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Authors: Mustapha Bouakkaz 1 ; Sabine Loudcher 2 and Youcef Ouinten 1

Affiliations: 1 University of Laghouat, Algeria ; 2 University of Lyon 2, France

ISBN: 978-989-758-096-3

Keyword(s): OLAP, Textual Data, Aggregation Function, Google Similrity.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Data Mining ; Data Warehouses and OLAP ; Databases and Information Systems Integration ; Enterprise Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: With the tremendous growth of unstructured data in the Business Intelligence, there is a need for incorporating textual data into data warehouses, to provide an appropriate multidimensional analysis (OLAP) and develop new approaches that take into account the textual content of data. This will provide textual measures to users who wish to analyse documents online. In this paper, we propose a new aggregation function for textual data in an OLAP context. For aggregating keywords, our contribution is to use a data mining technique, such as kmeans, but with a distance based on the Google similarity distance. Thus our approach considers the semantic similarity of keywords for their aggregation. The performance of our approach is analyzed and compared to another method using the k-bisecting clustering algorithm and based on the Jensen-Shannon divergence for the probability distributions. The experimental study shows that our approach achieves better performances in terms of recall, precisio n,F-measure complexity and runtime. (More)

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Paper citation in several formats:
Bouakkaz, M.; Loudcher, S. and Ouinten, Y. (2015). GOTA - Using the Google Similarity Distance for OLAP Textual Aggregation.In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-096-3, pages 121-127. DOI: 10.5220/0005357201210127

@conference{iceis15,
author={Mustapha Bouakkaz. and Sabine Loudcher. and Youcef Ouinten.},
title={GOTA - Using the Google Similarity Distance for OLAP Textual Aggregation},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2015},
pages={121-127},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005357201210127},
isbn={978-989-758-096-3},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - GOTA - Using the Google Similarity Distance for OLAP Textual Aggregation
SN - 978-989-758-096-3
AU - Bouakkaz, M.
AU - Loudcher, S.
AU - Ouinten, Y.
PY - 2015
SP - 121
EP - 127
DO - 10.5220/0005357201210127

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