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4.5. Related publications
Year: 2006
Abstract: The performance of document clustering systems depends on employing
optimal text representations, which are not only difficult to determine beforehand,
but also may vary from one clustering problem to another. As a first step towards
building robust document clusterers, a strategy based on feature diversity and cluster
ensembles is presented in this work. Experiments conducted on a binary clustering
problem show that our method is robust to near-optimal model order selection and
able to detect constructive interactions between different document representations in
the test bed.
A subsequent extension of this work was published at the Journal of the Spanish Society
for Natural Language Processing (Procesamiento del Lenguaje Natural) after its presentation
at the SEPLN 2006 conference held at Zaragoza.
Authors: Xavier Sevillano, Germán Cobo, Francesc Alías and Joan Claudi Socoró
Title: Robust Document Clustering by Exploiting Feature Diversity in Cluster Ensembles
In: Journal of the Spanish Society for Natural Language Processing (Procesamiento
del Lenguaje Natural)
Volume: 37
Pages: 169176
Year: 2006
Abstract: The performance of document clustering systems is conditioned by the use
of optimal text representations, which are not only difficult to determine beforehand,
but also may vary from one clustering problem to another. This work presents an
approach based on feature diversity and cluster ensembles as a first step towards
building document clustering systems that behave robustly across different clustering
problems. Experiments conducted on three binary clustering problems of increasing
difficulty show that the proposed method is i) robust to near-optimal model order
selection, and ii) able to detect constructive interactions between different document
representations, thus being capable of yielding consensus clusterings superior to any
of the individual clusterings available.
Last, a global analysis regarding clustering indeterminacies and how they can be overcome
via cluster ensembles was presented at the ICA 2007 conference as an oral presentation.
Authors: Xavier Sevillano, Germán Cobo, Francesc Alías and Joan Claudi Socoró
Title: Text Clustering on Latent Thematic Spaces: Variants, Strenghts and Weaknesses
In: Proceedings of 7th International Conference on Independent Component Analysis
and Signal Separation
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