André Lourenço, Liliana Medina, Ana Fred, Joaquim Filipe


Unsupervised organisation of documents, and in particular research papers, into meaningful groups is a difficult problem. Using the typical vector-space-model representation (Bag-of-words paradigm), difficulties arise due to its intrinsic high dimensionality, high redundancy of features, and the lack of semantic information. In this work we propose a document representation relying on a statistical feature reduction step, and an enrichment phase based on the introduction of higher abstraction terms, designated as metaterms, derived from text, using as prior knowledge papers topics and keywords. The proposed representation, combined with a clustering ensemble approach, leads to a novel document organization strategy. We evaluate the proposed approach taking as application domain conference papers, topic information being extracted from conference topics or areas. Performance evaluation on data sets from NIPS and INSTICC conferences show that the proposed approach leads to interesting and encouraging results.


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Paper Citation

in Harvard Style

Lourenço A., Medina L., Fred A. and Filipe J. (2011). UNSUPERVISED ORGANISATION OF SCIENTIFIC DOCUMENTS . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: SSTM, (IC3K 2011) ISBN 978-989-8425-79-9, pages 549-560. DOI: 10.5220/0003722905570568

in Bibtex Style

author={André Lourenço and Liliana Medina and Ana Fred and Joaquim Filipe},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: SSTM, (IC3K 2011)},

in EndNote Style

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: SSTM, (IC3K 2011)
SN - 978-989-8425-79-9
AU - Lourenço A.
AU - Medina L.
AU - Fred A.
AU - Filipe J.
PY - 2011
SP - 549
EP - 560
DO - 10.5220/0003722905570568