Metrics for Graph Comparison: A Practitioner's Guide

Comparison of graph structure is a ubiquitous task in data analysis and machine learning, with diverse applications in fields such as neuroscience, cyber security, social network analysis, and bioinformatics, among others. Discovery and comparison of structures such as modular communities, rich clubs, hubs, and trees in data in these fields yields insight into the generative mechanisms and functional properties of the graph. Often, two graphs are compared via a pairwise distance measure, with a small distance indicating structural similarity and vice versa. Common choices include spectral distances (also known as $\lambda$ distances) and distances based on node affinities. However, there has of yet been no comparative study of the efficacy of these distance measures in discerning between common graph topologies and different structural scales. In this work, we compare commonly used graph metrics and distance measures, and demonstrate their ability to discern between common topological features found in both random graph models and empirical datasets. We put forward a multi-scale picture of graph structure, in which the effect of global and local structure upon the distance measures is considered. We make recommendations on the applicability of different distance measures to empirical graph data problem based on this multi-scale view. Finally, we introduce the Python library NetComp which implements the graph distances used in this work

On the construction of probabilistic Newton-type algorithms

It has recently been shown that many of the existing quasi-Newton algorithms can be formulated as learning algorithms, capable of learning local models of the cost functions. Importantly, this understanding allows us to safely start assembling probabilistic Newton-type algorithms, applicable in situations where we only have access to noisy observations of the cost function and its derivatives. This is where our interest lies. We make contributions to the use of the non-parametric and probabilistic Gaussian process models in solving these stochastic optimisation problems. Specifically, we present a new algorithm that unites these approximations together with recent probabilistic line search routines to deliver a probabilistic quasi-Newton approach. We also show that the probabilistic optimisation algorithms deliver promising results on challenging nonlinear system identification problems where the very nature of the problem is such that we can only access the cost function and its derivative via noisy observations, since there are no closed-form expressions available

Towards business integration as a service 2.0 (BIaaS 2.0)

Cloud Computing Business Framework (CCBF) is a framework for designing and implementation of Could Computing solutions. This proposal focuses on how CCBF can help to address linkage in Cloud Computing implementations. This leads to the development of Business Integration as a Service 1.0 (BIaaS 1.0) allowing different services, roles and functionalities to work together in a linkage-oriented framework where the outcome of one service can be input to another, without the need to translate between domains or languages. BIaaS 2.0 aims to allow automation, enhanced security, advanced risk modelling and improved collaboration between processes in BIaaS 1.0. The benefits from adopting BIaaS 1.0 and developing BIaaS 2.0 are illustrated using a case study from the University of Southampton and several collaborators including IBM US. BIaaS 2.0 can work with mainstream technologies such as scientific workflows, and the proposal and demonstration of BIaaS 2.0 will be aimed to certainly benefit industry and academia. © 2011 IEEE

Inelastic neutron scattering studies of the quantum frustrated magnet clinoatacamite, γ\gamma-Cu2(OD)3Cl, a proposed valence bond solid (VBS)

The frustrated magnet clinoatacamite, $\gamma$-Cu$_2$(OH)$_3$Cl, is attracting a lot of interest after suggestions that at low temperature it forms an exotic quantum state termed a Valence Bond Solid (VBS) made from dimerised Cu$^{2+}$ ($S=1/2$) spins.\cite{Lee_clinoatacamite} Key to the arguments surrounding this proposal were suggestions that the kagom\'e planes in the magnetic pyrochlore lattice of clinoatacamite are only weakly coupled, causing the system to behave as a quasi-2-dimensional magnet. This was reasoned from the near 95$^\circ$ angles made at the bridging oxygens that mediate exchange between the Cu ions that link the kagom\'e planes. Recent work pointed out that this exchange model is inappropriate for $\gamma$-Cu$_2$(OH)$_3$Cl, where the oxygen is present as a $\mu_3$-OH.\cite{Wills_JPC} Further, it used symmetry calculations and neutron powder diffraction to show that the low temperature magnetic structure ($T<6$ K) was canted and involved significant spin ordering on all the Cu$^{2+}$ spins, which is incompatible with the interpretation of simultaneous VBS and N\'eel ordering. Correspondingly, clinoatacamite is best considered a distorted pyrochlore magnet. In this report we show detailed inelastic neutron scattering spectra and revisit the responses of this frustrated quantum magnet.Comment: Proceedings of The International Conference on Highly Frustrated Magnetism 2008 (HFM2008

Providing value to a business using a lightweight design system to support knowledge reuse by designers

This paper describes an alternative approach to knowledge based systems in engineering than traditional geometry or explicit knowledge focused systems. Past systems have supported product optimisation rather than creative solutions and provide little benefit to businesses for bespoke and low volume products or products which do not benefit from optimisation. The approach here addresses this by supporting the creativity of designers through codified tacit knowledge and encouraging knowledge reuse for bespoke product development, in particular for small to medium sized enterprises. The implementation and evaluation of the approach is described within a company producing bespoke fixtures and tooling in shorter than average lead times. The active support of knowledge management in the company is intended to add value to the business by further reducing the lead times of the designs and creating a positive impact to business processes. The evaluation demonstrates a viable alternative framework to the traditional management of knowledge in engineering, which could be implemented by other small to medium enterprises

Pseudo-half-metalicity in the double perovskite Sr2_2CrReO6_6 from density-functional calculations

The electronic structure of the spintronic material Sr$_2$CrReO$_6$ is studied by means of full-potential linear muffin-tin orbital method. Scalar relativistic calculations predict Sr$_2$CrReO$_6$ to be half-metallic with a magnetic moment of 1 $\mu_B$. When spin-orbit coupling is included, the half-metallic gap closes into a pseudo-gap, and an unquenched rhenium orbital moment appears, resulting in a significant increase of the total magnetic moment to 1.28 $\mu_B$. This moment is significantly larger than the experimental moment of 0.9 $\mu_B$. A possible explanation of this discrepancy is that the anti-site disorder in Sr$_2$CrReO$_6$ is significantly larger than hitherto assumed.Comment: 3 Pages, 1 figure, 1 Tabl

Expert Finding by Capturing Organisational Knowledge from Legacy Documents

Organisations capitalise on their best knowledge through the improvement of shared expertise which leads to a higher level of productivity and competency. The recognition of the need to foster the sharing of expertise has led to the development of expert finder systems that hold pointers to experts who posses specific knowledge in organisations. This paper discusses an approach to locating an expert through the application of information retrieval and analysis processes to an organization’s existing information resources, with specific reference to the engineering design domain. The approach taken was realised through an expert finder system framework. It enables the relationships of heterogeneous information sources with experts to be factored in modelling individuals’ expertise. These valuable relationships are typically ignored by existing expert finder systems, which only focus on how documents relate to their content. The developed framework also provides an architecture that can be easily adapted to different organisational environments. In addition, it also allows users to access the expertise recognition logic, giving them greater trust in the systems implemented using this framework. The framework were applied to real world application and evaluated within a major engineering company