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Authors: Marilena Ditta ; Fabrizio Milazzo ; Valentina Ravì ; Giovanni Pilato and Agnese Augello

Affiliation: ICAR CNR, Italy

Keyword(s): Latent Semantic Analysis, Triplet Extraction.

Abstract: This work proposes a data driven methodology for the extraction of subject-verb-object triplets from a text corpus. Previous works on the field solved the problem by means of complex learning algorithms requiring hand-crafted examples; our proposal completely avoids learning triplets from a dataset and is built on top of a well-known baseline algorithm designed by Delia Rusu et al.. The baseline algorithm uses only syntactic information for generating triplets and is characterized by a very low precision i.e., very few triplets are meaningful. Our idea is to integrate the semantics of the words with the aim of filtering out the wrong triplets, thus increasing the overall precision of the system. The algorithm has been tested over the Reuters Corpus and has it as shown good performance with respect to the baseline algorithm for triplet extraction.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Ditta, M.; Milazzo, F.; Ravì, V.; Pilato, G. and Augello, A. (2015). Data-driven Relation Discovery from Unstructured Texts. In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - DART; ISBN 978-989-758-158-8; ISSN 2184-3228, SciTePress, pages 597-602. DOI: 10.5220/0005614205970602

@conference{dart15,
author={Marilena Ditta. and Fabrizio Milazzo. and Valentina Ravì. and Giovanni Pilato. and Agnese Augello.},
title={Data-driven Relation Discovery from Unstructured Texts},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - DART},
year={2015},
pages={597-602},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005614205970602},
isbn={978-989-758-158-8},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) - DART
TI - Data-driven Relation Discovery from Unstructured Texts
SN - 978-989-758-158-8
IS - 2184-3228
AU - Ditta, M.
AU - Milazzo, F.
AU - Ravì, V.
AU - Pilato, G.
AU - Augello, A.
PY - 2015
SP - 597
EP - 602
DO - 10.5220/0005614205970602
PB - SciTePress