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In this paper, we propose a methodology for providing linguistic answers to queries involving the comparison of time series obtained from data cubes with time dimension. Time series related to events which are interesting for the user are obtained by querying data cubes using OnLine Analytical Processing (OLAP) operations on the time dimension. The comparison of these query results can be summarized so that an appropriate short linguistic description of the series is provided to the user. Our approach is based on linguistically quantified statements and pointwise definitions of the degree and sign of local change. Our linguistic summaries are well suited to be included in an interface layer of a data warehouse system, improving the quality of humanmachine interaction and the understandability of the results. C 2011 Wiley Periodicals, Inc.

In this paper, the use of an evolutionary approach when obtaining linguistic summaries from time series data is proposed. We assume the availability of a hierarchical partition of the time dimension in the time series. The use of natural language allows the human users to understand the resulting summaries in an easy way. The number of possible final summaries and the different ways of measuring their quality has taken us to adopt the use of a multi objective evolutionary algorithm. We compare the results of the new approach with our previous greedy algorithms.

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