Semantic content-based image retrieval: A comprehensive study
The complexity of multimedia contents is significantly increasing in the current digital world.
This yields an exigent demand for develo** highly effective retrieval systems to satisfy …
This yields an exigent demand for develo** highly effective retrieval systems to satisfy …
An overview of distance and similarity functions for structured data
S Ontañón - Artificial Intelligence Review, 2020 - Springer
The notions of distance and similarity play a key role in many machine learning approaches,
and artificial intelligence in general, since they can serve as an organizing principle by …
and artificial intelligence in general, since they can serve as an organizing principle by …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
Simgnn: A neural network approach to fast graph similarity computation
Graph similarity search is among the most important graph-based applications, eg finding
the chemical compounds that are most similar to a query compound. Graph …
the chemical compounds that are most similar to a query compound. Graph …
Data Mining The Text Book
C Aggarwal - 2015 - Springer
This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …
complex data types and their applications, capturing the wide diversity of problem domains …
Deep graph matching consensus
This work presents a two-stage neural architecture for learning and refining structural
correspondences between graphs. First, we use localized node embeddings computed by a …
correspondences between graphs. First, we use localized node embeddings computed by a …
Thirty years of graph matching in pattern recognition
A recent paper posed the question:" Graph Matching: What are we really talking about?". Far
from providing a definite answer to that question, in this paper we will try to characterize the …
from providing a definite answer to that question, in this paper we will try to characterize the …
Fifty years of graph matching, network alignment and network comparison
In this paper we survey methods for performing a comparative graph analysis and explain
the history, foundations and differences of such techniques of the last 50 years. While …
the history, foundations and differences of such techniques of the last 50 years. While …
A survey of graph edit distance
Inexact graph matching has been one of the significant research foci in the area of pattern
analysis. As an important way to measure the similarity between pairwise graphs error …
analysis. As an important way to measure the similarity between pairwise graphs error …
A graph distance metric based on the maximal common subgraph
H Bunke, K Shearer - Pattern recognition letters, 1998 - Elsevier
Error-tolerant graph matching is a powerful concept that has various applications in pattern
recognition and machine vision. In the present paper, a new distance measure on graphs is …
recognition and machine vision. In the present paper, a new distance measure on graphs is …