Clustering view-segmented documents via tensor modeling

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Abstract

We propose a clustering framework for view-segmented documents, i.e., relatively long documents made up of smaller fragments that can be provided according to a target set of views or aspects. The framework is designed to exploit a view-based document segmentation into a third-order tensor model, whose decomposition result would enable any standard document clustering algorithm to better reflect the multi-faceted nature of the documents. Experimental results on document collections featuring paragraph-based, metadata-based, or user-driven views have shown the significance of the proposed approach, highlighting performance improvement in the document clustering task. © 2014 Springer International Publishing.

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APA

Romeo, S., Tagarelli, A., & Ienco, D. (2014). Clustering view-segmented documents via tensor modeling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8502 LNAI, pp. 385–394). Springer Verlag. https://doi.org/10.1007/978-3-319-08326-1_39

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