کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
378838 659225 2015 22 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Efficient repair of dimension hierarchies under inconsistent reclassification
ترجمه فارسی عنوان
تعمیر کارآمد سلسله مراتب ابعاد تحت طبقه بندی نامناسب
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

On-Line Analytical Processing (OLAP) dimensions are usually modeled as a set of elements connected by a hierarchical relationship. To ensure summarizability, a dimension is required to be strict, that is, every element of the dimension must have a unique ancestor in each of its ancestor categories. In practice, elements in a dimension are often reclassified, meaning that their rollups are changed. After this operation the dimension may become non-strict. To fix this problem, we propose to compute a set of minimal r-repairs for the new non-strict dimension. Each minimal r-repair is a strict dimension that keeps the result of the reclassification, and is obtained by performing a minimum number of insertions and deletions to the dimension graph. We show that, although in the general case finding an r-repair is NP-complete, for real-world hierarchy schemas, computing such repairs can be done in polynomial time. Further, we propose efficient heuristic-based algorithms for computing r-repairs, and discuss their computational complexity. We also perform experiments over synthetic and real-world dimensions to show the plausibility of our approach.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Data & Knowledge Engineering - Volume 95, January 2015, Pages 1–22
نویسندگان
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