منابع مشابه
Bayesian Graph Edit Distance
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متن کاملMap Edit Distance vs. Graph Edit Distance for Matching Images
Generalized maps are widely used to model the topology of nD objects (such as 2D or 3D images) by means of incidence and adjacency relationships between cells (0D vertices, 1D edges, 2D faces, 3D volumes, ...). We have introduced in [1] a map edit distance. This distance compares maps by means of a minimum cost sequence of edit operations that should be performed to transform a map into another...
متن کاملSelf-organizing Graph Edit Distance
This paper addresses the issue of learning graph edit distance cost functions for numerically labeled graphs from a corpus of sample graphs. We propose a system of self-organizing maps representing attribute distance spaces that encode edit operation costs. The selforganizing maps are iteratively adapted to minimize the edit distance of those graphs that are required to be similar. To demonstra...
متن کاملEdit Distance From Graph Spectra
This paper is concerned with computing graph edit distance. One of the criticisms that can be leveled at existing methods for computing graph edit distance is that it lacks the formality and rigour of the computation of string edit distance. Hence, our aim is to convert graphs to string sequences so that standard string edit distance techniques can be used. To do this we use graph spectral seri...
متن کاملA parallel graph edit distance algorithm
Graph edit distance (GED) has emerged as a powerful and flexible graph matching paradigm that can be used to address different tasks in pattern recognition, machine learning, and data mining. GED is an error-tolerant graph matching problem which consists in minimizing the cost of the sequence that transforms a graph into another by means of edit operations. Edit operations are deletion, inserti...
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ژورنال
عنوان ژورنال: IEEE Transactions on Pattern Analysis and Machine Intelligence
سال: 2000
ISSN: 0162-8828
DOI: 10.1109/34.862201