Flexible constrained sampling with guarantees for pattern mining

Pattern sampling has been proposed as a potential solution to the infamous pattern explosion. Instead of enumerating all patterns that satisfy the constraints, individual patterns are sampled proportional to a given quality measure. Several sampling algorithms have been proposed, but each of them has its limitations when it comes to 1) flexibility in terms of quality measures and constraints that can be used, and/or 2) guarantees with respect to sampling accuracy. We therefore present Flexics, the first flexible pattern sampler that supports a broad class of quality measures and constraints, while providing strong guarantees regarding sampling accuracy. To achieve this, we leverage the perspective on pattern mining as a constraint satisfaction problem and build upon the latest advances in sampling solutions in SAT as well as existing pattern mining algorithms. Furthermore, the proposed algorithm is applicable to a variety of pattern languages, which allows us to introduce and tackle the novel task of sampling sets of patterns. We introduce and empirically evaluate two variants of Flexics: 1) a generic variant that addresses the well-known itemset sampling task and the novel pattern set sampling task as well as a wide range of expressive constraints within these tasks, and 2) a specialized variant that exploits existing frequent itemset techniques to achieve substantial speed-ups. Experiments show that Flexics is both accurate and efficient, making it a useful tool for pattern-based data exploration.Comment: Accepted for publication in Data Mining & Knowledge Discovery journal (ECML/PKDD 2017 journal track

The success-index: an alternative approach to the h-index for evaluating an individual's research output

Among the most recent bibliometric indicators for normalizing the differences among fields of science in terms of citation behaviour, Kosmulski (J Informetr 5(3):481-485, 2011) proposed the NSP (number of successful paper) index. According to the authors, NSP deserves much attention for its great simplicity and immediate meaning— equivalent to those of the h-index—while it has the disadvantage of being prone to manipulation and not very efficient in terms of statistical significance. In the first part of the paper, we introduce the success-index, aimed at reducing the NSP-index's limitations, although requiring more computing effort. Next, we present a detailed analysis of the success-index from the point of view of its operational properties and a comparison with the h-index's ones. Particularly interesting is the examination of the success-index scale of measurement, which is much richer than the h-index's. This makes success-index much more versatile for different types of analysis—e.g., (cross-field) comparisons of the scientific output of (1) individual researchers, (2) researchers with different seniority, (3) research institutions of different size, (4) scientific journals, etc

An index to quantify an individual's scientific research output that takes into account the effect of multiple coauthorship

I propose the index $\hbar$ ("hbar"), defined as the number of papers of an individual that have citation count larger than or equal to the $\hbar$ of all coauthors of each paper, as a useful index to characterize the scientific output of a researcher that takes into account the effect of multiple coauthorship. The bar is higher for $\hbar$.Comment: A few minor changes from v1. To be published in Scientometric

The hw-rank: an h-index variant for ranking web pages

We introduce a novel ranking of search results based on a variant of the h-index for directed information networks such as the Web. The h-index was originally introduced to measure an individual researcher’s scientific output and influence, but here a variant of it is applied to assess the ‘‘importance’’ of web pages. Like PageRank, the‘‘importance’’ of a page is defined by the ‘‘importance’’ of the pages linking to it. However, unlike the computation of PageRank which involves the whole web graph, computing the h-index for web pages (the hw-rank) is based on a local computation and only the neighbors of the neighbors of the given node are considered. Preliminary results show a strong correlation between ranking with the hw-rank and PageRank, and moreover its computation is simpler and less complex than computation of the PageRank. Further, larger scale experiments are needed in order to assess the applicability of the method

Statistical regularities in the rank-citation profile of scientists

Recent science of science research shows that scientific impact measures for journals and individual articles have quantifiable regularities across both time and discipline. However, little is known about the scientific impact distribution at the scale of an individual scientist. We analyze the aggregate production and impact using the rank-citation profile ci(r) of 200 distinguished professors and 100 assistant professors. For the entire range of paper rank r, we fit each ci(r) to a common distribution function. Since two scientists with equivalent Hirsch h-index can have significantly different ci(r) profiles, our results demonstrate the utility of the βi scaling parameter in conjunction with hi for quantifying individual publication impact. We show that the total number of citations Ci tallied from a scientist's Ni papers scales as . Such statistical regularities in the input-output patterns of scientists can be used as benchmarks for theoretical models of career progress

Natural disasters and indicators of social cohesion

Do adversarial environmental conditions create social cohesion? We provide new answers to this question by exploiting spatial and temporal variation in exposure to earthquakes across Chile. Using a variety of methods and controlling for a number of socio-economic variables, we find that exposure to earthquakes has a positive effect on several indicators of social cohesion. Social cohesion increases after a big earthquake and slowly erodes in periods where environmental conditions are less adverse. Our results contribute to the current debate on whether and how environmental conditions shape formal and informal institutions

A Measurement of Gravitational Lensing of the Cosmic Microwave Background Using SPT-3G 2018 Data

We present a measurement of gravitational lensing over 1500 deg$^2$ of the Southern sky using SPT-3G temperature data at 95 and 150 GHz taken in 2018. The lensing amplitude relative to a fiducial Planck 2018 $\Lambda$CDM cosmology is found to be $1.020\pm0.060$, excluding instrumental and astrophysical systematic uncertainties. We conduct extensive systematic and null tests to check the robustness of the lensing measurements, and report a minimum-variance combined lensing power spectrum over angular multipoles of $50<L<2000$, which we use to constrain cosmological models. When analyzed alone and jointly with primary cosmic microwave background (CMB) spectra within the $\Lambda$CDM model, our lensing amplitude measurements are consistent with measurements from SPT-SZ, SPTpol, ACT, and Planck. Incorporating loose priors on the baryon density and other parameters including uncertainties on a foreground bias template, we obtain a $1\sigma$ constraint on $\sigma_8 \Omega_{\rm m}^{0.25}=0.595 \pm 0.026$ using the SPT-3G 2018 lensing data alone, where $\sigma_8$ is a common measure of the amplitude of structure today and $\Omega_{\rm m}$ is the matter density parameter. Combining SPT-3G 2018 lensing measurements with baryon acoustic oscillation (BAO) data, we derive parameter constraints of $\sigma_8 = 0.810 \pm 0.033$, $S_8 \equiv \sigma_8(\Omega_{\rm m}/0.3)^{0.5}= 0.836 \pm 0.039$, and Hubble constant $H_0 =68.8^{+1.3}_{-1.6}$ km s$^{-1}$ Mpc$^{-1}$. Using CMB anisotropy and lensing measurements from SPT-3G only, we provide independent constraints on the spatial curvature of $\Omega_{K} = 0.014^{+0.023}_{-0.026}$ (95% C.L.) and the dark energy density of $\Omega_\Lambda = 0.722^{+0.031}_{-0.026}$ (68% C.L.). When combining SPT-3G lensing data with SPT-3G CMB anisotropy and BAO data, we find an upper limit on the sum of the neutrino masses of $\sum m_{\nu}< 0.30$ eV (95% C.L.)