Top_Keyword: An Aggregation Function for Textual Document OLAP

Authors:
Franck Ravat;Olivier Teste;Ronan Tournier;Gilles Zurfluh
Affiliations:
IRIT (UMR5505), Université de Toulouse, Toulouse Cedex 9, France F-31062;IRIT (UMR5505), Université de Toulouse, Toulouse Cedex 9, France F-31062;IRIT (UMR5505), Université de Toulouse, Toulouse Cedex 9, France F-31062;IRIT (UMR5505), Université de Toulouse, Toulouse Cedex 9, France F-31062
Venue:
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
Year:
2008

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Abstract

For more than a decade, researches on OLAP and multidimensional databases have generated methodologies, tools and resource management systems for the analysis of numeric data. With the growing availability of digital documents, there is a need for incorporating text-rich documents within multidimensional databases as well as an adapted framework for their analysis. This paper presents a new aggregation function that aggregates textual data in an OLAP environment. The Top_Keywordfunction (Top_Kwfor short) represents a set of documents by their most significant terms using a weighing function from information retrieval: tf.idf.