The Experts below are selected from a list of 9540 Experts worldwide ranked by ideXlab platform
Jianwei Wu - One of the best experts on this subject based on the ideXlab platform.
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cd graph planar graph representation for spatial adjacency and Neighbourhood Relation with constraints
International Journal of Geographical Information Science, 2013Co-Authors: Chongcheng Chen, Jianwei WuAbstract:Neighbourhood Relational graphs are widely used in Geosciences. Given a set of spatial objects vertices in the plane together with a set of spatial obstacles and spatial facilitators in straight-line edges, the constrained Delaunay graph CD-graph is an undirected graph representing the spatial adjacency and Neighbourhood Relation of objects. CD-graph is an approximated triangulation of vertices with the following properties: 1 the obstacles are included in the graph as some barrier edges that block the connection of the objects on both sides of the obstacles, and the facilitators are included in the graph as some nontrivial edges that connect the objects that are broken by the obstacles; 2 it is as close as possible to the Delaunay triangulation D-TIN. CD-graph can be used to represent the spatial adjacency and Neighbourhood Relation of objects with constraints. A theoretical contrast is conducted to differentiate CD-graph, arbitrary unconstrained D-TIN and constrained D-TIN. Meanwhile, a two-step constraint-embedding algorithm is proposed to build CD-graph in optimal time by using divide-and-conquer technique. Subsequently, the Voronoi diagram and D-TIN-based k-order neighbours is extended in CD-graph to express different scales of spatial adjacency and Neighbourhood Relation of objects. CD-graph can be widely used in geographical applications, such as spatial interpolation, spatial clustering and spatial decision support.
Chongcheng Chen - One of the best experts on this subject based on the ideXlab platform.
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cd graph planar graph representation for spatial adjacency and Neighbourhood Relation with constraints
International Journal of Geographical Information Science, 2013Co-Authors: Chongcheng Chen, Jianwei WuAbstract:Neighbourhood Relational graphs are widely used in Geosciences. Given a set of spatial objects vertices in the plane together with a set of spatial obstacles and spatial facilitators in straight-line edges, the constrained Delaunay graph CD-graph is an undirected graph representing the spatial adjacency and Neighbourhood Relation of objects. CD-graph is an approximated triangulation of vertices with the following properties: 1 the obstacles are included in the graph as some barrier edges that block the connection of the objects on both sides of the obstacles, and the facilitators are included in the graph as some nontrivial edges that connect the objects that are broken by the obstacles; 2 it is as close as possible to the Delaunay triangulation D-TIN. CD-graph can be used to represent the spatial adjacency and Neighbourhood Relation of objects with constraints. A theoretical contrast is conducted to differentiate CD-graph, arbitrary unconstrained D-TIN and constrained D-TIN. Meanwhile, a two-step constraint-embedding algorithm is proposed to build CD-graph in optimal time by using divide-and-conquer technique. Subsequently, the Voronoi diagram and D-TIN-based k-order neighbours is extended in CD-graph to express different scales of spatial adjacency and Neighbourhood Relation of objects. CD-graph can be widely used in geographical applications, such as spatial interpolation, spatial clustering and spatial decision support.
Cavique Luís - One of the best experts on this subject based on the ideXlab platform.
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Proverbs knowledge discovery in the virtual social network due to common knowledge of proverbs
'University of Aden - Faculty of Economics and Administration', 2010Co-Authors: Mendes, Armando B., Funk Matthias, Cavique LuísAbstract:DMIN - The 6th International Conference on Data Mining, Las Vegas, July 12-15, 2010In a series of interviews, it was collected a heterogeneous set of several million Relations of positive and negative knowledge that a group of thousands of people has about a set of circa twenty-two thousand Portuguese Proverbs. This is a unique source for socio-cultural analysis of the mechanisms of transmission of oral culture in geographic discontinuous spaces. We present in this article some results on the problem of finding a homomorphism between proverbial knowledge and geographical locations. To find this Relation, we chose an approach based on the Analysis of social networks where the broadcast of oral culture, at least historically, could be interpreted as a trace of direct social contact between some of their users. We can simply give the Hamming Distance between two people by comparing their proverbial knowledge and, then, choose for every person only those Relations to a peer where this distance is minimal. The resulting graph is analysed by a new Clique Analysis procedure, proposed in this work, design to work on very dense networks. The procedure was tested on a subset of data and we found that there are clusters where the Neighbourhood Relation inducted by the minimum Hamming Distance could be a reflex of the geographical distribution and of some migration flux of the Azorean population. When we compare the cliques with high geographic proximity, we found some proverbs which are good discriminators between the different clusters
Siyuan Jing - One of the best experts on this subject based on the ideXlab platform.
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a universal Neighbourhood rough sets model for knowledge discovering from incomplete heterogeneous data
Expert Systems, 2013Co-Authors: Siyuan JingAbstract:Neighbourhood rough set theory has proven already, as an efficient tool for knowledge discovering from heterogeneous data. However, some types of the data are incomplete and noisy in practical environments, such as signal analysis, fault diagnosis etc. To solve this problem, a universal Neighbourhood rough sets model variable precision tolerance Neighbourhood rough sets [VPTNRS] model is proposed based on a tolerance Neighbourhood Relation and the probabilistic theory. The proposed model can be inducing a family of much more comprehensive information granules to characterize arbitrary concepts in complex universe. In this paper, we discussed the properties of the model as well as some important relevant theorems are also introduced and proved. Furthermore, a heuristic heterogeneous feature selection algorithm is given based on the model. The experimental results with 10 choices University of California Irvine UCI standard data sets showed that the universal model performed well both in feature selection and classification, especially in incomplete environment.
Mendes, Armando B. - One of the best experts on this subject based on the ideXlab platform.
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Proverbs knowledge discovery in the virtual social network due to common knowledge of proverbs
'University of Aden - Faculty of Economics and Administration', 2010Co-Authors: Mendes, Armando B., Funk Matthias, Cavique LuísAbstract:DMIN - The 6th International Conference on Data Mining, Las Vegas, July 12-15, 2010In a series of interviews, it was collected a heterogeneous set of several million Relations of positive and negative knowledge that a group of thousands of people has about a set of circa twenty-two thousand Portuguese Proverbs. This is a unique source for socio-cultural analysis of the mechanisms of transmission of oral culture in geographic discontinuous spaces. We present in this article some results on the problem of finding a homomorphism between proverbial knowledge and geographical locations. To find this Relation, we chose an approach based on the Analysis of social networks where the broadcast of oral culture, at least historically, could be interpreted as a trace of direct social contact between some of their users. We can simply give the Hamming Distance between two people by comparing their proverbial knowledge and, then, choose for every person only those Relations to a peer where this distance is minimal. The resulting graph is analysed by a new Clique Analysis procedure, proposed in this work, design to work on very dense networks. The procedure was tested on a subset of data and we found that there are clusters where the Neighbourhood Relation inducted by the minimum Hamming Distance could be a reflex of the geographical distribution and of some migration flux of the Azorean population. When we compare the cliques with high geographic proximity, we found some proverbs which are good discriminators between the different clusters
