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gSpan: GraphBased Substructure Pattern Mining
, 2002
"... We investigate new approaches for frequent graphbased pattern mining in graph datasets and propose a novel algorithm called gSpan (graphbased Substructure pattern mining) , which discovers frequent substructures without candidate generation. gSpan builds a new lexicographic order among graphs, and ..."
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Cited by 639 (34 self)
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, and maps each graph to a unique minimum DFS code as its canonical label. Based on this lexicographic order, gSpan adopts the depthfirst search strategy to mine frequent connected subgraphs efficiently. Our performance study shows that gSpan substantially outperforms previous algorithms, sometimes
Community detection in graphs
, 2009
"... The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of th ..."
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Cited by 801 (1 self)
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The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices
Spanning Eulerian Subgraphs in clawfree graphs
"... A graph is clawfree if it has no induced K1,3 subgraph. A graph is essential 4edgeconnected if removing at most three edges, the resulting graph has at most one component having edges. In this note, we show that every essential 4edgeconnected claw free graph has a spanning Eulerian subgraph with ..."
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Cited by 1 (1 self)
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A graph is clawfree if it has no induced K1,3 subgraph. A graph is essential 4edgeconnected if removing at most three edges, the resulting graph has at most one component having edges. In this note, we show that every essential 4edgeconnected claw free graph has a spanning Eulerian subgraph
Frequent Subgraph Discovery
, 2001
"... Over the years, frequent itemset discovery algorithms have been used to solve various interesting problems. As data mining techniques are being increasingly applied to nontraditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the requirement of th ..."
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Cited by 407 (14 self)
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of these domains. An alternate way of modeling the objects in these data sets, is to use a graph to model the database objects. Within that model, the problem of finding frequent patterns becomes that of discovering subgraphs that occur frequently over the entire set of graphs. In this paper we present a
Labor Contracts as Partial Gift Exchange
 Quarterly Journal of Economics
, 1982
"... This paper explains involuntary unemployment in terms of the response of firms to workers ' group behavior. Workers ' effort depends upon the norms determining a fair day's work. In order to affect those norms, firms may pay more than the marketclearing wage. Industries that pay cons ..."
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Cited by 762 (1 self)
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This paper explains involuntary unemployment in terms of the response of firms to workers ' group behavior. Workers ' effort depends upon the norms determining a fair day's work. In order to affect those norms, firms may pay more than the marketclearing wage. Industries that pay consistently more than the marketclearing wage are primary, and those that pay only the marketclearing wage are secondary. Thus, this paper also gives a theory for division of labor markets between primary and secondary. I.
A Framework for Dynamic Graph Drawing
 CONGRESSUS NUMERANTIUM
, 1992
"... Drawing graphs is an important problem that combines flavors of computational geometry and graph theory. Applications can be found in a variety of areas including circuit layout, network management, software engineering, and graphics. The main contributions of this paper can be summarized as follows ..."
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Cited by 627 (44 self)
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Drawing graphs is an important problem that combines flavors of computational geometry and graph theory. Applications can be found in a variety of areas including circuit layout, network management, software engineering, and graphics. The main contributions of this paper can be summarized
Factor Graphs and the SumProduct Algorithm
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 1998
"... A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple c ..."
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Cited by 1787 (72 self)
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A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple
Interprocedural Slicing Using Dependence Graphs
 ACM TRANSACTIONS ON PROGRAMMING LANGUAGES AND SYSTEMS
, 1990
"... ... This paper concerns the problem of interprocedural slicinggenerating a slice of an entire program, where the slice crosses the boundaries of procedure calls. To solve this problem, we introduce a new kind of graph to represent programs, called a system dependence graph, which extends previou ..."
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Cited by 822 (85 self)
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... This paper concerns the problem of interprocedural slicinggenerating a slice of an entire program, where the slice crosses the boundaries of procedure calls. To solve this problem, we introduce a new kind of graph to represent programs, called a system dependence graph, which extends
The program dependence graph and its use in optimization
 ACM Transactions on Programming Languages and Systems
, 1987
"... In this paper we present an intermediate program representation, called the program dependence graph (PDG), that makes explicit both the data and control dependence5 for each operation in a program. Data dependences have been used to represent only the relevant data flow relationships of a program. ..."
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Cited by 989 (3 self)
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In this paper we present an intermediate program representation, called the program dependence graph (PDG), that makes explicit both the data and control dependence5 for each operation in a program. Data dependences have been used to represent only the relevant data flow relationships of a program
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