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Certified Machine-Learning Models Read chapter Read first chapter

2020 | OriginalPaper | Chapter

The HyperBagGraph DataEdron: An Enriched Browsing Experience of Datasets

Track: Foundation of Data Science and Engineering

Authors : Xavier Ouvrard, Jean-Marie Le Goff, Stéphane Marchand-Maillet

Published in: SOFSEM 2020: Theory and Practice of Computer Science

Publisher: Springer International Publishing

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Abstract

Traditional verbatim browsers give back information linearly according to a ranking performed by a search engine that may not be optimal for the surfer. The latter may need to assess the pertinence of the information retrieved, particularly when s\(\cdot \)he wants to explore other facets of a multi-facetted information space. Simultaneous facet visualisation can help to gain insights into the information retrieved and call for further refined searches. Facets are potentially heterogeneous co-occurrence networks, built choosing at least one reference type, and modeled by HyperBag-Graphs—families of multisets on a given universe. References allow to navigate inside the dataset and perform visual queries. The approach is illustrated on Arxiv scientific pre-prints searches.

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previous chapter Selection of a Green Logical Data Warehouse Schema by Anti-monotonicity Constraint
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Appendix
Available only for authorised users
Footnotes
1
We denote \(\mathfrak {A}_{m}=\left\{ x_{i}^{m_{i}}:i\in [\![n]\!]\right\} \) where \(m_{i}=m\left( x_{i}\right) \) a mset \(\mathfrak {A}_{m}=\left( A,m\right) \) of universe \(A=\left\{ x_{i}:i\in [\![n]\!]\right\} ,\) of multiplicity function m and of support \(\mathfrak {A}_{m}^{\star }=\left\{ x_{i}:m_{i}\ne 0\right\} .\)
 
2
We use fraktur font for multisets and hb-graphs: \(\mathfrak {A}:A,\mathfrak {e}:e,\mathfrak {E}:E,\mathfrak {H}:H\).
 
3
Metadata of interest for visualisation or referencing are in italic.
 
4
\(\Sigma _{\rho }\big /\mathcal {R}\) is the quotient set of \(\Sigma _{\rho }\) by \(\mathcal {R}\).
 
5
A video demo is available on: https://​www.​infos-informatique.​net.
 
Literature
1.
Ranganathan, S.R.: Elements of Library Classification. Asia Publishing House, Mumbai (1962)
2.
Ouvrard, X., Le Goff, J.-M., Marchand-Maillet, S.: Adjacency and tensor representation in general hypergraphs. part 2: multisets, hb-graphs and related e-adjacency tensors. arXiv preprint arXiv:​1805.​11952 (2018)
3.
Ouvrard, X., Le Goff, J.-M., Marchand-Maillet, S.: Diffusion by exchanges in hb-graphs: highlighting complex relationships extended version. arXiv:​1809.​00190v2 (2019)
4.
Ouvrard, X., Le Goff, J., Marchand-Maillet, S.: Hypergraph modeling and visualisation of complex co-occurence networks. Electron. Notes Discrete Math. 70, 65–70 (2018)MathSciNetCrossRef
5.
Dörk, M., Riche, N.H., Ramos, G., Dumais, S.: PivotPaths: strolling through faceted information spaces. IEEE Trans. Vis. Comput. Graph. 18(12), 2709–2718 (2012)CrossRef
6.
Zhao, J., Collins, C., Chevalier, F., Balakrishnan, R.: Interactive exploration of implicit and explicit relations in faceted datasets. IEEE Trans. Vis. Comput. Graph. 19(12), 2080–2089 (2013)CrossRef
7.
Agocs, A., Dardanis, D., Le Goff, J.-M., Proios, D.: Interactive graph query language for multidimensional data in collaboration spotting visual analytics framework. ArXiv e-prints, December 2017
8.
Indyk, P., Motwani, R.: Approximate nearest neighbors: towards removing the curse of dimensionality. In: Proceedings of the Thirtieth Annual ACM Symposium on Theory of Computing, pp. 604–613. ACM (1998)
Metadata
Title
The HyperBagGraph DataEdron: An Enriched Browsing Experience of Datasets
Authors
Xavier Ouvrard
Jean-Marie Le Goff
Stéphane Marchand-Maillet
Copyright Year
2020
Book
SOFSEM 2020: Theory and Practice of Computer Science

Print ISBN: 978-3-030-38918-5

Electronic ISBN: 978-3-030-38919-2

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-38919-2_30

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