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289
Adaptive Duplicate Detection Using Learnable String Similarity Measures
 In Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2003
, 2003
"... The problem of identifying approximately duplicate records in databases is an essential step for data cleaning and data integration processes. Most existing approaches have relied on generic or manually tuned distance metrics for estimating the similarity of potential duplicates. In this paper, we p ..."
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Cited by 344 (14 self)
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present a framework for improving duplicate detection using trainable measures of textual similarity. We propose to employ learnable text distance functions for each database field, and show that such measures are capable of adapting to the specific notion of similarity that is appropriate for the field
Expander Flows, Geometric Embeddings and Graph Partitioning
 IN 36TH ANNUAL SYMPOSIUM ON THE THEORY OF COMPUTING
, 2004
"... We give a O( log n)approximation algorithm for sparsest cut, balanced separator, and graph conductance problems. This improves the O(log n)approximation of Leighton and Rao (1988). We use a wellknown semidefinite relaxation with triangle inequality constraints. Central to our analysis is a ..."
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Cited by 312 (18 self)
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We give a O( log n)approximation algorithm for sparsest cut, balanced separator, and graph conductance problems. This improves the O(log n)approximation of Leighton and Rao (1988). We use a wellknown semidefinite relaxation with triangle inequality constraints. Central to our analysis is a
Comparing Stars: On Approximating Graph Edit Distance
, 2009
"... Graph data have become ubiquitous and manipulating them based on similarity is essential for many applications. Graph edit distance is one of the most widely accepted measures to determine similarities between graphs and has extensive applications in the fields of pattern recognition, computer visio ..."
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Cited by 29 (0 self)
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Graph data have become ubiquitous and manipulating them based on similarity is essential for many applications. Graph edit distance is one of the most widely accepted measures to determine similarities between graphs and has extensive applications in the fields of pattern recognition, computer
Fast Approximation of Centrality
 Journal of Graph Algorithms and Applications
, 2001
"... Social studies researchers use graphs to model group activities in social networks. An important property in this context is the centrality of a vertex: the inverse of the average distance to each other vertex. We describe a randomized approximation algorithm for centrality in weighted graphs. For g ..."
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Cited by 55 (0 self)
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Social studies researchers use graphs to model group activities in social networks. An important property in this context is the centrality of a vertex: the inverse of the average distance to each other vertex. We describe a randomized approximation algorithm for centrality in weighted graphs
Coil sensitivity encoding for fast MRI. In:
 Proceedings of the ISMRM 6th Annual Meeting,
, 1998
"... New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementa ..."
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Cited by 193 (3 self)
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space, sensitivity encoding by means of a receiver array permits reduction of the number of Fourier encoding steps. This is achieved by increasing the distance of sampling positions in kspace while maintaining the maximum kvalues. Thus scan time is reduced at preserved spatial resolution. The factor by which
ClosureTree: An Index Structure for Graph Queries
, 2006
"... Graphs have become popular for modeling structured data. As a result, graph queries are becoming common and graph indexing has come to play an essential role in query processing. We introduce the concept of a graph closure, a generalized graph that represents a number of graphs. Our indexing techniq ..."
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Cited by 92 (1 self)
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graphs that are similar to a query graph. For subgraph queries, we propose a technique called pseudo subgraph isomorphism which approximates subgraph isomorphism with high accuracy. For similarity queries, we measure graph similarity through edit distance using heuristic graph mapping methods. We
The betweenness centrality of a graph
, 2007
"... A measure of the centrality of a vertex of a graph is the portion of shortest paths crossing through it between other vertices of the graph. This is called betweenness centrality and here we study some of its general properties, relations with distance parameters (diameter, mean distance), local par ..."
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A measure of the centrality of a vertex of a graph is the portion of shortest paths crossing through it between other vertices of the graph. This is called betweenness centrality and here we study some of its general properties, relations with distance parameters (diameter, mean distance), local
Whom You Know Matters: Venture Capital Networks and Investment Performance,
 Journal of Finance
, 2007
"... Abstract Many financial markets are characterized by strong relationships and networks, rather than arm'slength, spotmarket transactions. We examine the performance consequences of this organizational choice in the context of relationships established when VCs syndicate portfolio company inv ..."
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Cited by 138 (8 self)
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graph theory, a mathematical discipline widely used in economic sociology. 2 Graph theory provides us with tools for describing networks at a "macro" level and for measuring the relative importance, or "centrality," of each actor in the network. Our centrality measures capture five
Finding Approximate Patterns in Undirected Acyclic Graphs
 Pattern Recognition
, 2002
"... We consider an approximate pattern matching problem for undirected acyclic graphs. Specifically, let P be a pattern graph, D a data graph and t an integer. We present an algorithm to locate a subgraph in D whose distance from P is at most t. The distance measure used here is the degree2 metric publ ..."
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Cited by 11 (2 self)
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We consider an approximate pattern matching problem for undirected acyclic graphs. Specifically, let P be a pattern graph, D a data graph and t an integer. We present an algorithm to locate a subgraph in D whose distance from P is at most t. The distance measure used here is the degree2 metric
Improved Approximate Pattern Matching on Hypertext
 In Proc. LATIN'98, LNCS 1380
, 1998
"... . The problem of approximate pattern matching on hypertext is defined and solved by Amir et al. in O(m(n log m + e)) time, where m is the length of the pattern, n is the total text size and e is the total number of edges. Their space complexity is O(mn). We present a new algorithm which is O(mk(n + ..."
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Cited by 9 (3 self)
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(mk(n + e)) time and needs only O(n) extra space, where k ! m is the number of allowed errors in the pattern. If the graph is acyclic, our time complexity drops to O(m(n + e)), improving Amir's results. 1 Introduction Approximate string matching problems appear in a number of important areas related
Results 1  10
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289