FI-FG: Frequent Item Sets Mining from Datasets with High Number of Transactions by Granular Computing and Fuzzy Set Theory
المؤلفون المشاركون
Zhang, Zhong-jie
Huang, Jian
Wei, Ying
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-12-10
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
Mining frequent item set (FI) is an important issue in data mining.
Considering the limitations of those exact algorithms and sampling methods, a novel FI mining algorithm based on granular computing and fuzzy set theory (FI-GF) is proposed, which mines those datasets with high number of transactions more efficiently.
Firstly, the granularity is applied, which compresses the transactions to some granules for reducing the scanning cost.
During the granularity, each granule is represented by a fuzzy set, and the transaction scale represented by a granule is optimized.
Then, fuzzy set theory is used to compute the supports of item sets based on those granules, which faces the uncertainty brought by the granularity and ensures the accuracy of the final results.
Finally, Apriori is applied to get the FIs based on those granules and the new computing way of supports.
Through five datasets, FI-GF is compared with the original Apriori to prove its reliability and efficiency and is compared with a representative progressive sampling way, RC-SS, to prove the advantage of the granularity to the sampling method.
Results show that FI-GF not only successfully saves the time cost by scanning transactions but also has the high reliability.
Meanwhile, the granularity has advantages to those progressive sampling methods.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhang, Zhong-jie& Huang, Jian& Wei, Ying. 2015. FI-FG: Frequent Item Sets Mining from Datasets with High Number of Transactions by Granular Computing and Fuzzy Set Theory. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1074310
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhang, Zhong-jie…[et al.]. FI-FG: Frequent Item Sets Mining from Datasets with High Number of Transactions by Granular Computing and Fuzzy Set Theory. Mathematical Problems in Engineering No. 2015 (2015), pp.1-14.
https://search.emarefa.net/detail/BIM-1074310
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhang, Zhong-jie& Huang, Jian& Wei, Ying. FI-FG: Frequent Item Sets Mining from Datasets with High Number of Transactions by Granular Computing and Fuzzy Set Theory. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1074310
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1074310
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر