Topic Oriented Auto-completion Models - Approaches Towards Fastening Auto-completion Systems

Stefan Prisca, Mihaela Dinsoreanu, Camelia Lemnaru

2015

Abstract

In this paper we propose an autocompletion approach suitable for mobile devices that aims to reduce the overall data model size and to speed up query processing while not employing any language specific processing. The approach relies on topic information from input documents to split the data models based on topics and index them in a way that allows fast identification through their corresponding topic. Doing so, the size of the data model used for prediction is decreased to almost one fifth of the size of a model that contains all topics, and the query processing becomes two times faster, while maintaining the same precision obtained by employing a model that contains all topics.

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Paper Citation


in Harvard Style

Prisca S., Dinsoreanu M. and Lemnaru C. (2015). Topic Oriented Auto-completion Models - Approaches Towards Fastening Auto-completion Systems . In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015) ISBN 978-989-758-158-8, pages 241-248. DOI: 10.5220/0005597502410248

in Bibtex Style

@conference{kdir15,
author={Stefan Prisca and Mihaela Dinsoreanu and Camelia Lemnaru},
title={Topic Oriented Auto-completion Models - Approaches Towards Fastening Auto-completion Systems},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015)},
year={2015},
pages={241-248},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005597502410248},
isbn={978-989-758-158-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2015)
TI - Topic Oriented Auto-completion Models - Approaches Towards Fastening Auto-completion Systems
SN - 978-989-758-158-8
AU - Prisca S.
AU - Dinsoreanu M.
AU - Lemnaru C.
PY - 2015
SP - 241
EP - 248
DO - 10.5220/0005597502410248