163,191 research outputs found
On the efficiency of estimating penetrating rank on large graphs
P-Rank (Penetrating Rank) has been suggested as a useful measure of structural similarity that takes account of both incoming and outgoing edges in ubiquitous networks. Existing work often utilizes memoization to compute P-Rank similarity in an iterative fashion, which requires cubic time in the worst case. Besides, previous methods mainly focus on the deterministic computation of P-Rank, but lack the probabilistic framework that scales well for large graphs. In this paper, we propose two efficient algorithms for computing P-Rank on large graphs. The first observation is that a large body of objects in a real graph usually share similar neighborhood structures. By merging such objects with an explicit low-rank factorization, we devise a deterministic algorithm to compute P-Rank in quadratic time. The second observation is that by converting the iterative form of P-Rank into a matrix power series form, we can leverage the random sampling approach to probabilistically compute P-Rank in linear time with provable accuracy guarantees. The empirical results on both real and synthetic datasets show that our approaches achieve high time efficiency with controlled error and outperform the baseline algorithms by at least one order of magnitude
Towards efficient SimRank computation on large networks
SimRank has been a powerful model for assessing the similarity of pairs of vertices in a graph. It is based on the concept that two vertices are similar if they are referenced by similar vertices. Due to its self-referentiality, fast SimRank computation on large graphs poses significant challenges. The state-of-the-art work [17] exploits partial sums memorization for computing SimRank in O(Kmn) time on a graph with n vertices and m edges, where K is the number of iterations. Partial sums memorizing can reduce repeated calculations by caching part of similarity summations for later reuse. However, we observe that computations among different partial sums may have duplicate redundancy. Besides, for a desired accuracy ϵ, the existing SimRank model requires K = [logC ϵ] iterations [17], where C is a damping factor. Nevertheless, such a geometric rate of convergence is slow in practice if a high accuracy is desirable. In this paper, we address these gaps. (1) We propose an adaptive clustering strategy to eliminate partial sums redundancy (i.e., duplicate computations occurring in partial sums), and devise an efficient algorithm for speeding up the computation of SimRank to 0(Kdn2) time, where d is typically much smaller than the average in-degree of a graph. (2) We also present a new notion of SimRank that is based on a differential equation and can be represented as an exponential sum of transition matrices, as opposed to the geometric sum of the conventional counterpart. This leads to a further speedup in the convergence rate of SimRank iterations. (3) Using real and synthetic data, we empirically verify that our approach of partial sums sharing outperforms the best known algorithm by up to one order of magnitude, and that our revised notion of SimRank further achieves a 5X speedup on large graphs while also fairly preserving the relative order of original SimRank scores
Dibaryons with two heavy quarks
The relativistic six-quark equations are constructed in the framework of the
dispersion relation technique. The relativistic six-quark amplitudes of
dibaryons including the light , and heavy , quarks are
calculated. The approximate solutions of these equations using the method based
on the extraction of leading singularities of the heavy hexaquark amplitudes
are obtained. The poles of these amplitudes determine the masses of charmed and
bottom dibaryons with the isospins I=0, 1, 2 and the spin-parities ,
, .Comment: 10 pages, types corrected. arXiv admin note: substantial text overlap
with arXiv:1105.081
Using XMM-Newton to study the energy dependent variability of H 1743-322 during its 2014 outburst
Black hole transients during bright outbursts show distinct changes of their
spectral and variability properties as they evolve during an outburst, that are
interpreted as evidence for changes in the accretion flow and X-ray emitting
regions. We obtained an anticipated XMM-Newton ToO observation of H 1743-322
during its outburst in September 2014. Based on data of eight outbursts
observed in the last 10 years we expected to catch the start of the
hard-to-soft state transition. The fact that neither the general shape of the
observed power density spectrum nor the characteristic frequency show an energy
dependence implies that the source still stays in the low-hard state at the
time of our observation near outburst peak. The spectral properties agree with
the source being in the low-hard state and a Swift/XRT monitoring of the
outburst reveals that H 1743-322 stays in the low-hard state during the entire
outburst (a. k. a. 'failed outburst'). We derive the averaged QPO waveform and
obtain phase-resolved spectra. Comparing the phase-resolved spectra to the
phase averaged energy spectrum reveals spectral pivoting. We compare
variability on long and short time scales using covariance spectra and find
that the covariance ratio does not show an increase towards lower energies as
has been found in other black hole X-ray binaries. There are two possible
explanations: either the absence of additional disc variability on longer time
scales is related to the rather high inclination of H 1743-322 compared to
other black hole X-ray binaries or it is the reason why we observe H 1743-322
during a failed outburst. More data on failed outbursts and on high-inclination
sources will be needed to investigate these two possibilities further.Comment: 9 pages, 7 figures, accepted by MNRA
Comparing two haptic interfaces for multimodal graph rendering
This paper describes the evaluation of two multimodal interfaces designed to provide visually impaired people with access to various types of graphs. The interfaces consist of audio and haptics which is rendered on commercially available force feedback devices. This study compares the usability of two force feedback devices: the SensAble PHANToM and the Logitech WingMan force feedback mouse in representing graphical data. The type of graph used in the experiment is the bar chart under two experimental conditions: single mode and multimodal. The results show that PHANToM provides better performance in the haptic only condition. However, no significant difference has been found between the two devices in the multimodal condition. This has confirmed the advantages of using multimodal approach in our research and that low-cost haptic devices can be successful. This paper introduces our evaluation approach and discusses the findings of the experiment
Gauging Correct Relative Rankings For Similarity Search
© 2015 ACM.One of the important tasks in link analysis is to quantify the similarity between two objects based on hyperlink structure. SimRank is an attractive similarity measure of this type. Existing work mainly focuses on absolute SimRank scores, and often harnesses an iterative paradigm to compute them. While these iterative scores converge to exact ones with the increasing number of iterations, it is still notoriously difficult to determine how well the relative orders of these iterative scores can be preserved for a given iteration. In this paper, we propose efficient ranking criteria that can secure correct relative orders of node-pairs with respect to SimRank scores when they are computed in an iterative fashion. Moreover, we show the superiority of our criteria in harvesting top-K SimRank scores and bucket orders from a full ranking list. Finally, viable empirical studies verify the usefulness of our techniques for SimRank top-K ranking and bucket ordering
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