کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6857912 | 664775 | 2014 | 20 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Parallel attribute reduction algorithms using MapReduce
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Attribute reduction is the key technique for knowledge acquisition in rough set theory. However, it is still a challenging task to perform attribute reduction on massive data. During the process of attribute reduction on massive data, the key to improving the reduction efficiency is the effective computation of equivalence classes and attribute significance. Aiming at this problem, we propose several parallel attribute reduction algorithms in this paper. Specifically, we design a novel structure of ãkey,valueã pair to speed up the computation of equivalence classes and attribute significance and parallelize the traditional attribute reduction process based on MapReduce mechanism. The different parallelization strategies of attribute reduction are also compared and analyzed from the theoretic view. Abundant experimental results demonstrate the proposed parallel attribute reduction algorithms can perform efficiently and scale well on massive data.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 279, 20 September 2014, Pages 671-690
Journal: Information Sciences - Volume 279, 20 September 2014, Pages 671-690
نویسندگان
Jin Qian, Duoqian Miao, Zehua Zhang, Xiaodong Yue,