Book ChapterDOI
Supervised encoding of graph-of-graphs for classification and regression problems
Shu Jia Zhang,Markus Hagenbuchner,Franco Scarselli,Ah Chung Tsoi +3 more
- pp 449-461
TLDR
This paper presents some preliminary results which show that the classification performance is already close to those provided by the state-of-the-art ones, and experimental results on a relatively large scale real world problem indicate that the learning is efficient.Abstract:
This paper introduces a novel approach for processing a general class of structured information, viz., a graph of graphs structure, in which each node of the graph can be described by another graph, and each node in this graph, in turn, can be described by yet another graph, up to a finite depth. This graph of graphs description may be used as an underlying model to describe a number of naturally and artificially occurring systems, e.g. nested hypertexted documents. The approach taken is a data driven method in that it learns from a set of examples how to classify the nodes in a graph of graphs. To the best of our knowledge, this is the first time that a machine learning approach is enabled to deal with such structured problem domains. Experimental results on a relatively large scale real world problem indicate that the learning is efficient. This paper presents some preliminary results which show that the classification performance is already close to those provided by the state-of-the-art ones.read more
Citations
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Journal ArticleDOI
Protein complex analysis: From raw protein lists to protein interaction networks
Pieter Meysman,Kevin Titeca,Sven Eyckerman,Jan Tavernier,Bart Goethals,Lennart Martens,Dirk Valkenborg,Kris Laukens +7 more
TL;DR: An overview of the most commonly used computational methods to process and interpret co-complex results is given, and the issues and unsolved problems that still exist within the field are discussed.
Book ChapterDOI
Overview of the INEX 2009 XML mining track: clustering and classification of XML documents
Richi Nayak,Christopher M. De Vries,Sangeetha Kutty,Shlomo Geva,Ludovic Denoyer,Patrick Gallinari +5 more
TL;DR: The objectives, datasets and evaluation criteria of both the clustering and classification tasks set in the INEX 2009 XML Mining Track were explained in this article, and the approaches and results obtained by the different participants were described.
Journal ArticleDOI
Analysis techniques for illicit Bitcoin transactions
TL;DR: This comprehensive overview of analysis techniques for illicit Bitcoin transactions addresses both technical, machine learning approaches as well as a non-technical, legal, and governance considerations.
Dissertation
Document clustering algorithms, representations and evaluation for information retrieval
De Vries,M Christopher +1 more
TL;DR: This thesis presents new methods for classification and thematic grouping of billions of web pages, at scales previously not achievable, in what is also known as document clustering.
Approximation contexts in addressing graph data structures
TL;DR: The author lists the publications, books, films, articles, photographs and other items related to “Abbreviations of the Year” that were published in 2016.
References
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Proceedings Article
TextRank: Bringing Order into Text
Rada Mihalcea,Paul Tarau +1 more
TL;DR: TextRank, a graph-based ranking model for text processing, is introduced and it is shown how this model can be successfully used in natural language applications.
Journal ArticleDOI
Computational Capabilities of Graph Neural Networks
TL;DR: The functions that can be approximated by GNNs, in probability, up to any prescribed degree of precision are described, and includes most of the practically useful functions on graphs.
Journal ArticleDOI
A self-organizing map for adaptive processing of structured data
TL;DR: This work proposes the first fully unsupervised model, namely an extension of traditional self-organizing maps (SOMs), for the processing of labeled directed acyclic graphs (DAGs) by using the unfolding procedure adopted in recurrent and recursive neural networks.
Book
Comparative Evaluation of XML Information Retrieval Systems: 5th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2006 Dagstuhl Castle, Germany, December 17-20, 2006 Revised and Selected Papers
TL;DR: This paper focuses on the development of a model for a transfer function of the HITS Algorithm for XML Retrieval, which automates the very labor-intensive and therefore time-heavy and expensive process of manually cataloging and decrypting XML documents.
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