کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4946457 1439291 2016 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Statistically-driven generation of multidimensional analytical schemas from linked data
ترجمه فارسی عنوان
تولید نسلی از طرحهای تحلیلی چند بعدی از داده های مرتبط
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
The ever-increasing Linked Data (LD) initiative has given place to open, large amounts of semi-structured and rich data published on the Web. However, effective analytical tools that aid the user in his/her analysis and go beyond browsing and querying are still lacking. To address this issue, we propose the automatic generation of multidimensional analytical stars (MDAS). The success of the multidimensional (MD) model for data analysis has been in great part due to its simplicity. Therefore, in this paper we aim at automatically discovering MD conceptual patterns that summarize LD. These patterns resemble the MD star schema typical of relational data warehousing. The underlying foundations of our method is a statistical framework that takes into account both concept and instance data. We present an implementation that makes use of the statistical framework to generate the MDAS. We have performed several experiments that assess and validate the statistical approach with two well-known and large LD sets.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 110, 15 October 2016, Pages 15-29
نویسندگان
, ,