On Information Granulation via Data Clustering for Granular Computing-Based Pattern Recognition: A Graph Embedding Case Study

On Information Granulation via Data Clustering for Granular Computing-Based Pattern Recognition: A Graph Embedding Case Study

Granular Computing is a powerful information processing paradigm, particularly useful for the synthesis of pattern recognition systems in structured domains (e.g., graphs or sequences). According to this paradigm, granules of information play the pivotal role of describing the underlying (possibly c...

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Bibliographic Details
Main Authors: Alessio Martino, Luca Baldini, Antonello Rizzi
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Algorithms
Subjects:
structural pattern recognition
supervised learning
graph classification
inexact graph matching
granular computing
information granulation
Online Access:https://www.mdpi.com/1999-4893/15/5/148

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