کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6855265 | 1437610 | 2018 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A weighted N-list-based method for mining frequent weighted itemsets
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: A weighted N-list-based method for mining frequent weighted itemsets A weighted N-list-based method for mining frequent weighted itemsets](/preview/png/6855265.png)
چکیده انگلیسی
Mining frequent itemsets (FIs) is an important problem in the field of data mining, and thus there have been many different methods proposed to solve this problem. However, mining FIs usually works on binary databases and has a limitation that is only concerned with the appearance of items regardless of their importance. In practical applications, items often have different importance depending on their values or meanings, and that leads to the emergence of weighted databases. In this paper, we propose a new method for mining frequent weighted itemsets (FWIs) from a weighted database by using the weighted N-list structure (WN-list), an extension of the N-list. Some theorems are proposed to calculate the weighted supports of itemsets fast, and then an algorithm is built based on these theorems for efficiently mining FWIs. The experimental results show that the proposed method outperforms existing methods, especially when run on very large and sparse databases.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 96, 15 April 2018, Pages 388-405
Journal: Expert Systems with Applications - Volume 96, 15 April 2018, Pages 388-405
نویسندگان
Huong Bui, Bay Vo, Ham Nguyen, Tu-Anh Nguyen-Hoang, Tzung-Pei Hong,