1,167 research outputs found
Vertex similarity in networks
We consider methods for quantifying the similarity of vertices in networks.
We propose a measure of similarity based on the concept that two vertices are
similar if their immediate neighbors in the network are themselves similar.
This leads to a self-consistent matrix formulation of similarity that can be
evaluated iteratively using only a knowledge of the adjacency matrix of the
network. We test our similarity measure on computer-generated networks for
which the expected results are known, and on a number of real-world networks
Visualising the structure of document search results: A comparison of graph theoretic approaches
This is the post-print of the article - Copyright @ 2010 Sage PublicationsPrevious work has shown that distance-similarity visualisation or âspatialisationâ can provide a potentially useful context in which to browse the results of a query search, enabling the user to adopt a simple local foraging or âcluster growingâ strategy to navigate through the retrieved document set. However, faithfully mapping feature-space models to visual space can be problematic owing to their inherent high dimensionality and non-linearity. Conventional linear approaches to dimension reduction tend to fail at this kind of task, sacrificing local structural in order to preserve a globally optimal mapping. In this paper the clustering performance of a recently proposed algorithm called isometric feature mapping (Isomap), which deals with non-linearity by transforming dissimilarities into geodesic distances, is compared to that of non-metric multidimensional scaling (MDS). Various graph pruning methods, for geodesic distance estimation, are also compared. Results show that Isomap is significantly better at preserving local structural detail than MDS, suggesting it is better suited to cluster growing and other semantic navigation tasks. Moreover, it is shown that applying a minimum-cost graph pruning criterion can provide a parameter-free alternative to the traditional K-neighbour method, resulting in spatial clustering that is equivalent to or better than that achieved using an optimal-K criterion
Monitoramento de parùmetros microbiológicos em sistemas de produção agropecuåria.
JIPE 2013
InfluĂȘncia de sistemas de integração lavoura-pecuĂĄria-floresta sobre a biomassa microbiana do solo.
JIPE 2013
SECaps: A Sequence Enhanced Capsule Model for Charge Prediction
Automatic charge prediction aims to predict appropriate final charges
according to the fact descriptions for a given criminal case. Automatic charge
prediction plays a critical role in assisting judges and lawyers to improve the
efficiency of legal decisions, and thus has received much attention.
Nevertheless, most existing works on automatic charge prediction perform
adequately on high-frequency charges but are not yet capable of predicting
few-shot charges with limited cases. In this paper, we propose a Sequence
Enhanced Capsule model, dubbed as SECaps model, to relieve this problem.
Specifically, following the work of capsule networks, we propose the seq-caps
layer, which considers sequence information and spatial information of legal
texts simultaneously. Then we design a attention residual unit, which provides
auxiliary information for charge prediction. In addition, our SECaps model
introduces focal loss, which relieves the problem of imbalanced charges.
Comparing the state-of-the-art methods, our SECaps model obtains 4.5% and 6.4%
absolutely considerable improvements under Macro F1 in Criminal-S and
Criminal-L respectively. The experimental results consistently demonstrate the
superiorities and competitiveness of our proposed model.Comment: 13 pages, 3figures, 5 table
Indicadores microbiológicos para avaliação da qualidade do solo em diferentes sistemas de integração lavoura-pecuåria-floresta.
A multi-layered Bayesian network model for structured document retrieval
New standards in document representation, like for example SGML, XML, and MPEG-7, compel Information Retrieval to design and implement models and tools to index, retrieve and present documents according to the given document structure. The paper presents the design of an Information Retrieval system for multimedia structured documents, like for example journal articles, e-books, and MPEG-7 videos. The system is based on Bayesian Networks, since this class of mathematical models enable to represent and quantify the relations between the structural components of the document. Some preliminary results on the system implementation are also presented
Long-term soil microbial biomass in conventional tillage, no tillage and crop-livestock systems.
Imaging review of the lung parenchymal complications in patients with IPF
Idiopathic pulmonary fibrosis (IPF) is a chronic, pulmonary-limited, interstitial lung disease with a poor prognosis. This condition is characterized by different clinical scenarios, ranging from the most typical slow and progressive deterioration of symptoms to a rapid and abrupt decline of lung function. Rapid worsening of clinical course is due to superimposed complications and comorbidities that can develop in IPF patients, with a higher incidence rate compared to the general population. These conditions may require a different management of the patient and a therapy adjustment, and thus it is fundamental to recognize them. High Resolution Computed Tomography (HRCT) is sensitive, but not specific, in detecting these complications, and can evaluate the presence of radiological variations when previous examinations are available; it recognizes ground glass opacities or consolidation that can be related to a large spectrum of comorbidities, such as infection, lung cancer, or acute exacerbation. To reach the final diagnosis, a multidisciplinary discussion is required, particularly when the clinical context is related to imaging findings
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