Results 11  20
of
1,357
Extracting LargeScale Knowledge Bases From the Web
 Proceedings of the 25th VLDB Conference
, 1999
"... The subject of this paper is the creation of knowledge bases by enumerating and organizing all web occurrences of certain subgraphs. We focus on subgraphs that are signatures of web phenomena such as tightlyfocused topic communities, webrings, taxonomy trees, keiretsus, etc. For instance, the ..."
Abstract

Cited by 121 (2 self)
 Add to MetaCart
, the signature of a webring is a central page with bidirectional links to a number of other pages. We develop novel algorithms for such enumeration problems. A key technical contribution is the development of a model for the evolution of the web graph, based on experimental observations derived from a
Sharp Thresholds of Graph properties, and the ksat Problem
 J. Amer. Math. Soc
, 1998
"... Given a monotone graph property P , consider p (P ), the probability that a random graph with edge probability p will have P . The function d p (P )=dp is the key to understanding the threshold behavior of the property P . We show that if d p (P )=dp is small (corresponding to a nonsharp thres ..."
Abstract

Cited by 210 (7 self)
 Add to MetaCart
sharp threshold), then there is a list of graphs of bounded size such that P can be approximated by the property of having one of the graphs as a subgraph. One striking consequences of this result is that a coarse threshold for a random graph property can only happen when the value of the critical edge
An efficient algorithm for discovering frequent subgraphs
 IEEE Transactions on Knowledge and Data Engineering
, 2002
"... Abstract — Over the years, frequent itemset discovery algorithms have been used to find interesting patterns in various application areas. However, as data mining techniques are being increasingly applied to nontraditional domains, existing frequent pattern discovery approach cannot be used. This i ..."
Abstract

Cited by 120 (7 self)
 Add to MetaCart
problem is as that of discovering subgraphs that occur frequently over the entire set of graphs. In this paper we present a computationally efficient algorithm, called FSG, for finding all frequent subgraphs in large graph datasets. We experimentally evaluate the performance of FSG using a variety of real
Efficient subgraph matching on billion node graphs
 In PVLDB
, 2012
"... The ability to handle large scale graph data is crucial to an increasing number of applications. Much work has been dedicated to supporting basic graph operations such as subgraph matching, reachability, regular expression matching, etc. In many cases, graph indices are employed to speed up query pr ..."
Abstract

Cited by 33 (5 self)
 Add to MetaCart
The ability to handle large scale graph data is crucial to an increasing number of applications. Much work has been dedicated to supporting basic graph operations such as subgraph matching, reachability, regular expression matching, etc. In many cases, graph indices are employed to speed up query
PowerGraph: Distributed GraphParallel Computation on Natural Graphs
"... Largescale graphstructured computation is central to tasks ranging from targeted advertising to natural language processing and has led to the development of several graphparallel abstractions including Pregel and GraphLab. However, the natural graphs commonly found in the realworld have highly ..."
Abstract

Cited by 128 (4 self)
 Add to MetaCart
Largescale graphstructured computation is central to tasks ranging from targeted advertising to natural language processing and has led to the development of several graphparallel abstractions including Pregel and GraphLab. However, the natural graphs commonly found in the realworld have highly
Spectral segmentation with multiscale graph decomposition
 In CVPR
, 2005
"... We present a multiscale spectral image segmentation algorithm. In contrast to most multiscale image processing, this algorithm works on multiple scales of the image in parallel, without iteration, to capture both coarse and fine level details. The algorithm is computationally efficient, allowing to ..."
Abstract

Cited by 185 (3 self)
 Add to MetaCart
to segment large images. We use the Normalized Cut graph partitioning framework of image segmentation. We construct a graph encoding pairwise pixel affinity, and partition the graph for image segmentation. We demonstrate that large image graphs can be compressed into multiple scales capturing image structure
Arboricity and Bipartite Subgraph Listing Algorithms
, 1994
"... In graphs of bounded arboricity, the total complexity of all maximal complete bipartite subgraphs is O(n). We describe a linear time algorithm to list such subgraphs. The arboricity bound is necessary: for any constant k and any n there exists an nvertex graph with O(n) edges and (n/ log n) k ..."
Abstract

Cited by 41 (4 self)
 Add to MetaCart
In graphs of bounded arboricity, the total complexity of all maximal complete bipartite subgraphs is O(n). We describe a linear time algorithm to list such subgraphs. The arboricity bound is necessary: for any constant k and any n there exists an nvertex graph with O(n) edges and (n/ log n) k
HipG: Parallel Processing of LargeScale Graphs
"... Distributed processing of realworld graphs is challenging duetotheirsizeandtheinherentirregularstructureofgraph computations. We present HipG, a distributed framework that facilitates programming parallel graph algorithms by composing the parallel application automatically from the userdefined pie ..."
Abstract

Cited by 12 (1 self)
 Add to MetaCart
Distributed processing of realworld graphs is challenging duetotheirsizeandtheinherentirregularstructureofgraph computations. We present HipG, a distributed framework that facilitates programming parallel graph algorithms by composing the parallel application automatically from the user
SeriesParallel Subgraphs of Planar Graphs
"... In this paper we show that every 3connected (3edgeconnected) planar graph contains a 2connected (respectively, 2edgeconnected) spanning partial 2tree (seriesparallel) graph. In contrast, a recent result by [4] implies that not all 3connected graphs contain 2edgeconnected seriesparallel s ..."
Abstract
 Add to MetaCart
In this paper we show that every 3connected (3edgeconnected) planar graph contains a 2connected (respectively, 2edgeconnected) spanning partial 2tree (seriesparallel) graph. In contrast, a recent result by [4] implies that not all 3connected graphs contain 2edgeconnected seriesparallel
Graph sketches: sparsification, spanners, and subgraphs
 In PODS
, 2012
"... When processing massive data sets, a core task is to construct synopses of the data. To be useful, a synopsis data structure should be easy to construct while also yielding good approximations of the relevant properties of the data set. A particularly useful class of synopses are sketches, i.e., tho ..."
Abstract

Cited by 46 (10 self)
 Add to MetaCart
.e., those based on linear projections of the data. These are applicable in many models including various parallel, stream, and compressed sensing settings. A rich body of analytic and empirical work exists for sketching numerical data such as the frequencies of a set of entities. Our work investigates graph
Results 11  20
of
1,357