کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
385462 660866 2015 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An improved algorithm for mining class association rules using the difference of Obidsets
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
An improved algorithm for mining class association rules using the difference of Obidsets
چکیده انگلیسی


• Difference of Obidsets (d2O) is developed.
• Obidset can be replaced by d2O to compute the support of itemsets.
• Sorting strategy is derived for fast computing d2O of itemsets.
• An algorithm for fast mining CARs using d2O is also developed.

Class association rules play an important role in decision support systems and have thus been extensively studied. Recently, an efficient algorithm for mining class association rules, named CAR-Miner, has been proposed. It, however, consumes a lot of memory for storing the Obidsets (sets of object identifiers that contain itemsets) of itemsets and requires a lot of time to compute the intersection between two Obidsets, especially in the large datasets. This paper proposes an improved algorithm for mining class association rules that uses the difference between two Obidsets (d2O) to save memory usage and run time. Firstly, the d2O concept is developed. A strategy for reducing the storage space and computation time of d2O is then derived. Experimental results show that the proposed algorithm is more efficient than CAR-Miner in terms of run time and memory usage.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 42, Issue 9, 1 June 2015, Pages 4361–4369
نویسندگان
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