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graph-based information modeling

Brain network modeling based on Mutual Information and Graph Theory for predicting the connection mechanism in the development of Alzheimer’s disease

Brain network modeling based on Mutual Information and Graph Theory for predicting the connection mechanism in the development of Alzheimer’s disease

... In the current work, we study the changes of network properties for a further investigation of the fundamental rule that causes the formation of AD network topologies. Prior models such as ECM, AA, and PA, estimated the ...

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A knowledge-based approach for keywords modeling into a semantic graph

A knowledge-based approach for keywords modeling into a semantic graph

... to information gained from analyzing a large corpus of documents; Or ii) graph-based, which quantify semantic relatedness of words using information derived from semantic networks or knowledge ...

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An Empirical Investigation of Structured Output Modeling for Graph based Neural Dependency Parsing

An Empirical Investigation of Structured Output Modeling for Graph based Neural Dependency Parsing

... put modeling is weaker, the improvements brought by the global model generally get ...input modeling, the parser can gen- erally benefit more from structured output model- ...input modeling can make ...

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Strengthening IoT WSN Architecture for Environmental Monitoring

Strengthening IoT WSN Architecture for Environmental Monitoring

... IoT based wireless sensor ...the information among the ...Networks Based on Bipartite-Flow Graph Modeling [12], Application-aware end-to-end delay and message loss estimation in ...

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Graph based transforms based on prediction inaccuracy modeling for pathology image coding

Graph based transforms based on prediction inaccuracy modeling for pathology image coding

... The Graph-Based Transform (GBT) has been recently shown to attain promising results for data de-correlation and energy ...underlying graph structure, which can accurately reflect the correlation ...

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Sequence-to-sequence modeling for graph representation learning

Sequence-to-sequence modeling for graph representation learning

... learn graph representations for the graph classification ...not based solely on the graph ...of Graph Neural Networks (GNNs) and rely on the idea of message propagation around the ...

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Graph-based Data Modeling and Analysis for Data Fusion in Remote Sensing

Graph-based Data Modeling and Analysis for Data Fusion in Remote Sensing

... borhood information are combined into a third order tensor ...analysis based algorithms NTD and NTF, and three multilinear subspace learning based algorithms MPCA, TLPP and TNPE, are introduced for ...

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An Effective Method for Utility Preserving Social Network Graph Anonymization Based on Mathematical Modeling

An Effective Method for Utility Preserving Social Network Graph Anonymization Based on Mathematical Modeling

... private information are gathered in social ...the graph are considered by Ying and Wu ...method based on k- ...anonymity. Based on the definition, a graph G = (V, E) is called (k, l)- ...

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ECCENTRICITY BASED ZAGREB INDICES OF BISMUTH TRI-IODIDE

ECCENTRICITY BASED ZAGREB INDICES OF BISMUTH TRI-IODIDE

... a graph, where V is a non-empty set of vertices and E is a set of ...chemical graph theory applies graph theory to mathematical modeling of molecular phenomena, which is helpful for the study ...

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Graph based Local Coherence Modeling

Graph based Local Coherence Modeling

... Grammatical information associated with each entity is extracted automatically thanks to the Stanford parser using dependency conversion (de Marneffe et ...bipartite graph are defined following the ...

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Scientific Papers Retrieval with an Emphasis on Graph-based Structural Information

Scientific Papers Retrieval with an Emphasis on Graph-based Structural Information

... In recent years, along with introducing and developing concepts such as semantic web, machine learning, data mining, text processing and etc. some new approaches have been considered for information retrieval. In ...

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Implementation of Efficient Keyword Search in Relational Databases

Implementation of Efficient Keyword Search in Relational Databases

... In the literature, the existing works are categorized into schemabased approaches and schema-free approaches for (structural) keyword search. The schema-based approaches process a keyword query in two steps, ...

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The Combination between the Individual Factors and the Collective Experience for Ultimate Optimization Learning Path using Ant Colony Algorithm

The Combination between the Individual Factors and the Collective Experience for Ultimate Optimization Learning Path using Ant Colony Algorithm

... On each arc of our graph, we define an initialization pheromone value that represents the distinction given by the teaching team in an arc. More the value of these pheromones is essential; the teaching staff ...

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Relation Aware Entity Alignment for Heterogeneous Knowledge Graphs

Relation Aware Entity Alignment for Heterogeneous Knowledge Graphs

... relation information of KGs. Although the relational graph convolutional networks (RGCNs) [Schlichtkrull et ...Dual-Primal Graph Con- volutional Networks (DPGCNN) [Monti et ...the graph and ...

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Information Theoretic Graph Kernels

Information Theoretic Graph Kernels

... of graph entropies with that of using a depth-based representation to develop a novel depth-based complexity trace for a ...a graph into substructures ...the information content flow ...

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Technical Meeting on Preparation of a Guidance Document on Life Cycle Management of Design Knowledge November 2014, Vienna, Austria

Technical Meeting on Preparation of a Guidance Document on Life Cycle Management of Design Knowledge November 2014, Vienna, Austria

... and information system for nuclear power units, based on 3D modeling, within the Rosenergoatom corporate information system, for the period from 2010 to 2020”, systematic development of 3D ...

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Graph based Semi Supervised Model for Joint Chinese Word Segmentation and Part of Speech Tagging

Graph based Semi Supervised Model for Joint Chinese Word Segmentation and Part of Speech Tagging

... A statistical analysis of the segmentation and tag- ging results of the supervised joint model (Base- line II) and our model is carried out to comprehend the influence of the graph-based semi-supervised ...

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The Dynamic to Static Conversion of Dynamic Fault Trees Using Stochastic Dependency Graphs and Stochastic Activity Networks

The Dynamic to Static Conversion of Dynamic Fault Trees Using Stochastic Dependency Graphs and Stochastic Activity Networks

... Medium level models are used to represent the behavior and the fault logic of the system. The behavioral model is built using the knowledge contained in the DG model. A special class of GSPN—Stochastic Activity Networks ...

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Volume 16: International Conference on Graph Transformation 2008 - Doctoral Symposium

Volume 16: International Conference on Graph Transformation 2008 - Doctoral Symposium

... One of the next goals is stronger and more direct tool support, using internal data structures of editors to get rid of the need for explicit reading and writing files. This implies the need of direct access to an API ...

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Speech Act Based Communication and Information Modeling with Demo

Speech Act Based Communication and Information Modeling with Demo

... The first step in the DEMO analysis of the Conciliation Board for Consumers is the description of the activities at the essential level. This means that the business is described as a ne[r] ...

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