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Authors: Carmelo Spiccia ; Agnese Augello and Giovanni Pilato

Affiliation: Istituto di Calcolo e Reti ad Alte Prestazioni (ICAR) and Italian National Research Council (CNR), Italy

ISBN: 978-989-758-158-8

Keyword(s): Word Prediction, Posgram, Part of Speech Prediction, Two Steps Prediction, Missing Word, Sentence Completion.

Abstract: Several word prediction algorithms have been described in literature for automatic sentence completion from a finite candidate words set. However, at the best of our knowledge, very little or no work has been done on reducing the cardinality of this set. To address this issue, we use posgrams to predict the part of speech of the missing word first. Candidate words are then restricted to the ones fulfilling the predicted part of speech. We show how this additional step can improve the processing speed and the accuracy of word predictors. Experimental results are provided for the Italian language.

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Paper citation in several formats:
Spiccia, C.; Augello, A. and Pilato, G. (2015). Posgram Driven Word Prediction.In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: DART, (IC3K 2015) ISBN 978-989-758-158-8, pages 589-596. DOI: 10.5220/0005613305890596

@conference{dart15,
author={Carmelo Spiccia. and Agnese Augello. and Giovanni Pilato.},
title={Posgram Driven Word Prediction},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: DART, (IC3K 2015)},
year={2015},
pages={589-596},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005613305890596},
isbn={978-989-758-158-8},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: DART, (IC3K 2015)
TI - Posgram Driven Word Prediction
SN - 978-989-758-158-8
AU - Spiccia, C.
AU - Augello, A.
AU - Pilato, G.
PY - 2015
SP - 589
EP - 596
DO - 10.5220/0005613305890596

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