Graph-Theoretic Techniques for Web Content Mining

DOI10.1142/5832zbMath1077.68007OpenAlexW1551709509MaRDI QIDQ5464454

Adam Schenker, Mark Last, Abraham Kandel, Horst Bunke

Publication date: 17 August 2005

Published in: Series in Machine Perception and Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://scholarcommons.usf.edu/etd/1467

zbMATH Keywords

machine learning algorithmsrobust graph representations of data

Mathematics Subject Classification ID

Introductory exposition (textbooks, tutorial papers, etc.) pertaining to computer science (68-01) Learning and adaptive systems in artificial intelligence (68T05) Network design and communication in computer systems (68M10)

Related Items (11)

Graph characterization by counting sink star subgraphs ⋮ Recovery of missing information in graph sequences by means of reference pattern matching and decision tree learning ⋮ The hybrid representation model for web document classification ⋮ Recent advances in graph-based pattern recognition with applications in document analysis ⋮ The graph matching problem ⋮ Graph ambiguity ⋮ Modeling the Uncertainty of a Set of Graphs Using Higher-Order Fuzzy Sets ⋮ A comparative analysis of multidimensional features of objects resembling sets of graphs ⋮ Generalized median graph computation by means of graph embedding in vector spaces ⋮ Median graphs: A genetic approach based on new theoretical properties ⋮ A Recursive Embedding Approach to Median Graph Computation

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