3,973 research outputs found
A network approach to topic models
One of the main computational and scientific challenges in the modern age is
to extract useful information from unstructured texts. Topic models are one
popular machine-learning approach which infers the latent topical structure of
a collection of documents. Despite their success --- in particular of its most
widely used variant called Latent Dirichlet Allocation (LDA) --- and numerous
applications in sociology, history, and linguistics, topic models are known to
suffer from severe conceptual and practical problems, e.g. a lack of
justification for the Bayesian priors, discrepancies with statistical
properties of real texts, and the inability to properly choose the number of
topics. Here we obtain a fresh view on the problem of identifying topical
structures by relating it to the problem of finding communities in complex
networks. This is achieved by representing text corpora as bipartite networks
of documents and words. By adapting existing community-detection methods --
using a stochastic block model (SBM) with non-parametric priors -- we obtain a
more versatile and principled framework for topic modeling (e.g., it
automatically detects the number of topics and hierarchically clusters both the
words and documents). The analysis of artificial and real corpora demonstrates
that our SBM approach leads to better topic models than LDA in terms of
statistical model selection. More importantly, our work shows how to formally
relate methods from community detection and topic modeling, opening the
possibility of cross-fertilization between these two fields.Comment: 22 pages, 10 figures, code available at https://topsbm.github.io
Sampling motif-constrained ensembles of networks
The statistical significance of network properties is conditioned on null
models which satisfy spec- ified properties but that are otherwise random.
Exponential random graph models are a principled theoretical framework to
generate such constrained ensembles, but which often fail in practice, either
due to model inconsistency, or due to the impossibility to sample networks from
them. These problems affect the important case of networks with prescribed
clustering coefficient or number of small connected subgraphs (motifs). In this
paper we use the Wang-Landau method to obtain a multicanonical sampling that
overcomes both these problems. We sample, in polynomial time, net- works with
arbitrary degree sequences from ensembles with imposed motifs counts. Applying
this method to social networks, we investigate the relation between
transitivity and homophily, and we quantify the correlation between different
types of motifs, finding that single motifs can explain up to 60% of the
variation of motif profiles.Comment: Updated version, as published in the journal. 7 pages, 5 figures, one
Supplemental Materia
Trajectories in a space with a spherically symmetric dislocation
We consider a new type of defect in the scope of linear elasticity theory,
using geometrical methods. This defect is produced by a spherically symmetric
dislocation, or ball dislocation. We derive the induced metric as well as the
affine connections and curvature tensors. Since the induced metric is
discontinuous, one can expect ambiguity coming from these quantities, due to
products between delta functions or its derivatives, plaguing a description of
ball dislocations based on the Geometric Theory of Defects. However, exactly as
in the previous case of cylindric defect, one can obtain some well-defined
physical predictions of the induced geometry. In particular, we explore some
properties of test particle trajectories around the defect and show that these
trajectories are curved but can not be circular orbits.Comment: 11 pages, 3 figure
Comparative study of the performance of different anodic materials in a microbial fuel cell inoculated with Geobacter sulfurreducens
Symmetry aspects of fermions coupled to torsion and electromagnetic fields
We study and explore the symmetry properties of fermions coupled to dynamical
torsion and electromagnetic fields. The stability of the theory upon radiative
corrections as well as the presence of anomalies are investigated.Comment: 9 pages, LaTe
Caracterização de abóboras quanto aos teores carotenóides totais, alfa e beta-caroteno.
Esse trabalho teve como objetivo caracterizar variedades locais de abóboras de diferentes origens para os teores de carotenóides totais, alfa e beta caroteno.bitstream/item/57215/1/BPD-78.pd
Distribution of epicenters in the Olami-Feder-Christensen model
We show that the well established Olami-Feder-Christensen (OFC) model for the
dynamics of earthquakes is able to reproduce a new striking property of real
earthquake data. Recently, it has been pointed out by Abe and Suzuki that the
epicenters of earthquakes could be connected in order to generate a graph, with
properties of a scale-free network of the Barabasi-Albert type. However, only
the non conservative version of the Olami-Feder-Christensen model is able to
reproduce this behavior. The conservative version, instead, behaves like a
random graph. Besides indicating the robustness of the model to describe
earthquake dynamics, those findings reinforce that conservative and non
conservative versions of the OFC model are qualitatively different. Also, we
propose a completely new dynamical mechanism that, even without an explicit
rule of preferential attachment, generates a free scale network. The
preferential attachment is in this case a ``by-product'' of the long term
correlations associated with the self-organized critical state. The detailed
study of the properties of this network can reveal new aspects of the dynamics
of the OFC model, contributing to the understanding of self-organized
criticality in non conserving models.Comment: 7 pages, 7 figure
Divergência genética entre acessos de batata-doce utilizando descritores morfoagronômicos das raÃzes.
Objetivou-se caracterizar morfoagronômicamente 23 genótipos de batata-doce do banco ativo de germoplasma mantido na Embrapa Hortaliças; utilizar estas caracterÃsticas para avaliar a variabilidade genética entre os materiais pela aplicação dos métodos de Análise por agrupamento hierárquico e análise por componentes principais e estimar parâmetros populacionais
Superdiffusion of massive particles induced by multi-scale velocity fields
We study drag-induced diffusion of massive particles in scale-free velocity
fields, where superdiffusive behavior emerges due to the scale-free size
distribution of the vortices of the underlying velocity field. The results show
qualitative resemblance to what is observed in fluid systems, namely the
diffusive exponent for the mean square separation of pairs of particles and the
preferential concentration of the particles, both as a function of the response
time.Comment: 5 pages, 5 figures. Accepted for publication in EP
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