rdf graph

connectivity issues for graphs: the connected component and spanning tree of undirected graphs, all vertices are by edges connected together, but There is no diagram of the loop. Figure g= (V, E) is a connected graph that divides the edge set E (g) into two sets of T (g) and B (g) When traversing the graph G from any vertex of the graph. where T (g) is the set of

Reference: Http://www.cs.ucsb.edu/~xyan/papers/gSpan.pdfHttp://www.cs.ucsb.edu/~xyan/papers/gSpan-short.pdfHttp://www.jos.org.cn/1000-9825/18/2469.pdfhttp://blog.csdn.net/coolypf/article/details/8263176more mining algorithms:https://github.com/linyiqun/DataMiningAlgorithm IntroductionGspan algorithm is an algorithm of graph mining neighborhood, and as a sub-graph mining algorithm, it is also the basis of ot

Original: http://blog.csdn.net/leolin_/article/details/7199688 Minimum Edge overlay = maximum Independent set = | v| -Maximum number of matches this is done on the original and the binary chart.The minimum path cover and the minimum side cover are different, the graph is not required to be a binary graph, but is required to be n x n the direction of the graph, ca

One: Figure of the Classification 1: No direction diagramThat is, there is no explicit pointing relationship between the two vertices, only one edge is connected, for example, a vertex and B vertex can be represented as 2: The MapThe vertices are directional, such as between A and b vertices, a points to the b,b also points to a, the two are different, if the edge is given weight, then this difference is more significant============================================================================

Graph Cut and its application in computer VisionOriginal source:Http://lincccc.blogspot.tw/2011/04/graph-cut-and-its-application-in.htmlThe network flow algorithm was originally used to solve the optimization problems of flow network, such as water pipe network, communication transmission and city traffic. Graph Cut is one of the most common algorithms used to so

Tags: Big Data System Architecture storage Graph DatabaseExcerpt from "Big Data Day know: Architecture and Algorithms" Chapter 14, book catalogue hereFor the large amount of data to be excavated, in the distributed computing environment, the first problem is how to distribute the data evenly to different servers. For non-graph data, this problem is often more intuitive to solve, because there is no independ

We introduced the tree data structure, the tree is composed of N (n>0) a finite node by connecting their edges to form a hierarchical relationship of the set, call it "tree" because it looks like an upside down tree, including two fork tree, red black tree, 2-3-4 tree , heap and other different trees, there are some of these trees do not understand can refer to my previous several blog. And this blog we will introduce another kind of data structure--diagram, diagram is the most commonly used in

For an exercise solution in this section, please refer to: HTTPS://SITES.GOOGLE.COM/SITE/ALGORITHMSSOLUTION/HOME/C22first, the concept of the graphClassification of graphs: Whether there is a ring Whether there is a heavy edge Whether there is a forward edge Simple undirected graph (simply no graph) X X X Multigraph (multiple plots) X √

Search a graph is ordered along the edge of the graph to visit all fixed points, the graph of the search algorithm can enable us to find a lot of graph structure information, Graph search technology is the core of the graph algori

Brief introductionPrevious note: TensorFlow study notes 1:get Started We talked about TensorFlow is a computing system based on graph. The nodes of the graph are made up of operations (operation), and each node of the graph is connected by tensor (Tensor) as an edge. So TensorFlow's calculation process is a tensor flow graph