کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
391105 661343 2008 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Mining multiple-level fuzzy blocks from multidimensional data
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Mining multiple-level fuzzy blocks from multidimensional data
چکیده انگلیسی

Multidimensional databases are now recognized as being the standard way to store aggregated and historized data. Multidimensional databases are designed to store information on measures (also known as indicators) regarding a set of dimensions. One important issue in this framework is the identification of homogeneous areas in data cubes, which allows users to summarize and visualize the data through the main trends they contain. In our previous work, we have proposed a levelwise approach to mine homogeneous areas of the data, called blocks that can be interpreted, for instance, as If product is Chocolate and month is between January and March and city is London or Paris, then the number of sales is 5. However, in this work, the information provided by the hierarchies defined over the dimensions is not taken into account. In this paper, we consider the case where measure values are discretized using a fuzzy partition, and we extend our method so as to mine multiple-level fuzzy blocks, that is, blocks that are defined using hierarchies and that characterize fuzzy measure values. Moreover, in order to avoid redundancies in the output set of blocks, only the most specific ones (according to hierarchies) are computed. We show that our algorithms are linear in the size of the cube, thus providing an efficient method for summarizing data cubes.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Fuzzy Sets and Systems - Volume 159, Issue 12, 16 June 2008, Pages 1535-1553