the proceedings contain 36 papers. the special focus in this conference is on graph-based Representation, graph Matching, graph Clustering and graph-based Applications. the topics include: Approximation of graph edit ...
ISBN:
(纸本)9783319182230
the proceedings contain 36 papers. the special focus in this conference is on graph-based Representation, graph Matching, graph Clustering and graph-based Applications. the topics include: Approximation of graph edit distance in quadratic time;data graph formulation as the minimum-weight maximum-entropy problem;an entropic edge assortativity measure;a subpath kernel for learning hierarchical image representations;coupled-feature hypergraph representation for feature selection;reeb graphs through local binary patterns;incremental embedding within a dissimilarity-based framework;a first step towards exact graph edit distance using bipartite graph matching;consensus of two graph correspondences through a generalisation of the bipartite graph matching;revisiting Volgenant-Jonker for approximating graph edit distance;a hypergraph matching framework for refining multi-source feature correspondences;a tool for solving substitution-tolerant subgraph isomorphism;a graph database repository and performance evaluation metrics for graph edit distance;learning graph model for different dimensions image matching;report on the first contest on graph matching algorithms for pattern search in biological databases;large-scale graph indexing using binary embeddings of node contexts;on the influence of node centralities on graph edit distance for graph classification;a quantum Jensen-Shannon graph kernel using discrete-time quantum walks;density based cluster extension and dominant sets clustering;salient object segmentation from stereoscopic images;causal video segmentation using superseeds and graph matching;fast minimum spanning tree based clustering algorithms on local neighborhood graph and graphbased lymphatic vessel wall localisation and tracking.
BackgroundMissing values frequently arise in modern biomedical studies due to various reasons, including missing tests or complex profiling technologies for different omics measurements. Missing values can complicate ...
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BackgroundMissing values frequently arise in modern biomedical studies due to various reasons, including missing tests or complex profiling technologies for different omics measurements. Missing values can complicate the application of clustering algorithms, whose goals are to group points based on some similarity criterion. A common practice for dealing with missing values in the context of clustering is to first impute the missing values, and then apply the clustering algorithm on the completed *** consider missing values in the context of optimal clustering, which finds an optimal clustering operator with reference to an underlying random labeled point process (RLPP). We show how the missing-value problem fits neatly into the overall framework of optimal clustering by incorporating the missing value mechanism into the random labeled point process and then marginalizing out the missing-value process. In particular, we demonstrate the proposed framework for the Gaussian model with arbitrary covariance structures. Comprehensive experimental studies on both synthetic and real-world RNA-seq data show the superior performance of the proposed optimal clustering with missing values when compared to various clustering *** clustering with missing values obviates the need for imputation-based pre-processing of the data, while at the same time possessing smaller clustering errors.
About ten years ago, a novel graph edit distance framework based on bipartite graph matching has been introduced. this particular framework allows the approximation of graph edit distance in cubic time. this, in turn,...
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ISBN:
(纸本)9783319589619;9783319589602
About ten years ago, a novel graph edit distance framework based on bipartite graph matching has been introduced. this particular framework allows the approximation of graph edit distance in cubic time. this, in turn, makes the concept of graph edit distance also applicable to larger graphs. In the last decade the corresponding paper has been cited more than 360 times. Besides various extensions from the methodological point of view, we also observe a great variety of applications that make use of the bipartite graph matching framework. the present paper aims at giving a first survey on these applications stemming from six different categories (which range from document analysis, over biometrics to malware detection).
Regular path queries (RPQs) are a fundamental part of recent graph query languages like SPARQL and PGQL. they allow the definition of recursive path structures through regular expressions in a declarative pattern matc...
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graphpattern matching is an important and challenging operation on graph data. Typical use cases are related to graph analytics. Since analysts are otten non-programmers, a graph system will only gain acceptance, if ...
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Representation learning is one of the foundations of Deep Learning and allowed big improvements on several Machine Learning fields, such as Neural Machine Translation, Question Answering and Speech recognition. Recent...
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the proceedings contain 13 papers. the topics discussed include: SPARQL graphpattern processing with Apache Spark;entropy-based selection of graph cuboids;cypher-basedgraphpattern matching in Gradoop;Cytosm: declar...
ISBN:
(纸本)9781450350389
the proceedings contain 13 papers. the topics discussed include: SPARQL graphpattern processing with Apache Spark;entropy-based selection of graph cuboids;cypher-basedgraphpattern matching in Gradoop;Cytosm: declarative property graph queries without data migration;can modern graph processing engines run concurrent queries?;towards a property graph generator for benchmarking;PGX.D Async : a scalable distributed graphpattern matching engine;Granula: towards fine-grained performance analysis of large-scale graph processing platforms;graphGen: adaptive graph extraction and analytics over relational databases;extending SQL for computing shortest paths;do we need specialized graph databases? benchmarking real-time social networking applications;and finding top k shortest simple paths with improved space efficiency.
In this paper, we present a novel approach that assists in the task of data-parallel patternrecognition. the classification of program code into parallel patterns relies mainly in the extraction of characteristics th...
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Here, we intend to propose a 2D contour descriptor that we call Generalized Curvature Scale Space (GCSS) based on the iso-curvature levels, and the curvature scale space (CSS) descriptor. We start by computing the cur...
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ISBN:
(纸本)9783319606545;9783319606538
Here, we intend to propose a 2D contour descriptor that we call Generalized Curvature Scale Space (GCSS) based on the iso-curvature levels, and the curvature scale space (CSS) descriptor. We start by computing the curvature in different scales and extract the points which have the same curvature values as the maximums in each scale. Each CSS image is represented by a set of key points. the Dynamic Time Warping (DTW) similarity measure is used. We reach a significant rate in image recognition using two data sets (HMM GPD and MPEG7 CE Shape-1 Part-B set).
the proceedings contain 22 papers. the special focus in this conference is on Conceptual Modeling. the topics include: Towards an ontology for strategic decision making: the Case of quality in rapid software developme...
ISBN:
(纸本)9783319706245
the proceedings contain 22 papers. the special focus in this conference is on Conceptual Modeling. the topics include: Towards an ontology for strategic decision making: the Case of quality in rapid software development projects;detecting bad smells of refinement in goal-oriented requirements analysis;Requirements engineering for data warehouses (RE4DW): From strategic goals to multidimensional model;towards formal strategy analysis with goal models and semantic web technologies;assisting process modeling by identifying business process elements in natural language texts;Using multidimensional concepts for detecting problematic Sub-KPIs in analysis systems;automatically annotating business process models with ontology concepts at design-time;OPL-ML: A modeling language for representing ontology pattern languages;Evaluating quality issues in BPMN models by extending a technical debt software platform;data modelling for dynamic monitoring of vital signs: Challenges and perspectives;utility-driven data management for data-intensive applications in fog environments;Assessing the positional planimetric accuracy of DBpedia georeferenced resources;Assessing the completeness evolution of DBpedia: A case study;towards care systems using model-driven adaptation and monitoring of autonomous multi-clouds;clustering event traces by behavioral similarity;goal-based selection of visual representations for big data analytics;A four V’s design approach of NoSQL graph databases;towards efficient and informative omni-channel customer relationship management;stream clustering of chat messages with applications to twitch streams;towards consistent demarcation of enterprise design domains.
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