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Similarity graphs
 In Proceedings of ISMIS’03, volume LNAI 2871
, 2003
"... Abstract. The focus of this paper is approaches to measuring similarity for application in contentbased query evaluation. Rather than only comparing at the level of words, the issue here is conceptual resemblance. The basis is a knowledge base defining major concepts of the domain and may include t ..."
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Cited by 8 (0 self)
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Abstract. The focus of this paper is approaches to measuring similarity for application in contentbased query evaluation. Rather than only comparing at the level of words, the issue here is conceptual resemblance. The basis is a knowledge base defining major concepts of the domain and may include
Growth of selfsimilar graphs
, 2001
"... Abstract. Locally finite selfsimilar graphs with bounded geometry and without bounded geometry as well as nonlocally finite selfsimilar graphs are characterized by the structure of their cell graphs. Geometric properties concerning the volume growth and distances in cell graphs are discussed. The ..."
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Cited by 13 (3 self)
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Abstract. Locally finite selfsimilar graphs with bounded geometry and without bounded geometry as well as nonlocally finite selfsimilar graphs are characterized by the structure of their cell graphs. Geometric properties concerning the volume growth and distances in cell graphs are discussed
Growth of SelfSimilar Graphs
, 2002
"... Abstract: Locally finite selfsimilar graphs with bounded geometry and without bounded geometry as well as nonlocally finite selfsimilar graphs are characterized by the structure of their cell graphs. Geometric properties concerning the volume growth and distances in cell graphs are discussed. The ..."
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Abstract: Locally finite selfsimilar graphs with bounded geometry and without bounded geometry as well as nonlocally finite selfsimilar graphs are characterized by the structure of their cell graphs. Geometric properties concerning the volume growth and distances in cell graphs are discussed
Growth of selfsimilar graphs
, 2002
"... Geometric properties of selfsimilar graphs concerning their volume growth and distances in certain finite subgraphs are discussed. The length scaling factor ν and the volume scaling factor µ can be defined similarly to the corresponding parameters of continuous selfsimilar sets. There are differen ..."
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Geometric properties of selfsimilar graphs concerning their volume growth and distances in certain finite subgraphs are discussed. The length scaling factor ν and the volume scaling factor µ can be defined similarly to the corresponding parameters of continuous selfsimilar sets
Books in graphs
, 2008
"... A set of q triangles sharing a common edge is called a book of size q. We write β (n, m) for the the maximal q such that every graph G (n, m) contains a book of size q. In this note 1) we compute β ( n, cn 2) for infinitely many values of c with 1/4 < c < 1/3, 2) we show that if m ≥ (1/4 − α) ..."
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Cited by 2380 (22 self)
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A set of q triangles sharing a common edge is called a book of size q. We write β (n, m) for the the maximal q such that every graph G (n, m) contains a book of size q. In this note 1) we compute β ( n, cn 2) for infinitely many values of c with 1/4 < c < 1/3, 2) we show that if m ≥ (1/4 − α
Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching
, 2002
"... Matching elements of two data schemas or two data instances plays a key role in data warehousing, ebusiness, or even biochemical applications. In this paper we present a matching algorithm based on a fixpoint computation that is usable across different scenarios. The algorithm takes two graphs (sch ..."
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Cited by 575 (12 self)
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Matching elements of two data schemas or two data instances plays a key role in data warehousing, ebusiness, or even biochemical applications. In this paper we present a matching algorithm based on a fixpoint computation that is usable across different scenarios. The algorithm takes two graphs
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
Efficient similarity search in sequence databases
, 1994
"... We propose an indexing method for time sequences for processing similarity queries. We use the Discrete Fourier Transform (DFT) to map time sequences to the frequency domain, the crucial observation being that, for most sequences of practical interest, only the first few frequencies are strong. Anot ..."
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Cited by 505 (21 self)
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We propose an indexing method for time sequences for processing similarity queries. We use the Discrete Fourier Transform (DFT) to map time sequences to the frequency domain, the crucial observation being that, for most sequences of practical interest, only the first few frequencies are strong
Results 1  10
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