2/3D1/3+n5/6) \tilde O(n^{2/3} D^{1/3} + n^{5/6}) rounds. We significantly improve upon this upper bound with our two new randomized algorithms for polynomially bounded integer edge weights, the first performing O~(nD) \tilde O (\sqrt{n D}) rounds and the second performing O~(nD1/4+n3/5+D) \tilde O (\sqrt{n} D^{1/4} + n^{3/5} + D) rounds. Our bounds also compare favorably to the independent result by Ghaffari and Li [STOC 2018]. As side results, we obtain a (1+ϵ) (1 + \epsilon) -approximation O~((nD1/4+D)/ϵ) \tilde O ((\sqrt{n} D^{1/4} + D) / \epsilon) -round algorithm for directed SSSP and a new work/depth trade-off for exact SSSP on directed graphs in the PRAM model.Comment: Presented at the the 59th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2018

    Linear-Space Approximate Distance Oracles for Planar, Bounded-Genus, and Minor-Free Graphs

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    A (1 + eps)-approximate distance oracle for a graph is a data structure that supports approximate point-to-point shortest-path-distance queries. The most relevant measures for a distance-oracle construction are: space, query time, and preprocessing time. There are strong distance-oracle constructions known for planar graphs (Thorup, JACM'04) and, subsequently, minor-excluded graphs (Abraham and Gavoille, PODC'06). However, these require Omega(eps^{-1} n lg n) space for n-node graphs. We argue that a very low space requirement is essential. Since modern computer architectures involve hierarchical memory (caches, primary memory, secondary memory), a high memory requirement in effect may greatly increase the actual running time. Moreover, we would like data structures that can be deployed on small mobile devices, such as handhelds, which have relatively small primary memory. In this paper, for planar graphs, bounded-genus graphs, and minor-excluded graphs we give distance-oracle constructions that require only O(n) space. The big O hides only a fixed constant, independent of \epsilon and independent of genus or size of an excluded minor. The preprocessing times for our distance oracle are also faster than those for the previously known constructions. For planar graphs, the preprocessing time is O(n lg^2 n). However, our constructions have slower query times. For planar graphs, the query time is O(eps^{-2} lg^2 n). For our linear-space results, we can in fact ensure, for any delta > 0, that the space required is only 1 + delta times the space required just to represent the graph itself
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