کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10281720 | 501789 | 2015 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Efficient algorithms for mining up-to-date high-utility patterns
ترجمه فارسی عنوان
الگوریتم های کارآمد برای معادن به روز رسانی الگوهای بالا ابزار
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
High-utility pattern mining (HUPM) is an emerging topic in recent years instead of association-rule mining to discover more interesting and useful information for decision making. Many algorithms have been developed to find high-utility patterns (HUPs) from quantitative databases without considering timestamp of patterns, especially in recent intervals. A pattern may not be a HUP in an entire database but may be a HUP in recent intervals. In this paper, a new concept namely up-to-date high-utility pattern (UDHUP) is designed. It considers not only utility measure but also timestamp factor to discover the recent HUPs. The UDHUP-apriori is first proposed to mine UDHUPs in a level-wise way. Since UDHUP-apriori uses Apriori-like approach to recursively derive UDHUPs, a second UDHUP-list algorithm is then presented to efficiently discover UDHUPs based on the developed UDU-list structures and a pruning strategy without candidate generation, thus speeding up the mining process. A flexible minimum-length strategy with two specific lifetimes is also designed to find more efficient UDHUPs based on a users' specification. Experiments are conducted to evaluate the performance of the proposed two algorithms in terms of execution time, memory consumption, and number of generated UDHUPs in several real-world and synthetic datasets.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advanced Engineering Informatics - Volume 29, Issue 3, August 2015, Pages 648-661
Journal: Advanced Engineering Informatics - Volume 29, Issue 3, August 2015, Pages 648-661
نویسندگان
Jerry Chun-Wei Lin, Wensheng Gan, Tzung-Pei Hong, Vincent S. Tseng,